Výsledky vyhľadávania - "Machine Learning and Artificial Intelligence in Bioinformatics"

Comprehensive ensemble in QSAR prediction for drug discovery Autor Kwon, Sunyoung, Bae, Ho, Jo, Jeonghee, Yoon, Sungroh

“… Ensemble learning builds a set of diversified models and combines them. However, the most prevalent approach random forest and other ensemble approaches in QSAR prediction limit their model diversity to a single subject…”
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GAT-LI: a graph attention network based learning and interpreting method for functional brain network classification Autor Hu, Jinlong, Cao, Lijie, Li, Tenghui, Dong, Shoubin, Li, Ping

“…Background Autism spectrum disorders (ASD) imply a spectrum of symptoms rather than a single phenotype. ASD could affect brain connectivity at different degree…”
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Extracting chemical reactions from text using Snorkel Autor Mallory, Emily K., de Rochemonteix, Matthieu, Ratner, Alex, Acharya, Ambika, Re, Chris, Bright, Roselie A., Altman, Russ B.

“…Background Enzymatic and chemical reactions are key for understanding biological processes in cells. Curated databases of chemical reactions exist but these…”
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Deep neural networks for human microRNA precursor detection Autor Zheng, Xueming, Fu, Xingli, Wang, Kaicheng, Wang, Meng

“…Background MicroRNAs (miRNAs) play important roles in a variety of biological processes by regulating gene expression at the post-transcriptional level. So,…”
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Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses Autor Manduchi, Elisabetta, Fu, Weixuan, Romano, Joseph D., Ruberto, Stefano, Moore, Jason H.

“…) constitute an appealing approach to this end. However, in biomedical data, there are often baseline characteristics of the subjects in a study or batch effects that need to be adjusted for in order to better isolate the effects of the features…”
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Time-resolved evaluation of compound repositioning predictions on a text-mined knowledge network Autor Mayers, Michael, Li, Tong Shu, Queralt-Rosinach, Núria, Su, Andrew I.

“…Background Computational compound repositioning has the potential for identifying new uses for existing drugs, and new algorithms and data source aggregation…”
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