3 citations
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April 2019 in “Clinical Therapeutics” This study identified 19 genes targeted by 29 potential drugs for topical treatment of chemotherapy-induced alopecia, suggesting avenues for drug repositioning in pharmaceutical research.
232 citations
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January 2016 in “BMC Bioinformatics” This study found that using curated biomedical databases as training examples for information extraction tasks in Genome-Wide Association Studies can outperform cost-insensitive methods, demonstrating their potential use without expert annotation.
5 citations
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October 2014 in “Methods” This article describes how PESCADOR software assists in creating detailed biological pathway charts from PubMed abstracts, focusing on hair and breast development case studies without providing new clinical results.
This study introduces Kalya Research, an AI-driven tool designed to identify and categorize literature on complementary and alternative medicines, showing its effectiveness compared to Medline in finding relevant alopecia research within the context of breast cancer patients.
85 citations
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June 2015 in “Scientific Reports” This study applied semantic text-mining to identify phenotypes linked to over 6,000 diseases, demonstrating that these phenotypes can accurately identify known disease-associated genes, creating a human disease network based on phenotypic similarity.