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Meta-analysis of whole-transcriptome data for prediction of novel genes associated with autism spectrum disorder.

, and . CSBio, page 56-61. ACM, (2017)

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Meta-analysis of whole-transcriptome data for prediction of novel genes associated with autism spectrum disorder., and . CSBio, page 56-61. ACM, (2017)Significant path selection improves the prediction of novel drug-target interactions., , and . SoICT, page 30-35. ACM, (2016)Assessing human disease phenotype similarity based on ontology., , and . RIVF, page 211-216. IEEE, (2016)Neighbor-favoring weight reinforcement to improve random walk-based disease gene prioritization., and . Comput. Biol. Chem., (2013)GPEC: A Cytoscape plug-in for random walk-based gene prioritization and biomedical evidence collection., and . Comput. Biol. Chem., (2012)RWRMTN: a tool for predicting disease-associated microRNAs based on a microRNA-target gene network., and . BMC Bioinform., 21 (1): 244 (2020)Multi-Task Regression Learning for Prediction of Response Against a Panel of Anti-Cancer Drugs in Personalized Medicine., and . MAPR, page 1-5. IEEE, (2018)Meta-analysis of computational methods for breast cancer classification., , , , , and . Int. J. Intell. Inf. Database Syst., 13 (1): 89-111 (2020)Disease subtyping using community detection from consensus networks., , , , , and . KSE, page 318-323. IEEE, (2020)Network-based ranking methods for prediction of novel disease associated microRNAs.. Comput. Biol. Chem., (2015)