{'fraction_non_alphanumeric': 0.01784037558685446, 'fraction_numerical': 0.003755868544600939, 'mean_word_length': 5.383233532934132, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
TMABoost: an integrated system for comprehensive management of tissue microarray data

In the last decade, high-throughput technologies such as DNA and tissue microarrays (TMAs) have become a means of large-scale investigation of gene expression, providing a plethora of new biomedical data in a relatively short time. Data collection and organization are critical aspects in this process to ensure the quality and reliability of future data interpretation. In this work, we propose a comprehensive approach to handle TMA data with the aim of supporting and promoting biomarker development. We describe a web-based system for the complete management of tissue microarray data in the field of pathology. The system has been in use since June, 2003. Our approach includes automatic localization and identification of tissue microarray samples, and quantitative image analysis that allows high-throughput screening of TMAs by ensuring nonsubjective measures and novel prognosis associations. In this paper, we present the architecture and the components of this system