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Mereenie WM26 Spuds
The well is being drilled by Ensign Australia Pty Ltd using its Ensign 932 Drilling Rig.
The well aims to access the known gas that exists in the Stairway formation which overlies the present producing zones in the Mereenie Oil & Gas Field. It is designed to take advantage of the naturally fractured sandstone.
The WM26 drilling program anticipates a 36 day drilling timeline to reach a total depth of 2,915 metres MD (measure depth) with a vertical depth of 1,242 metres TVD (total vertical depth) and a horizontal reservoir section of up to 1,481 metres.
About Central Petroleum Limited
Central Petroleum Limited (ASX:CTP) is an oil and gas explorer and producer listed on the Australian Securities Exchange focused on supplying the domestic gas market. Central is advancing several separate projects across what is regarded as the biggest package of proven and prospective oil and gas acreage across central Australia. This spread of assets gives Central multiple options for growth and development. 88% of this land being gas prone has led to the Company's focus on becoming a major domestic gas producer.
Central Petroleum Limited

subset: commoncrawl


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Descripción de la oferta
- Sin Experiencia
- Sin estudios
- Salario a negociar
- Temuco
We are searching for a decisive, driven Admissions Director to lead our admissions department as we examine, define, and conduct our admissions process and promote our school to prospective students and their guardians. The Admissions Director will help establish and update our procedures and criteria, work with potential students to determine their eligibility, and oversee the admissions process as we evaluate applications and issues decisions. You will also plan and oversee promotional activities and schedule or conduct tours, student interviews, and information sessions.
To be a successful Admissions Director, you should be committed to promoting your school and attracting top talent. You should be engaging, highly organized, and analytical with exceptional communication skills.
Admissions Director Responsibilities:
Helping colleges, universities, and other academic institutions establish, examine, alter, and explain admissions guidelines, processes, and requirements.
Assisting in the admissions decision making process as student applications are evaluated and accepted or denied.
Providing students, parents, and guardians with information regarding admissions requirements and processes, financial aid applications, enrollment issues, or other procedures.
Engaging in the recruiting process by planning, coordinating, and overseeing promotional events, campus tours, student interviews, and other admissions activities.
Reviewing and interpreting student information, including test scores, extracurricular activities, and grades.
Communicating changes, statistics, and other information to the school president, registrar, and department heads.
Directing, hiring, and coaching admissions staff members.
Admissions Director Requirements:
Master's degree in Education or related field, Doctorate may be preferred.
Extensive experience in education or admissions.
Understanding of statistics, admissions requirements and procedures, school funding, and financial aid application processes.
Experience with specific schools may be a major plus.
Ability to analyze and interpret information.
Strong interpersonal, presentation, networking, and verbal and written communication skills.
Proficiency with computers.
Some sales and marketing skills may prove beneficial.
Sobre la empresa
We enable our clients to become better employers by designing, deploying, maintaining and operating HR as a service. Our HR business process services cover workforce management, time and attendance, local, regional and global payroll, talent administration, and people analytics.
Changing lives for people through creating opportunity to reach potential.
Empresas en el sector
CLB Consultoresa
Santiago Centro, Metropolitana de Santiago
Tiro associates Ltda
Mercuri Urvala
Cascais, Lisboa
- Bechtel Corporation
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- Caterpillar
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Empresas destacadas
- Comerciales y Vendedores
- Informáticos
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- Profesores y educadores
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text:
PRESS RELEASE – The Paintco Lady Strykers' Alexy Barbe came through in the clutch with a goal two minutes before the final whistle to break a 2-2 tie and secure her team's win over the dck Masters on opening day of the 2012 Bud Light Women's 7-A-Side League at the Guam Football Association facility in Harmon.
The Lady Strykers switched gears in the second half, scoring the three goals the team needed to overcome a 2-0 advantage the Masters held by halftime.
Barbe opened scoring for the Lady Strykers capitalizing on a one-on-one opportunity with dck's goalkeeper Jamie Skornia five minutes into the second half. Skornia initially came out of the box to approach Barbe, but at the last minute retreated. By the time Skornia decided to again approach the ball, Barbe was able to send her shot to the back of the net.
The Lady Strykers' Caroline Quigley scored the game equalizer just a minute later, taking a pass from Barbe on the right side and shooting successfully to the opposite post.
After over 20 scoreless minutes, the Lady Strykers found their best opportunity to break the tie when Mia Santos passed the ball to Barbe who was unmarked near the left wing. Barbe avoided Skornia's slide tackle in front of the goal to send in her shot successfully for the eventual game-winner. The game – played in a two 30-minute half format – ended before the Masters could manage a second-half goal.
The Masters initially held a 2-0 lead on a pair of Jaime Fahy goals in the 8th and 19th minute before the halftime whistle.
In other matches, the Doosan Crushers shut out Pika Soccer Club 10-0. Anjelica Perez finished with a hat trick and teammate Kristin Thompson scored twice. Andrea Odell, Tatyana Ungacta, Simie Willter and Kim Sherman also scored for the Crushers. The Crushers' other goal came on a Pika own goal right before halftime.
Quality Distributors was the day's other winning team after Guam Shipyard forfeited its first game.
League matches continue Saturday at 2:15 p.m. at the GFA mini pitch when the Lady Strykers take on Shipyard. Quality goes up against the Crushers at 3:30 p.m. and Pika faces Hyundai at 4:45 p.m.
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- Software
- Open Access
PhyloFacts: an online structural phylogenomic encyclopedia for protein functional and structural classification
- Nandini Krishnamurthy1,
- Duncan P Brown1,
- Dan Kirshner1 and
- Kimmen Sjölander1Email author
© Krishnamurthy et al.; licensee BioMed Central Ltd. 2006
- Received: 8 May 2006
- Accepted: 14 September 2006
- Published: 14 September 2006
The Berkeley Phylogenomics Group presents PhyloFacts, a structural phylogenomic encyclopedia containing almost 10,000 'books' for protein families and domains, with pre-calculated structural, functional and evolutionary analyses. PhyloFacts enables biologists to avoid the systematic errors associated with function prediction by homology through the integration of a variety of experimental data and bioinformatics methods in an evolutionary framework. Users can submit sequences for classification to families and functional subfamilies. PhyloFacts is available as a worldwide web resource from http://phylogenomics.berkeley.edu/phylofacts.
- Gene Ontology
- Additional Data File
- Protein Structure Prediction
- Protein Function Prediction
- Evidence Code
Computational methods for protein function prediction have been critical in the post-genome era in the functional annotation of literally millions of novel sequences. The standard protocol for sequence functional annotation - transferring the annotation of a database hit to a sequence 'query' based on predicted homology - has been shown to be prone to systematic error [1–3]. The top hit in a sequence database may have a different function to the query due to neofunctionalization stemming from gene duplication [4], differences in domain structure [5, 6], mutations at key functional positions, or speciation [1]. Annotation errors have been shown to propagate through databases by the application of homology-based annotation transfer [7–9]. While the exact frequency of annotation error is unknown (one published estimate is 8% or higher [7]), the importance of detecting and correcting existing errors and preventing future errors is undisputed.
An additional complicating factor in annotation transfer by homology is the complete failure of this approach for an average of 30% of the genes in most genomes sequenced: in some cases no homologs can be detected within a particular significance threshold, for instance, a BLAST [10] expectation (E) value (that is, the number of hits receiving a given score expected by chance alone in the database searched) of 0.001 or less, while in other cases database hits may be labeled as 'hypothetical' or 'unknown'.
With the huge array of bioinformatics software tools and resources available, it might seem unthinkable that functional annotation accuracy would be so difficult to ensure. Rather like the parable of the blind men and the elephant, each tool used separately provides a partial and imperfect picture; taken as a whole, the probable molecular function of the protein, biological process, cellular component, interacting partners, and other aspects of a protein's function can often come into better focus. For instance, annotation transfer from the top BLAST hit may suggest a protein is a receptor-like protein kinase, while domain structure prediction reveals that no kinase domain is present; the two orthogonal analyses prevent mis-annotation of the unknown protein.
In this paper we present PhyloFacts, an online structural phylogenomics encyclopedia containing almost 10,000 'books' for protein families and domains, designed to improve the accuracy and specificity of protein function prediction [11]. PhyloFacts integrates a wide array of biological data and informatics methods for protein families, organized on the basis of structural similarity and by evolutionary relationships. This enables a biologist to examine a rich array of experimental data and bioinformatics predictions for a protein family, and to quickly and accurately infer the function of a protein in an evolutionary context.
Annotation accuracy requires data and method integration
PhyloFacts is motivated by two of the biggest lessons of the post-genome era - the power of integrating data and inference tools from different sources, and improved prediction accuracy using consensus approaches in bioinformatics. For instance, protein structure prediction 'meta-servers' making predictions based on a consensus over results retrieved from several independent servers typically have lower error rates than any one server used separately [12]. In the case of protein structure prediction, we can also take advantage of the fact that members of a large diverse protein family tend to share the same three-dimensional structure even when their primary sequence similarity becomes undetectable. This enables us to use another type of consensus approach involving the application of the same method to several different members of the family to boost prediction accuracy (for example, [13]).
We employ the same basic principles in this resource, by integrating many different prediction methods and sources of experimental data over an evolutionary tree. In cases where attributes are known to persist over long evolutionary distances (such as protein three-dimensional structure), we can integrate predictions over the entire tree to derive a consensus prediction for the family as a whole. In cases where attributes are more restricted in their distribution in the family (for example, ligand recognition among G-protein coupled receptors), inferences will be more circumspect, potentially restricted to strict orthologs. Evolutionary and structural clustering of proteins enables us to integrate these disparate types of data and inference methods effectively, to identify potential errors in database annotations and provide a platform to improve the accuracy of functional annotation overall.
In addition to new methods developed by us for phylogenomic inference, PhyloFacts includes a number of standard bioinformatics methods available publicly. To motivate the need for protein functional classification integrating diverse methods and data in an evolutionary framework, we examine the major classes of bioinformatics methods in turn, and discuss their different pros and cons. Methods designed for predicting the biological process(es) in which a protein participates (for example, bioinformatics approaches such as Phylogenetic Profiles [14] and Rosetta Stone [15], analysis of DNA chip array data, and proteomics experiments such as pull-down experiments, yeast two-hybrid data, and so on) are clearly complementary, and will be included in future releases of the PhyloFacts resource.
Database homolog search tools
Database homolog search tools (for example, BLAST, FASTA [16], and so on) can be blindingly fast, but do not distinguish between local matches and sequences sharing global similarity; they report a score or E-value measuring the significance of the local match between a query sequence and sequences in the database. This can lead to errors when annotations are transferred in toto based on only local similarity. These pairwise sequence comparison methods of homolog detection have also been shown to have limited effectiveness at recognizing remote homologs (distantly related sequences) [17].
Iterated homology search methods
Iterated homology search methods such as PSI-BLAST [10] have been developed in recent years. These methods enable larger numbers of sequences to be annotated functionally, albeit with a potentially higher error rate due to divergence in function from their common ancestor.
Domain-based annotation and protein structure prediction
Domain-based annotation and protein structure prediction libraries of profiles or hidden Markov models (HMMs) for functional or structural domains (PFAM [18], SMART [19], or Superfamily [20]) are particularly helpful when a homolog search fails. There are two primary limitations of this approach to functional annotation. First, these statistical models of protein families and domains are typically designed for sensitivity rather than specificity, and thus afford a fairly coarse level of annotation. For example, the PFAM 7TM_1 HMM recognizes a variety of G-protein coupled receptors, irrespective of their ligand specificity. Second, a protein's function is a composite of all its constituent domains; thus, even in cases where each of a protein's domains can be identified, the actual function of the protein may not be elucidated.
Phylogenomic inference
Phylogenomic inference was originally designed to address the problem of annotation transfer from paralogous rather than orthologous genes through the construction and analysis of phylogenetic trees overlaid with experimental data. This approach has been shown to enable the highest accuracy in prediction of protein molecular function [21–23], but inherent technical and computational complexity has limited its use. Several attempts at identification of orthologs (for example, Orthostrapper [24] and RIO [25]) and at automating phylogenomic inference of molecular function [26] have been presented, and may lead to more widespread application of this approach.
Prediction of protein localization
Prediction of protein localization is enabled by resources such as the TMHMM [27] transmembrane prediction server, the TargetP [28] cellular component prediction server, and the PHOBIUS [29] integrated signal peptide and transmembrane prediction server. These provide another perspective on a protein's function, and can suggest participation in biological pathways when other data are lacking. Because these methods can rely on fairly weak and non-specific signals (for example, hydrophobic stretches as indicators of membrane localization), both false positive and false negative predictions are not uncommon [30].
The PhyloFacts phylogenomic encyclopedia
As of 11 July 2006, the PhyloFacts encyclopedia contains 9,710 'books' for protein superfamilies and structural domains. Each book in the PhyloFacts resource contains heterogeneous data for protein families, including a cluster of homologous proteins, multiple sequence alignment, one or more phylogenetic trees, predicted three-dimensional structures, predicted functional subfamilies, taxonomic distributions, Gene Ontology (GO) annotations [31], PFAM domains, hyperlinks to key literature and other online resources, and annotations provided by biologist experts. Residues conferring family and subfamily specificity are predicted using alignment/evolutionary analyses; these patterns are plotted on three-dimensional structures. HMMs constructed for each family and subfamily enable classification of novel sequences to different functional classes. Details on each aspect of the resource construction are available in the 'Details on Library Construction and Software Tools' section.
Distribution of various book types in PhyloFacts
Book type
No. of books in PhyloFacts
Global homology group
Conserved region
The PhyloFacts phylogenomic resource can be used in several ways: sequences can be submitted for protein structure prediction or functional classification, protein family books can be browsed, and data of various types (multiple sequence alignments (MSAs), phylogenetic trees, HMMs, and so on) can be downloaded from the resource.
Browsing PhyloFacts
Sequence analysis
PhyloFacts includes books focusing on specific protein families or classes. The largest of these series is the PhyloFacts 'Protein Structure Prediction' library, with 5,328 books, each representing either a structural domain from the Astral database [34] or protein structures from the Protein Data Bank (PDB [35]). This series enables biologists to obtain predicted structures for submitted proteins. The books in the Protein Structure Prediction library were created using individual structural domains as seeds, gathering homologs from the NR [36] database using PSI-BLAST or the UCSC SAM [37] software tools.
The second major book series in PhyloFacts is the 'Animal Proteome Explorer' library, containing 4,226 protein families in the human genome, expanded to include additional homologs from other organisms. Specialized sections of the Animal Proteome Explorer series are devoted to protein families of particular biomedical relevance: G-Protein Coupled Receptors (65 books), Ion Channels (50 books), and Innate Immunity (52 books). The Animal Proteome Explorer series has been constructed using GHGCluster (see section 'Details on Library Construction and Software Tools'). The GPCR library includes books for protein families based on the classification of the GPCRDB [38].
The 'Plant Disease Resistance Phylogenomic Explorer' forms the third main series of specialized books in PhyloFacts, devoted to protein families involved in plant disease resistance and host-pathogen interaction (105 books). Families in this series include the canonical plant R (resistance) genes, proteins involved in defense signaling and effector proteins from plant pathogens.
These three main divisions are not strictly distinct, and there are some overlaps. For instance, a book for the Toll Interleukin Receptor (TIR) domain (PhyloFacts book ID: bpg002615) is placed in the Protein Structure Prediction library (due to the presence of a solved structure for this family) as well as in the Innate Immunity and Plant Disease Resistance libraries (since TIR domains are found in both plant and animal proteins involved in eukaryotic innate immunity).
Because our recommended protocol for protein function prediction starts with transfer of annotation from globally alignable orthologs (see section 'Functional annotation using PhyloFacts'), a large number of books in PhyloFacts are designated as type Global Homology, and subjected to rigorous quality control (see section 'Details on Library Construction and Software Tools, Defining Book Type'). Standard protein clustering tools typically ignore the issue of global sequence similarity, so that even resources intending to cluster proteins based on global similarity can occasionally fail (for example, the Celera Panther resource [39] class Leucine-Rich Transmembrane Proteins [PTHR23154] contains proteins with diverse domain structures; Additional data file 1). By contrast, most web servers for protein functional classification provide primarily domain-level analyses (for example, SMART and PFAM). To supplement these analyses, PhyloFacts also provides books for different types of structural similarities across sequences, including short conserved motifs and structural domains.
Comparison of PhyloFacts with other functional classification resources
Analysis of user-submitted sequences
Sanger PFAM
Classification to full-length protein families
Subfamily level classification
Domain level classification
DNA sequence analysis
Batch-mode sequence inputs allowed
Analysis required for phylogenomic inference
Clusters based on full-length protein families
Phylogenetic trees for full-length protein families
Subfamily identification
GO data for individual sequences
GO data for clusters
GO evidence codes
EC numbers for individual sequences
EC numbers for each cluster
Taxonomy information
Analyses required for function inference based on structure
Phylogenetic trees for single domains
Clusters based on domains
Predicted three-dimensional structure for a protein family
Predicted critical residues
PDB structure visualization
PFAM domains
Transmembrane domain prediction
Signal peptide prediction
SCOP classification
Links to PDB
Additional protein family data
Retrieval of relevant literature for individual families
Extended protein family annotation
Clusters of interacting domain families
Graphic displays of related domain architectures
Fractional coverage of genomes
Model organism
Number of sequences
Fractional coverage
Homo sapiens
Escerichia coli
Arabidopsis thaliana
Caenorhabditis elegans
Drosophila melanogaster
Functional annotation using PhyloFacts
In an ideal scenario, annotation transfer between a query and homolog would meet three criteria [22]: first, global homology; second, orthology [44]; and third, supporting experimental evidence for the functional annotation being transferred. In practice, confirming agreement at all three criteria is not always straightforward. Very few sequences have experimentally solved structures; satisfaction of the first condition is, therefore, typically determined by comparison of their predicted domain structures using, for example, PFAM or Conserved Domain [45] analysis, or by pairwise alignment analysis. Automated determination of orthology is complicated due to incomplete sequencing, gene duplication and loss, errors in gene structure and other issues; for a review see [46]. Satisfying the last condition is equally difficult due to the paucity of sequences with experimentally determined function; our analysis of GO annotations and evidence codes for over 370,000 sequences in the UniProt database [47] shows <3% to have experimental evidence supporting a functional annotation. (This statistic is based on the analysis of 372,448 UniProt sequences present in the PhyloFacts resource as of June 2005. Two-thirds of these (248,152) had GO annotations, but only 3% of this smaller set had evidence codes indicating experimental support: IDA (inferred from direct assay), IGI (inferred from genetic interaction), IMP (inferred from mutant phenotype), IPI (inferred from physical interaction), and TAS (traceable author statement).)
Books in the PhyloFacts resource are labeled by the level of structural similarity across members (that is, global homology, domain, and so on), and include phylogenetic trees, inferred subfamilies, and GO annotations and evidence codes to enable a biologist to check for agreement at the three criteria for transferring annotations. In cases where a protein of unknown function is placed in a global homology group with an ortholog having experimentally determined function, annotation transfer can proceed with high confidence. In other cases, the biologist can check for experimentally determined function in paralogous genes (bearing in mind that functions may have diverged), or at domain-based clusters, to obtain clues to the molecular function for different regions of a protein of interest. We attempt to accommodate all of these possibilities; a sequence search against the resource may match books representing global homology groups, structural domains, conserved regions, or even short motifs, all of which are presented to the user (Figure 2).
We note that while domain-based annotation is inherently less precise, PhyloFacts does provide predicted functional subfamilies within domain-based books as well as within books representing global homology groups. While annotation transfer across proteins having different overall folds is prone to systematic error, previous results suggest that subfamily classification of sequences aligned along a single common domain can be consistent with the overall domain structure and molecular function of sequences [48]. Our experiments using SCI-PHY to analyze proteins with different overall domain structures also support the same conclusion (unpublished data, Brown DP, Krishnamurthy N, Sjölander K).
In addition to the value PhyloFacts presents to a human investigator, it also provides a framework for the development of a fully automated functional inference system. A new generation of probabilistic methods for inferring molecular function automatically has arisen in recent years (for example, [26, 49, 50]). For instance, SIFTER uses a Bayesian approach to infer a distribution over possible functions in a phylogenetic tree, taking as input a cluster of sequences, a phylogenetic tree, and GO annotations and evidence codes, all of which PhyloFacts collects and integrates in one resource. SIFTER integration is to be available in our next release.
However, technical issues present barriers to the goal of fully automated function prediction (see [51] for a review). Sequences in a cluster may have different descriptors based on the species of origin; for example, the Drosophila community is likely to use different names for a gene to that used by the Caenorhabditis elegans community, and both are likely to use different terms to those used by investigators working in mouse genomics. The value of a standardized nomenclature, such as that being developed by GO, is obviously important, but significant work remains in this area. An exhaustive thesaurus of equivalent biological terms would be valuable. The sparse nature of experimentally supported molecular functions provides an additional barrier to automated approaches. We discuss these issues further in the section 'Challenges to phylogenomic inference'.
Clustering together proteins based on predictable global homology enables us to analyze a cluster of homologs as a unit and detect potential errors in annotation; database annotation errors tend to stand out as anomalous against a backdrop of otherwise consistent annotations (unless, of course, annotation errors have percolated through the database).
For instance, the Oryza sativa GenBank protein AAR00644 is labeled as a 'putative LRR receptor-like protein kinase'. The canonical structure of receptor-like kinases (RLKs) consists of an extracellular leucine-rich repeat (LRR) region, a transmembrane domain, and a cytoplasmic kinase domain; AAR00644 contains no kinase domain. On the other hand, AAR00644 does match the canonical structure of closely related receptor-like proteins (RLPs), which are structurally very similar to RLKs, except that they terminate with a short cytoplasmic tail, and do not contain a kinase domain [52]. In the PhyloFacts resource, this protein is classified as a member of the global homology group book 'Plant LRR proteins (putative RLPs)' (PhyloFacts book ID: bpg005632), where PFAM domain analysis of the cluster shows no detectable kinase domains.
For a second example, the GenBank sequence AAF19052 labeled as 'neutral human sphingomyelinase' [53] appears to be neither human nor a sphingomyelinase. Instead it appears to encode a bacterial isochorismate synthase protein. This sequence is classified to the PhyloFacts book 'Isochorismate synthase-related' (Phylofacts book ID: bpg004927), in which this purportedly 'human' sequence is the only representative eukaryote. (Note that even the translated BLAST search of this sequence against the human genome finds no matches.) In this case, both domain structure analysis and analysis of the taxonomic distribution of the globally homologous members of the family help identify the probable error.
Lastly, G-protein coupled receptor (GPCR) classification is notoriously difficult, with many receptors having no known ligand (termed 'orphan receptors'). One such orphan, a GPCR from river lamprey (UniProt: Q9YHY4), is annotated as 'Putative odorant receptor LOR3', based on its expression in the olfactory epithelium [54]. Standard profile/HMM-based analyses (for example, PFAM, SMART and the NCBI CDD) only match this protein to the PFAM 7TM_1 class, containing dozens of subtypes. BLAST analysis shows other putative odorant receptors from river lamprey (submitted by the same authors) as top hits, followed by trace amine receptors. However, analyses of phylogenetic trees containing this sequence show it (and the other putative odorant receptors detected by BLAST) to be located within subtrees containing trace amine receptors (see PhyloFacts books bpg004950, bpg000525 and bpg000543) and to be quite different from experimentally confirmed odorant receptors (Additional data file 2).
Anomalous annotations such as these are often signs that annotation transfer has gone wrong. In other cases, anomalies may be quite real and provide new insights into the evolution of novel functions in a family. Automated anomaly detection faces the same technical barriers as automated functional annotation, including the need for probabilistic inference of gene function, standardized nomenclatures and exhaustive synonym tables of biological terms. At present, these anomalies - whether true functional differences or database annotation errors - are detected manually. In the future we expect automated function prediction methods will enable anomalous annotations to be flagged for expert examination. Protocols will then need to be established by the biological community to correct any errors and to ensure that sequence databases receive corrected annotations.
Details on resource construction and software tools
Clustering sequences for PhyloFacts books
Sequences for structural domain books were gathered using PSI-BLAST and UCSC SAM Target-2K (T2K) [37]. Sequences retrieved for global homology group books are required to share the same overall domain structure (global alignment). We have two tools for this process: FlowerPower (NK, Brown D, KS, unpublished data) and GHGCluster.
FlowerPower is an iterative homolog detection algorithm like PSI-BLAST that retrieves homologs to a seed sequence (or query) and aligns sequences using profile methods. However, instead of using a single profile to identify and align new sequences, FlowerPower uses subfamily identification and subfamily HMM construction to expand the homology cluster in each iteration. Alignment analysis is used to restrict the cluster to match user-specified criteria (for example, global alignment for protein function prediction using phylogenomic inference, and global-local alignment (global to the seed, local to the database hit) for domain-based clustering). Experimental validation of FlowerPower shows it has greater selectivity than BLAST, PSI-BLAST and the UCSC SAM-T2K methods of homolog detection at discriminating sequences with local similarity from those with global similarity. The FlowerPower server is available online [55].
The Global Homology Group (GHG) Cluster program enables us to cluster a selected sequence database (for example, a genome) into global homology groups, while also including homologs from a second, generally larger, database.
GHGCluster takes two inputs: a set of sequences Q, containing the sequences to be clustered, and a database D to use for expanding the clusters to include globally alignable homologs from other organisms. A superset of sequences, the expansion database E, is created by merging Q and D. To improve run time, E is partitioned into overlapping bins based on sequence length. A seed sequence (query) is chosen from Q and homologs are gathered from its corresponding bin in E, using PSI-BLAST (E-value < 1e-5; user-specified number of iterations). Each hit is assessed for global homology to the query, based on percent identity (≥20%), and bi-directional alignment coverage, that is the fractional aligned length of both seed and hit (ranging from 60% for sequences <100 residues to 85% for sequences of >500 residues). In some cases, PSI-BLAST returns multiple short aligned regions, none of which is long enough to pass the above requirements. In these cases, the failing hits are realigned to an HMM built from the seed, followed by alignment analysis. The seed and any accepted sequences are defined as a cluster and removed from Q (but not E). A new seed is then chosen from Q and the process is iterated until Q is empty.
This procedure results in a set of clusters, some of which may contain the same sequence(s). At this stage we merge compatible overlapping clusters. We rank all pairs of clusters by the number of sequences they have in common and attempt to merge pairs in order. For each pair, we choose the alignment with the greater number of aligned columns and designate this as cluster A; the other cluster becomes B. We build an HMM from the cluster A alignment and use the COACH algorithm [56] to align the entire cluster B alignment to this HMM (and therefore to cluster A). If the total fraction of gap characters in the merged alignment (that is, no. of gaps/(no. of sequences × no. of columns)) is less than 20%, and the mean percent identity is greater than 20%, the merge is accepted. Otherwise, if the alignment fails based on gap content alone, we trim columns with >30% gaps from the amino and carboxyl termini and reassess: the merge is accepted if cluster sequences align at least 70% of their residues, on average, within the trimmed 'core' alignment and if the core alignment contains >50% of the columns from the merged alignment and <10% gaps. Note, this procedure is computationally efficient, but can produce clusters that fail to meet the criteria set for global homology group books. In these cases, books are flagged for additional automated analysis and manual inspection in order to maintain quality control.
GHGCluster was used to cluster the human genome in the construction of the PhyloFacts Animal Proteome Explorer, including homologs from NR, using three iterations of PSI-BLAST.
Note on clustering splice and allelic variants
Our atomic unit in PhyloFacts clustering is the protein sequence, independent of its origin. Consequently, splice and allelic variants of a gene are not handled differently to genes from entirely different species during clustering, alignment and tree construction (although they would be interpreted differently during a subsequent phylogenomic analysis using the resource). If the variant retains the same domain structure and is globally alignable to other isoforms, it will be included in the global homology group cluster for those genes, otherwise it may end up in a different book in the resource. It should be noted that the presence of different isoforms for a gene can cause difficulties in phylogenomic inference if their common genome locus is not evident. Future releases of PhyloFacts will display this information and create links between different gene isoforms present in different books.
Multiple sequence alignment
The alignment method is selected based on the type of book. For alignments of global homology group proteins, we normally use the MUSCLE software [57] to realign sequences obtained in clustering; in some cases, we use the SATCHMO software [58]. Both methods have outstanding performance evaluated on benchmark datasets. Alignments of structural domains are taken directly from the clustering algorithm (PSI-BLAST or T2K). The method used is indicated in the 'Book Details' section at the bottom of each book page, under 'Build method notes'. Multiple sequence alignments for all books (except those constructed to model solved three-dimensional structures) are masked to remove columns with >70% gaps prior to phylogenetic tree construction. Alignments are available for the family as a whole and for each subfamily; these can be downloaded or viewed using the Java-based Jalview software [59]. An annotated alignment, indicating SCI-PHY subfamily membership, is also available for viewing and download. Alignment statistics are provided, including average, minimum and maximum percent identity, fraction of gap characters in the MSA, and other relevant measurements.
Defining book type
To be defined as a 'Global Homology' book, a multiple sequence alignment must meet the following criteria: first, ≤15% gap characters over the multiple sequence alignment; second, ≤30% columns with BLOSUM62 [60] sum-of-pairs scores < 0; third, difference between the longest and the shortest sequence in the alignment <150 amino acids; and fourth, all sequences align over ≥75% of their length. Books of type 'Domain' were required to match a structural domain (as determined by SCOP) or to correspond to a PDB structure. Books labeled as 'Conserved Region' required global-local alignment of sequences to the HMM (generally matching over 70% of the HMM match states). Most books labeled as 'Pending' are those that were produced by the GHGCluster program, but which failed the stringent 'Global Homology Group' alignment quality control tests; the final classification of these books to the different structural types is in progress.
Subfamily identification
Subfamily identification is provided using the SCI-PHY (Subfamily Classification In Phylogenomics) software [61]. SCI-PHY is an automatic subfamily identification algorithm; given an input MSA, SCI-PHY uses Dirichlet mixture densities [62] and relative entropy to construct a hierarchical tree, and cuts the tree into subtrees to identify subfamilies using minimum-description-length principles. Extensive studies show SCI-PHY subfamilies correspond closely to both expert-identified subtypes and to conserved clades in phylogenetic trees (unpublished data, Brown DP, Krishnamurthy N, Sjölander K). The SCI-PHY server is available online [63].
HMM construction for the family and individual subfamilies
The UCSC Sequence Alignment and Modeling (SAM) software is used to construct HMMs and in scoring sequences against HMMs [64]. This software was selected based on its outstanding performance in remote homology detection [17, 64]. Family HMMs are constructed using the UCSC SAM w0.5 software. Subfamily HMMs (SHMMs) are constructed as described in [65]. Validation experiments on over 500 unique SCOP folds comparing subfamily and family HMMs show SHMMs to have high specificity in detecting functionally similar sequences and to improve the range of homolog detection with significant scores (unpublished data, Brown DP, Krishnamurthy N, Sjölander K).
Protein structure and domain prediction
PFAM domains are identified using the consensus sequence for the family as a query using the PFAM gathering threshold as a cutoff. Matches to PDB structures are predicted by BLAST analysis of the family consensus sequence, using an E-value cutoff of 0.001 (that is, protein structure prediction based on inferred homology). Any putative homologous structures were aligned to the family HMM using local-local alignment (SAM parameter - sw 2). Transmembrane domains and signal peptides are predicted using the PHOBIUS server [29], selected due to its ability to differentiate between signal peptides and transmembrane domains.
Phylogenetic tree construction and visualization
Because many of the protein superfamilies in the PhyloFacts resource span extremes of evolutionary divergence (for example, with pairwise identities <20%), tree topologies produced by different methods can often disagree. For this reason, most of the protein families in the resource contain several phylogenetic trees built using different algorithms, enabling biologists interested in these families to examine the differences and commonalities between the trees.
Neighbor-Joining trees are constructed using the PHYLIP software [66], using the default parameters for 'protdist' and 'neighbor' (JTT model [67] and no variation of rates). Maximum Likelihood trees are estimated using the PHYML software [68], also using the JTT model, four substitution rate categories, and a gamma-distributed model of rates (gamma = 1), and are set to optimize tree topology only. Maximum Parsimony trees are estimated using the PAUP* software [69], by taking an extended majority rule consensus of the most parsimonious trees obtained via ten repetitions of heuristic tree search. All trees are rooted using the midpoint method. As of 4 July 2006, of the 9,707 books in the library, 8,511 have at least one true phylogenetic tree constructed, and 3,613 have NJ, ML and MP trees. All books have had SCI-PHY subfamily analyses completed, and will eventually include Neighbor-Joining (including bootstrap values), Maximum Likelihood and Maximum Parsimony trees.
Predicted critical residues
Novel sequence classification
Classification to a protein family is enabled by HMM scoring. Since HMM scoring is computationally intensive and the PhyloFacts resource contains almost 10,000 books (each containing a family HMM and potentially dozens of subfamily HMMs), we provide heuristic approaches enabling rapid classification of user-submitted sequences. For computational efficiency, we select books for HMM scoring via BLAST analysis of the submitted query against a dataset of over 2.5 million PhyloFacts training sequences using an E-value cutoff of 10; this significantly reduces the number of HMM scores required without affecting sensitivity. Users can override this 'BLAST pre-screen' protocol using the 'Advanced' settings page. Books retrieved based on either protocol can then be selected for scoring the submitted sequence(s) against subfamily HMMs for additional specificity of functional classification.
Future work
In future releases of the PhyloFacts resource we plan to include automated predictions of protein function using the SIFTER software. SIFTER will be used to provide predicted molecular functions and participation in biological processes for SCI-PHY subfamilies as well as for conserved evolutionary clades. Links between proteins, or between books, will be provided, to reflect the many types of relationships (for example, participating in the same pathway or complex, sharing a common domain or a predicted common ancestor, splice variation, and so on). Users will be able to navigate between proteins in the same pathway using the Cytoscape software, in which links to PhyloFacts books will be embedded. Users will be able to retrieve comparative (homology) models for selected proteins from the ModBase resource [72] through hyperlinks on book pages. Literature will be retrieved automatically for sequences in a book, and natural language processing software will be used to summarize the key points. We will expand the resource for improved coverage of key (animal) model organisms (human, mouse, C. elegans, D. melanogaster), and to keep our protein structure prediction library current. We plan to reduce redundancy in the library by combining books with significant sequence overlap. We will develop software tools to identify and include new family members as well as new experimental data (for example, the availability of solved structures, results from site-directed mutagenesis, protein-protein interactions, and so on). We will also include extensions to the subfamily HMM scoring protocol to differentiate between sequences representing a novel subtype and those that can be classified to the top-scoring subfamily (based on logistic regression analysis). Phylogenetic trees for each family will be extended to include strict consensus trees across two or more methods, and bootstrap analysis will be provided for Neighbor Joining trees. Finally, we plan to provide community annotation tools to enable biologists to upload their data, commentaries and hyperlinks to experimental data for members of protein families.
Challenges to phylogenomic inference
Phylogenomic analysis of protein function is known to improve the accuracy of functional annotation, but has had restricted application due to its technical complexity. The PhyloFacts resource enables biologists who may have limited bioinformatics expertise to take advantage of pre-computed phylogenomic analyses for hundreds of thousands of proteins. New sequences can be classified to families and subfamilies using over 700,000 hidden Markov models, for increased functional specificity. The resource as a whole brings together many different types of bioinformatics analyses and data; the integration of these data and improved orthology determination enables biologists to avoid making new annotation errors at the outset, and to detect, and possibly correct, existing annotation errors.
Phylogenetic uncertainty and ambiguity remain significant challenges to phylogenomic inference of molecular function. Consensus analysis can be used to detect clades with support across two or more tree methods, but this approach could inadvertently be misleading if inherent biases in the methods are not taken into account. It is critical that the computational biology community and the systematics community work together to develop methods to assess the expected accuracy of phylogenetic methods for protein superfamily reconstruction; new simulation studies should be developed that model the kinds of structural and functional changes observed in protein superfamily evolution.
Other challenges to automating functional annotation through phylogenomics methods include: the lack of a standardized nomenclature for gene names across different model organisms, although the GO consortium efforts are making progress in this respect; natural structural and sequence divergence among family members causing difficulties in clustering; ensuring multiple sequence alignment accuracy when divergently related sequences are included in a cluster; and the persistence of database annotation errors. Database annotation errors should be correctable at the source, so that the primary sequence repositories (GenBank, UniProt, and so on) can be kept current.
One of the fundamental questions in phylogenomic inference of protein function is determining the evolutionary distance within which annotations may be transferred. Given the paucity of sequences with experimentally determined function, if annotations can only be transferred between orthologs (and are also restricted to annotations having experimental support), the vast majority of unknown sequences will remain without predicted function. Is this necessary or overkill? Analysis of different types of 'function' associated with proteins show that some types of attributes (for example, catalytic activity) persist over large evolutionary distances, while in other cases (for example, substrate specificity), functions can diverge extremely rapidly. Moreover, the degree to which different types of function persist over evolutionary distance can vary from one family to another. One intriguing possibility for the next generation of phylogenomic inference methods involves identifying attribute-specific evolutionary distances over which attributes may percolate.
Finally, assessing annotation accuracy is a very labor-intensive practice. Biological curators can spend days analyzing and annotating a single gene; to do this in high-throughput for thousands of sequences is clearly not feasible. An additional complication is that definitions of molecular 'function' or 'subfunction' are not at all standardized within biology. Instead, some biologists use the term 'function' very specifically (see for example, [3]) while others may use the term more loosely. Assessing annotation accuracy, and comparing the relative effectiveness of different function prediction protocols, also requires judgment calls regarding definitions of correctness. An annotation may be technically correct, but at such a high level that it is minimally helpful. For instance, a novel gene may be labeled as 'putative membrane protein', 'putative GPCR' and 'putative chemokine receptor'. If experimental studies show the protein to be a chemokine receptor, then only the third annotation would be particularly helpful to biologists, although all annotations would be technically correct. In other cases, an annotation may be technically incorrect, although quite close, due to annotation transfer from a paralog with a slightly different functional specificity (for example, Serotonin receptor type 1 versus Serotonin receptor type 2). Critically, there is also no community-accepted benchmark dataset or scoring function to evaluate methods of protein functional classification. These need to be developed to enable computational biologists to determine what types of inference methods are robust under what conditions, and where our methods fail. Efforts to develop true de novo function prediction efforts, analogous to the biennial CASP protein structure prediction experiments, are underway [73], and are likely to play an important role in improving our understanding of method accuracy in this important area.
Additional data files
This work was supported by a Presidential Early Career Award for Scientists and Engineers (PECASE) from the National Science Foundation, and by an R01 from the National Human Genome Research Institute of the NIH. Neither funding source was involved in: the study design; the collection, analysis, and interpretation of data; the writing of the manuscript; or the decision to submit the manuscript for publication. The authors wish to thank several anonymous reviewers for very helpful comments and suggestions.
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text:
Cole Imperi, CT
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I teach people, businesses and organizations how to embrace loss, difficult moments and mistakes to turn those into foundations for growth.
Cole Imperi is a dual-certified thanatologist and one of America's leading experts on death, dying and grief. As a writer and podcast host, she is enthusiastically changing the way we approach loss, death and dying in the United States, and teaches how to live a brighter life by finding the light of loss. Cole is represented by literary agent Sam Hiyate, President of The Rights Factory.
Cole is a Certified Integrative Thanatologist and Certified in Thanatology: Death, Dying and Bereavement through the Association for Death Education and Counseling. Cole is a 200-hour Registered Yoga Teacher. She holds a post-graduate Certificate in Typeface Design from the Type@Cooper Condensed Program. She is a Certified Crematory Operator. Cole was appointed by the City of Covington, Kentucky to the Board of Overseers of Historic Linden Grove Cemetery and Arboretum and serves on the board of a green burial cemetery—Heritage Acres—in Cincinnati, OH. She is teaching faculty for the ICCFA Cremation Arranger Certification program, and a public speaker covering topics ranging from generational marketing, end-of-life issues, and grief/loss. She is Adjunct Faculty at a mortuary college teaching Thanatology. Cole is Associate Producer of MORTAL, a feature-length documentary film about the human condition. She serves on the Advisory Board for the Art of Dying Institute. Cole is an active hospice volunteer and bereavement support group leader for children as young as 3 to adults.
Doth is my consulting firm. We work with businesses mostly within deathcare to help them navigate market changes and reach the right audiences. We provide marketing, operations, pricing, packaging and branding support.
We provide mystery phone shopping for the deathcare profession. We'll call your business and provide you with a thorough report that helps you identify areas where your business is excelling, and where it needs to improve.
I regularly teach at conventions, training seminars, and workshops. My public speaking topics range from generational marketing to end-of-life issues and grief/loss. Contact me today to see if my services would be a good fit for your next event.


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Piga, Giampaolo and Guirguis, Michele and Bartoloni, Piero and Malgosa, Assumpció and Enzo, Stefano (2010) A Funerary rite study of the Phoenician-Punic necropolis of Mount Sirai (Sardinia, Italy). International Journal of Osteoarchaeology, Vol. 20 (2), p. 144-157. eISSN 1099-1212. Article.
Full text not available from this repository.
DOI: 10.1002/oa.1012
A recent excavation in the Phoenician-Punic necropolis of Mount Sirai, located in the southwestern part of Sardinia, Italy, has brought to light a number of tombs contextually attributed to a period from the early 6th to early 5th century BC, which is simultaneous with the beginning of the Carthago influence in Sardinia. Among the interred burials recently brought to light, the skeletal remains, sometimes of two superposed bodies, are found in a primary position and with fine anatomic connection. Some of the bones were visually stained, suggesting they were possibly subjected to fire treatment. In order to ascertain more objectively whether the bodies were subjected to burning, the bones from all the tombs were investigated by powder X-ray diffraction (XRD) and Fourier Transform infra-red (FT-IR) spectroscopy techniques. After excluding the role of important diagenetic effects, from line broadening/sharpening analysis of hydroxylapatite in the bones according to the Rietveld method, it was evaluated that the bodies were probably subjected to a temperature regime from 300 to 700°C. These data were supplemented and confirmed by an analysis of the splitting factor (SF) of apatite phosphate peaks in the infra-red spectrum of the bones. Our results indicate the existence of a rite intermediate between incineration and inhumation. This sort of semi-combustion, perhaps limited to the period of the early 5th century BC, appears to be peculiar just to this site.
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Buy Electronic CigaretteSaturday, August 6th, 2011
What is E ? It stands for Electronic and E commerce is a big part of our daily lives at present we buy electronic cigarettes for example online and save our selves a fortune and get healthy! Why ? Because it makes economical and viable sense to the smokers out there and especially the ones who cant just kick the habit . Most smokers have allready tried the nicotine gum and nicotine patches but now this relatively new product that hits our streets is sure to become an internet and end users sensation! The body gets the desired nicotine and we get more money in our pockets 🙂


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Comfort Wear
COS tee // Joie pants (similar) // Rebecca Minkoff bag // ALDO booties
I'm typically all about structured pieces, but sometimes I just want to be as comfortable as possible and wear cotton. This COS tee has quickly become a closet staple -- I was turned on to the brand once I saw Damsel in Dior rock a striped tee of theirs, and it's the perfect wear-all-day and sleep-in-it-later kind of t-shirt brand. I also snagged these Joie pants (similar here) a few years ago, and they never get old -- the material is so comfortable and breathable but looks great all day and doesn't wrinkle.


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Padres outlast Blue Jays in 17 innings
San Diego, CA – Jedd Gyorko drove in a pair and scored the tying run in the fifth inning.
Twelve innings later, he scored the winning run, too.
Jesus Guzman knocked him in from second base in the bottom of the 17th inning, and the San Diego Padres outlasted the Toronto Blue Jays, 4-3, in near five- hour marathon at Petco Park.
Gyorko had three of the Padres' nine hits, with his last coming on a sharp liner off the third base bag with one out in final frame.
Clayton Richard (1-5), who was suppose to start the middle test on Saturday of this three game set, pitched two scoreless innings of relief before laying down a sac bunt.
"We took Clayton's start tomorrow out of the equation and decided to use him tonight and go for the W," said Padres manager Bud Black.
Gyorko moved to second on the sacrifice and Guzman, who was 0-for-3 to that point, lined a base hit up the middle to score the winning run and lift the Padres to their third win in four games.
Todd Redmond (0-1) pitched 3 2/3 innings out of the bullpen for Toronto, which mustered just three singles over the last 10 innings of play.
Each team used eight pitchers, with San Diego's bullpen at one point retiring 17 straight batters from the end of the seventh through the 12th inning.
Toronto held the early lead, but when it had runners in scoring position, it never managed a hit in five chances.
Colby Rasmus went 4-for-7 and smacked a two-run homer in the top of the second, and then took one away from Yonder Alonso in the bottom half.
On Alonso's shot to straight away center, Rasmus backed up and snagged it from going over the wall to keep the contest, 2-0, in favor of Toronto.
Edwin Encarnacion's blast into left the field seats to begin the fourth gave the Blue Jays a three-run cushion, but Gyorko brought the Padres even an inning later.
With runners on first and second, Gyorko ripped an offering from Toronto starter Chad Jenkins into the gap in right center for a double. Both runners scored on the hit and Gyorko eventually came home on the play when catcher J.P. Arencibia tried to catch him advancing to third.
Sab Diego starter Jason Marquis was pulled after loading the bases in the top half of the sixth, but Tyson Ross escaped the one-out jam by forcing Melky Cabrera into the unconventional 3-2-3 double play.
After each team foiled opportunities to score in the sixth and seventh innings, only the Padres put runners in scoring position the rest of the game.
Game Notes
Marquis allowed three runs on seven hits and four walks over 5 1/3 innings. He struck out six ... Jenkins lasted five innings and was charged with three runs -- two earned -- on three hits ... Alonso was plunked on the right hand in the seventh and left the game in the ninth. The Padres are calling it a hand contusion, X-rays were negative, and he'll be reevaluated later on Saturday ... Adam Lind had three hits for Toronto.


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Thursday, February 5, 2009
Huge school of spinner sharks off the coast
Thousands of spinner sharks have been spotted off the coast of Florida today. Beaches have posted signs up and down the coast line to warn people to stay out of the water. The aerial footage of the schools of sharks are impressive. Needless to say, you had better stay out of those coastal waters for a few days or at least until the sharks have quit migrating in that area. You don't want to have your family looking for instant term life insurance quotes while you are dying in the hospital from a shark bite.
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As most home owner who always follows probably looking to improve your home, save some money and make your home the best place to look more and more comfortable to live effectively. This is a fact that most people who own their own home is very proud home then there are those who are looking for ways to improve your home to sell quickly and move forward in today's competitive housing are market. Here some of the home improvements you can make more profitable, say it, one that will not cost a fortune, but it will give a great return on investment:
Install double glazed sash current instruments if you have old, single glazed or tinted windows as the three types of windows will be energy inefficient and unsafe. Single glazing allows the hot air to escape quickly and allows cold air to penetrate easily say it, heating only goes so far and if not enough We take into account the cost of gas and electricity these days. Replace your appliances new for old, as these models more energy efficient appliances are the days that pass strict tests and energy are given a letter grade from A + to G, A + G, it is the best and the worst. Look for these notes when you buy in the store I empty online customer comments and ratings often do you tell how many people have been saved on energy bills and water as a direct result of the investment in a more efficient washing machine, dishwasher, TV or fridge freezer.
Loft insulation and have the camera installed, this does not have to be expensive or harmful if you do your homework and if you're not sure it's worth asking Where contact your local council for advice or go online and find a reputable company base of customer comments and feedback. The insulation can reduce your heating bills by an average of £ 150 per year, so the money to install it again in one to two years, it a great return on investment.
Riding out the butt of a decent rain water gutters on the outside of your house and collect water used to water the garden and vegetables when it stops raining and the sun. We lose a lot of natural resources and this is an easy way to take advantage of nature and is an easy way to save money.


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St Davids Kitchen has been born out of a love for the St Davids Peninsula – the local community, the environment and locally grown food.
We only serve the freshest local produce, including our own St Davids Welsh Black Beef (reared within the Pembrokeshire Coast National Park just outside St Davids) and our newly acquired Ramsey Island lambs & venison.
We support local farmers, producers and fishermen by buying the best from the best, and delivering that to your plate at St Davids Kitchen.
What our customers say…
"Epic food, superb ambience & friendly staff – with plenty of gin!"
Louise from Bristol on tripadvisor
"A Class Of Its Own"
WOTRCyclists from Macclesfield
"Great champion for local produce."
Lesley E from Lincolnshire
"A fabulous meal and a lovely atmosphere. Best in St Davids by far."
Rudgie7 from Meriden
Book a table
Please call or email us if you would like to make a booking.
Plus you can follow us for all the latest news and exclusive special offers on social media.
Call us on 01437 720 009
Opening hours
We are currently open 7 days a week from 12:00 – 15:00 for lunch and 18:00 – 22:00 for evening meals.
How to find us
We are just off the Cross Square in St Davids, at 16 Nun Street.
There is on-street parking or long term parking at the Quickwell Hill car park less than 2 minutes walk away.
Need directions? Just give us a call.


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Infertility condition can be defined as the failure to achieve pregnancy even after the repeated practice of unprotected intercourse. This failure in pregnancy will be either due to female infertility problem or male infertility problem.
The infertility issue can be arised due to age problem, physical problems, hormonal imbalance, environmental factors or improper lifestyle including food habits. It is a usual practice to curse women for not being able to conceive a baby, but the studies prove that only one third of the infertility problems are seen in women. The other one third in men and the remaining one third in both.
Causes of infertility
male :
male :
- Abnormality in the production of sperm.
- Problems with the sperm carrying tube.
- Overexposure to certain environmental factors.
- Problems ejaculating.
female :
- Ovulation disorders.
- Uterine or cervical abnormalities.
- Fallopian tube damage or blockage.
- Endometriosis.
- Primary ovarian insufficiency.
- Pelvic adhesions.
Infertility Treatments Offered:
Your doctor will go through your infertility issue and will evaluate the reason behind your infertility disorders. For the purpose certain tests will be carried out to assess the fallopian tube and uterus, Genetic testing for inheritable diseases and miscarriages, and surgical tests like hysteroscopy and laparoscopy.
Once you are diagnosed with the factors behind your infertility, you will be subjected to certain suitable treatment like,
- Male evaluation
- Female evaluation
- Ovulation induction
- Artificial insemination
- Intrauterine insemination (IUI)
- Assisted Reproductive technique (IVF, ICSI, PESA, TESA)
Sometimes due to certain severe factors, the treatments may get unable to make you conceive due to the lack of egg production (in female), sperm production (in male) and thereby leading you to a failure to generate an embryo. In such cases we are providing you other techniques like, Egg donation, Sperm donation and Embryo donation.
If you too are missing to have your little one's cute smile,
Vijaya Fertility Clinic IVF & Endoscopic Centre, the supreme one to solve your infertility issue, provides you the best Infertility treatments in Kochi. We aim to fulfill your dream by giving you the glory of a blessed life.
For more details visit us on : www.vijaya-ivf.com
E-mail us on : firstname.lastname@example.com


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Lost in the Fifties- Another Time, Another Place
6 Ways to Help Your Aging Parent Move to a New Place
As the general population ages and people are living longer, many of us will face the challenge of moving an aging parent.
According to SpareFoot.com, the world's largest online marketplace to find and book self-storage units, here are six guidelines to help the transition go smoothly.
1. Start Early.
If you're considering when to bring up the topic of change, "anytime is a good time," said Fritzi Gros-Daillon, owner of Household Guardians, a company that offers safety kits and safety consultations. Having this conversation while your parent is in good health can make it easier to lay out a plan together. When it comes to elderly parents, "remember it is all about them being in control, and maintaining their independence and quality of life," Butler said. "You are only there to help."
2. Find the Right Place.
Before making any decisions, you'll want to look into the assisted living facilities or retirement communities in whichever areas are under consideration. "Many assisted living facilities will set an appointment with you for a tour of the facility and to stay for lunch," Butler said. If possible, take your parent along for the visit. In addition to the facility's physical amenities, check out the services offered there. "Ask what level of care is available now and in the future," said Rick Lauber, author of"Caregiver's Guide for Canadians" and a former caregiver for his own aging parents.
Surviving Eldercare: 6 Tips for the Sandwich Generation
Here are some alarming statistics.
According to a recent Statistics Canada census (figures globally will be equivalent, anywhere burgeoning elder populations exist):
The number of seniors who live with relatives and non-relatives in private dwellings is 393,150 – up from 285,370 only a few years' previously;
Twenty-five percent of those aged 45 to 64 (the so-called Sandwich Generation) have children living at home and perform some form of eldercare;
Fifteen percent of those workers must take time off from their job to care for aging relatives.
Juggling multiple competing demands is tough at the best of times. You're already split umpteen ways daily through your employment or business, significant other, children, grandchildren, home and/or car maintenance, your health and tons more.
You're not alone.
Finding The Source Of Your Fears
A sure way to overcoming your fears and anxieties is in finding the source of your fears and being able to manage it. In dealing with any kinds of fears or anxieties, try to learn what is the real source of your fears and anxieties. Knowing what is causing your anxieties can go a long way in finding the solution.
A person can find the source of his or her own fears by doing some self-evaluation and also by talking to a professional. Asking yourself questions such as: "Why am I afraid" or "What is causing my anxiety" will lead you in the right direction in finding the source of your fears. Give it some time and eventually you will find the answers your looking for.
Once you find the true source of your fears, the next step is to find the solutions that will solve your problem. With the help of a professional, write down a list of possible techniques and solutions that you think will manage your fear and anxieties. The next step is to apply the techniques that you uncovered. Here is a brief list of some techniques you can use to help deal with your fears.
Baby Boomers Turn to Support, Tech for Long Distance Caregiving
Just a generation ago, aging family members typically had at least one relative living nearby. These days, many are being cared for by baby boomer children who live far away.
Balancing careers and kids of their own, these grown children may find it difficult to move closer to parents who have begun to need daily help.
Caregiving has become "an unexpected second career" for many people in their 50s and 60s, says Tamar Shovali, who studies gerontology and teaches at Eckerd College in St. Petersburg, Florida.
When You Are Looking for a Home at the Lake
Be sure to contact Shirley Smith!
Shirley is originally from the Midwest. She was in sales/marketing and owned her own business for many years. She and her husband Don moved to Georgia in 1993 and, when they discovered the Lake Oconee area, they fell in love with its beauty and vacation-like atmosphere.
The Smith's have two children, William, and Dr. Ted. While the boys were in college they would come to visit their parents and both knew that they would like to live in this beautiful state. William is in management for a large equipment company inCobb County and Dr. Ted is a Dr. of Chiropractic in the Lake Oconee Area. Both have two sons and a daughter.
Shirley is one of Lake Oconee's top Realtors. Having lived here for over 20 years, she feels that she has a lot to offer when it comes to assisting buyers or sellers in Real Estate. She can relate to the experiences clients encounter when they relocate.
A Boomer's Guide to Online Dating
Nearly half of all single baby boomers are dating, and many of them are swelling the profiles of online matchmaking websites with names like SilverSingles, SeniorPassions and dating.aarp.org.
Match.com, one of the largest dating sites for people of all ages, says its baby boomer clientele has grown 90 percent in five years, with a quarter of its 15 million users ages 50 to 65.
"Older people love a good romance as much as 20-somethings, and many of us still get just as love-drunk as we did when we wore size 32 Levis with no Expanda-Waist," says Charles W. Massie, a baby boomer who wrote about his online dating experience in a new novel, "Stains on the Gavel" (www.starshowpublications.com).
"But you've really got to be careful, whether you're a woman or a man. A lot of women my age complain the men they meet haven't changed at all in 50 years – they want to skip the coffee and head straight for the bedroom. My experience was even worse!"
Builders of Homes for Folks 55+ are Chipper
Improvement in the housing market is leading more baby boomers to consider a move — and that's boosting business for builders of housing catered specifically to those 55 and older.
"55-plus buyers are out in force. They're ready to make a move, they're tired of waiting. They know the market is right for folks who want to sell their [existing] home," said Steve Bomberger, president of Benchmark Builders in Wilmington, Del.
Last year, Benchmark Builders's total number of closings rose to 92, from 52 in 2012. For 55+ homes, it had 42 closings in 2013, up from 26 in 2012.
10 Tips for Baby Boomers Taking Care of Aging Parents
Many baby boomers are leading complicated lives nowadays. As people enter their fifties and sixties, they often have to juggle plans for their upcoming retirement while putting their own kids through college and welcoming the first grandchildren. For some baby boomers, there is also the extra task of caring for aging parents. These responsibilities can be difficult and stressful. Luckily, there are a number of tips and hints that can make caregiving easier for busy members of the boomer generation.
1. Take Care of Your Own Health
If you don't take care of your own physical and emotional health, it can be difficult to take care of other people. To be the best caregiver you can be, it's important to stay in good health. Try not to let your responsibilities get in the way of a healthy lifestyle with good food, exercise, and enough sleep. There may be difficult days when you're just too busy to cook fresh food or head outside for a walk, but you can always be on the lookout for opportunities to refresh and restore yourself. Investing in your own health will make you a better caretaker for aging parents.
2. Don't Be Afraid to Outsource
We've all heard the old cliché that "time is money." When it comes to caring for an older member of the family, you should protect your time as carefully as you protect your money. By hiring someone to come in for a few hours a week and help you with everyday tasks, you can take the pressure off your schedule and create some much-needed free time for yourself.
[Read more…]
It Takes a Village: Seniors Thrive While Living at Home
Instead of moving into an assisted living facility, some retirees are discovering the benefits of community and how that can help them remain in their own homes.
Visit NBCNews.com for breaking news, world news, and news about the economy
Dr. Nancy Snyderman: My Life as a Caregiver
NBC News's Chief Medical Editor, Dr. Nancy Snyderman, describes how she slowly began taking on more responsibility while helping care for her parents, and the difficult conversations that arise from end-of-life discussions.
Visit NBCNews.com for breaking news, world news, and news about the economy
Grandparents and Grandchildren
Retire on Your Own Terms
By Debra E. Novotny
Most Americans are aware that they need to save for retirement. It is a topic that is easy to brush aside to a later date because although the subject is important, it may not seem urgent. But the longer you put off some basic retirement planning, the harder it will be to catch up later.
We'd like to share with you a few important items about Social Security retirement benefits.
[Read more…]
Connected Health for Baby Boomers
Nora has knee pain. Combine 55 years of normal wear and tear, a bad fall skiing last year, and decades of wearing high heels left Nora with recurrent pain in her left knee. She researched doctors on the Internet and chose a female orthopedist at the local Bone Palace. Dr. Barnes ordered the usual tests. After Nora visited Radiology, she headed over to Dr. Barnes' office. Dr. Barnes showed Nora her MRI results on a tablet. Good news! Nora does not need knee replacement and will most likely see improvement from physical therapy. When Nora visited the therapist, her test results were instantly available on the integrated computer system. Nora's therapist set her up on a routine of visits to his practice, and also worked with her on a home schedule tied into an app on her smart phone. The app will not only remind her of home exercise, but will track her progress.
Nora's story and the almost instantaneous communication between doctor and patient illustrate the sea change technology is bringing to modern healthcare. New technology and tools are increasing connectivity between providers and patients. Accenture surveyed 3,700 physicians in eight countries and found that more doctors are adopting the use of EMRs (Electronic Medical Records) and joining HIEs (Health Information Exchanges). In essence, the digital doctor is now fully in the office.
Evolving technology has infiltrated healthcare in almost every conceivable way, from smart phone apps for diabetic compliance to physician e-prescriptions.
[Read more…]
That's Not My Age
I'd just started making notes for my talk on ageing, fashion and culture – with Ari Seth Cohen – at London College of Fashion later this month, when I saw this quote from Parisian designer Vanessa Bruno in the Telegraph:
'Focusing on age is boring. It's much more interesting to think about style.'
I've always believed that you don't have to have youth to have style, and would be interested to hear your thoughts on the matter – let's call it research! Thank you.