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Deep learning architectures for multi-label classification of intelligent health risk prediction.

, , , , , , , , and . BMC Bioinform., 18 (14): 121-131 (2017)

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Deep learning architectures for multi-label classification of intelligent health risk prediction., , , , , , , , and . BMC Bioinform., 18 (14): 121-131 (2017)Erratum to: A novel procedure on next generation sequencing data analysis using text mining algorithm., , , , , , , and . BMC Bioinform., (2016)Discovering Drug-Drug Associations in the FDA Adverse Event Reporting System Database with Data Mining Approaches., , , , , , , , , and 1 other author(s). BIBM, page 1197-1204. IEEE, (2021)Microarray scanner calibration curves: characteristics and implications., , , , , , , , , and 8 other author(s). BMC Bioinform., (2005)Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era., , , and . Briefings Bioinform., 18 (4): 682-697 (2017)The EDKB: an established knowledge base for endocrine disrupting chemicals., , , , , , , , and . BMC Bioinform., 11 (S-6): S5 (2010)ESSESA: An expert system for structure elucidation from spectra, 6. Substructure constraints from analysis of 13C-NMR spectra., , , and . J. Chem. Inf. Comput. Sci., 35 (6): 979-1000 (1995)Factorial analysis of error correction performance using simulated next-generation sequencing data., , , , , and . BIBM, page 1164-1169. IEEE Computer Society, (2016)The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models., , , , , , , , , and 193 other author(s). Nat Biotechnol, 28 (8): 827--838 (August 2010)Accurate Prediction and Recognition of Subfamilies of G Protein-Coupled Receptors from Amino Acid Sequences., , and . BIOCOMP, page 3-9. CSREA Press, (2009)