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Data-Driven Drug Discovery and Molecular Informatics

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  • Currently displaying 221 - 240 of 574 publications
A decision theoretic approach to model evaluation in computational drug discovery
O Watson, I Cortes-Ciriano, A Taylor, JA Watson
(2018)
(link to publication)
Emerging Patents in the Therapeutic Areas of Glioma and Glioblastoma.
M Harris, F Svensson, L Kopanitsa, GR Ladds, D Bailey
– Expert Opinion on Therapeutic Patents
(2018)
(doi: 10.1080/13543776.2018.1494155.)
In Silico Computational Transcriptomics Reveals Novel Endocrine Disruptors in Largemouth Bass (Micropterus salmoides)
D Basili, J-L Zhang, J Herbert, K Kroll, ND Denslow, CJ Martyniuk, F Falciani, P Antczak
– Environ Sci Technol
(2018)
52,
7553
(doi: 10.1021/acs.est.8b02805)
Computer-Assisted Discovery of Retinoid X Receptor Modulating Natural Products and Isofunctional Mimetics.
D Merk, F Grisoni, L Friedrich, E Gelzinyte, G Schneider
– Journal of medicinal chemistry
(2018)
61,
5442
(doi: 10.1021/acs.jmedchem.8b00494)
Endocrine-disrupting chemicals in aquatic environment: what are the risks for fish gametes?
O Carnevali, S Santangeli, I Forner-Piquer, D Basili, F Maradonna
– Fish Physiology and Biochemistry
(2018)
44,
1561
(doi: 10.1007/s10695-018-0507-z)
Extending in silico protein target prediction models to include functional effects
LH Mervin, AM Afzal, L Brive, O Engkvist, A Bender
– Frontiers in Pharmacology
(2018)
9,
613
(doi: 10.3389/fphar.2018.00613)
Identification of Nontoxic Substructures: A New Strategy to Avoid Potential Toxicity Risk.
H Yang, L Sun, W Li, G Liu, Y Tang
– Toxicol Sci
(2018)
165,
396
(doi: 10.1093/toxsci/kfy146)
Scaffold hopping from synthetic RXR modulators by virtual screening and de novo design.
D Merk, F Grisoni, L Friedrich, E Gelzinyte, G Schneider
– RSC Medicinal Chemistry
(2018)
9,
1289
(doi: 10.1039/c8md00134k)
Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing
I Cortés-Ciriano, J-K Lee, R Xi, D Jain, Y Jung, L Yang, D Gordenin, L Klimczak, C-Z Zhang, D Pellman, P Park, on behalf of the PCAWG Structural Variation Working Group, the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Network
(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?
M Gottardi, JD Tyzack, A Bender, N Cedergreen
– Aquatic Toxicology
(2018)
201,
11
(doi: 10.1016/j.aquatox.2018.05.017)
A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes.
CN Schlaffner, GJ Pirklbauer, A Bender, JAJ Steen, JS Choudhary
– 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.
Y Cai, H Yang, W Li, G Liu, PW Lee, Y Tang
– J Chem Inf Model
(2018)
58,
1169
(doi: 10.1021/acs.jcim.7b00656)
Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty
F Svensson, N Aniceto, U Norinder, I Cortes-Ciriano, O Spjuth, L Carlsson, A Bender
– Journal of Chemical Information and Modeling
(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.
H Yang, L Sun, W Li, G Liu, Y Tang
– Frontiers in chemistry
(2018)
6,
129
(doi: 10.3389/fchem.2018.00129)
A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria
Y KalantarMotamedi, RT Eastman, R Guha, A Bender
– Malar J
(2018)
17,
160
(doi: 10.1186/s12936-018-2294-5)
Comprehensive Characterization of Cancer Driver Genes and Mutations
MH Bailey, C Tokheim, E Porta-Pardo, S Sengupta, D Bertrand, A Weerasinghe, A Colaprico, MC Wendl, J Kim, B Reardon, PK-S Ng, KJ Jeong, S Cao, Z Wang, J Gao, Q Gao, F Wang, EM Liu, L Mularoni, C Rubio-Perez, N Nagarajan, I Cortés-Ciriano, DC Zhou, W-W Liang, JM Hess, VD Yellapantula, D Tamborero, A Gonzalez-Perez, C Suphavilai, JY Ko, E Khurana, PJ Park, EM Van Allen, H Liang, MC3 Working Group, Cancer Genome Atlas Research Network, MS Lawrence, A Godzik, N Lopez-Bigas, J Stuart, D Wheeler, G Getz, K Chen, AJ Lazar, GB Mills, R Karchin, L Ding
– 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
L Ding, MH Bailey, E Porta-Pardo, V Thorsson, A Colaprico, D Bertrand, DL Gibbs, A Weerasinghe, K-L Huang, C Tokheim, I Cortés-Ciriano, R Jayasinghe, F Chen, L Yu, S Sun, C Olsen, J Kim, AM Taylor, AD Cherniack, R Akbani, C Suphavilai, N Nagarajan, JM Stuart, GB Mills, MA Wyczalkowski, BG Vincent, CM Hutter, JC Zenklusen, KA Hoadley, MC Wendl, L Shmulevich, AJ Lazar, DA Wheeler, G Getz, Cancer Genome Atlas Research Network
– Cell
(2018)
173,
305
(doi: 10.1016/j.cell.2018.03.033)
Special Issue: Cheminformatics in Drug Discovery
A Bender, N Brown
– ChemMedChem
(2018)
13,
467
(doi: 10.1002/cmdc.201800123)
eMolTox: Prediction of molecular toxicity with confidence
C Ji, F Svensson, A Zoufir, A Bender
– Bioinformatics (Oxford, England)
(2018)
34,
2508
(doi: 10.1093/bioinformatics/bty135)
In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts.
H Yang, L Sun, W Li, G Liu, Y Tang
– Frontiers in chemistry
(2018)
6,
30
(doi: 10.3389/fchem.2018.00030)

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