Found: 10
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An eigenvalue transformation technique for predicting drug-target interaction.
- Published in:
- Scientific Reports, 2015, p. 13867, doi. 10.1038/srep13867
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- Article
A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach.
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- Journal of Computer-Aided Molecular Design, 2015, v. 29, n. 4, p. 349, doi. 10.1007/s10822-014-9827-y
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- Article
Mutation status coupled with RNA-sequencing data can efficiently identify important non-significantly mutated genes serving as diagnostic biomarkers of endometrial cancer.
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- BMC Bioinformatics, 2017, v. 18, p. 39, doi. 10.1186/s12859-017-1891-6
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- Article
A Systematic Investigation of Computation Models for Predicting Adverse Drug Reactions (ADRs).
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- PLoS ONE, 2014, v. 9, n. 9, p. 1, doi. 10.1371/journal.pone.0105889
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- Article
Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction.
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- Scientific Reports, 2017, p. 43709, doi. 10.1038/srep43709
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- Article
Expression dynamics and relations with nearby genes of rat transposable elements across 11 organs, 4 developmental stages and both sexes.
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- BMC Genomics, 2017, v. 18, p. 1, doi. 10.1186/s12864-017-4078-7
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- Article
Computational identifying and characterizing circular RNAs and their associated genes in hepatocellular carcinoma.
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- PLoS ONE, 2017, v. 12, n. 3, p. 1, doi. 10.1371/journal.pone.0174436
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- Article
Post‐modified non‐negative matrix factorization for deconvoluting the gene expression profiles of specific cell types from heterogeneous clinical samples based on RNA‐sequencing data.
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- Journal of Chemometrics, 2018, v. 32, n. 11, p. N.PAG, doi. 10.1002/cem.2929
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- Article
Combination use of protein-protein interaction network topological features improves the predictive scores of deleterious non-synonymous single-nucleotide polymorphisms.
- Published in:
- Amino Acids, 2014, v. 46, n. 8, p. 2025, doi. 10.1007/s00726-014-1760-9
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- Article
Improving the Understanding of Pathogenesis of Human Papillomavirus 16 via Mapping Protein-Protein Interaction Network.
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- BioMed Research International, 2015, v. 2015, p. 1, doi. 10.1155/2015/890381
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- Article