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Prediction of Compound-Target Interactions of Natural Products Using Large-scale Drug and Protein Information.

, , and . DTMBIO@CIKM, page 15. ACM, (2015)

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Identification of a Specific Base Sequence of Pathogenic E. Coli through a Genomic Analysis., and . DTMBIO@CIKM, page 25-28. ACM, (2014)Identification of temporal association rules from time-series microarray data sets., , and . BMC Bioinform., (2009)hERG-Att: Self-attention-based deep neural network for predicting hERG blockers., and . Comput. Biol. Chem., (2020)A Systems Approach to Predict Oncometabolites via Context-Specific Genome-Scale Metabolic Networks., , , , , , and . PLoS Comput. Biol., (2014)Prediction of Compound-Target Interactions of Natural Products Using Large-scale Drug and Protein Information., , and . DTMBIO@CIKM, page 15. ACM, (2015)In Silico Simulation of Signal Cascades in Biomedical Networks Based on the Production Rule System., and . ISBRA, volume 10330 of Lecture Notes in Computer Science, page 356-361. Springer, (2017)Combining tissue transcriptomics and urine metabolomics for breast cancer biomarker identification., , , , and . Bioinform., 25 (23): 3151-3157 (2009)Identification of temporal association rules from time-series microarray data set: temporal association rules., , and . DTMBIO, page 21-28. ACM, (2008)Identification of Genomic Features in the Classification of Loss- and Gain-of-Function Mutation: Extended Abstract., , , and . DTMBIO@CIKM, page 23. ACM, (2014)DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences., , and . PLoS Comput. Biol., (2019)