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- Currently displaying 221 - 240 of 574 publications
Comprehensive Characterization of Cancer Driver Genes and Mutations.
Cell
(2018)
174
1034
(doi: 10.1016/j.cell.2018.07.034)
A decision theoretic approach to model evaluation in computational drug
discovery
(2018)
Emerging Patents in the Therapeutic Areas of Glioma and Glioblastoma.
Expert Opinion on Therapeutic Patents
(2018)
In Silico Computational Transcriptomics Reveals Novel Endocrine Disruptors in Largemouth Bass (Micropterus salmoides)
Environmental Science and Technology
(2018)
52
7553
(doi: 10.1021/acs.est.8b02805)
Computer-Assisted Discovery of Retinoid X Receptor Modulating Natural Products and Isofunctional Mimetics
J Med Chem
(2018)
61
5442
(doi: 10.1021/acs.jmedchem.8b00494)
Endocrine-disrupting chemicals in aquatic environment: what are the risks for fish gametes?
Fish Physiol Biochem
(2018)
44
1561
(doi: 10.1007/s10695-018-0507-z)
Identification of Nontoxic Substructures: A New Strategy to Avoid Potential Toxicity Risk
Toxicol Sci
(2018)
165
396
(doi: 10.1093/toxsci/kfy146)
Scaffold hopping from synthetic RXR modulators by virtual screening and de novo design
RSC Medicinal Chemistry
(2018)
9
1289
(doi: 10.1039/c8md00134k)
Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing
(2018)
333617
(doi: 10.1101/333617)
Can the inhibition of cytochrome P450 in aquatic invertebrates due to azole fungicides be estimated with in silico and in vitro models and extrapolated between species?
Aquatic toxicology (Amsterdam, Netherlands)
(2018)
201
11
A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
Journal of visualized experiments : JoVE
(2018)
2018
57633
(doi: 10.3791/57633)
Multiclassification Prediction of Enzymatic Reactions for Oxidoreductases and Hydrolases Using Reaction Fingerprints and Machine Learning Methods
J Chem Inf Model
(2018)
58
1169
(doi: 10.1021/acs.jcim.7b00656)
Conformal Regression for Quantitative Structure–Activity Relationship Modeling—Quantifying Prediction Uncertainty
J Chem Inf Model
(2018)
58
1132
(doi: 10.1021/acs.jcim.8b00054)
Corrigendum: In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts
Front Chem
(2018)
6
129
(doi: 10.3389/fchem.2018.00129)
A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria
Malaria journal
(2018)
17
160
(doi: 10.1186/s12936-018-2294-5)
Comprehensive Characterization of Cancer Driver Genes and Mutations
Cell
(2018)
173
371
(doi: 10.1016/j.cell.2018.02.060)
Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics.
Cell
(2018)
173
305
(doi: 10.1016/j.cell.2018.03.033)
Special Issue: Cheminformatics in Drug Discovery
ChemMedChem
(2018)
13
467
(doi: 10.1002/cmdc.201800123)
eMolTox: Prediction of molecular toxicity with confidence
Bioinformatics (Oxford, England)
(2018)
34
2508