Matthew Matlock, MD PhD
Matthew Matlock, MD PhD
Resident, Emergency Medicine, Washington University in St Louis
Verified email at
Cited by
Cited by
CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer
M Griffith, NC Spies, K Krysiak, JF McMichael, AC Coffman, AM Danos, ...
Nature genetics 49 (2), 170-174, 2017
XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks
J Zaretzki, M Matlock, SJ Swamidass
Journal of chemical information and modeling 53 (12), 3373-3383, 2013
Recurrent somatic mutations affecting B-cell receptor signaling pathway genes in follicular lymphoma
K Krysiak, F Gomez, BS White, M Matlock, CA Miller, L Trani, CC Fronick, ...
Blood, The Journal of the American Society of Hematology 129 (4), 473-483, 2017
Deep learning global glomerulosclerosis in transplant kidney frozen sections
JN Marsh, MK Matlock, S Kudose, TC Liu, TS Stappenbeck, JP Gaut, ...
IEEE transactions on medical imaging 37 (12), 2718-2728, 2018
XenoSite server: a web-available site of metabolism prediction tool
MK Matlock, TB Hughes, SJ Swamidass
Bioinformatics 31 (7), 1136-1137, 2015
Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples
EK Barnell, P Ronning, KM Campbell, K Krysiak, BJ Ainscough, LM Sheta, ...
Genetics in Medicine 21 (4), 972-981, 2019
ProteomeScout: a repository and analysis resource for post-translational modifications and proteins
MK Matlock, AS Holehouse, KM Naegle
Nucleic acids research 43 (D1), D521-D530, 2015
Modeling small-molecule reactivity identifies promiscuous bioactive compounds
MK Matlock, TB Hughes, JL Dahlin, SJ Swamidass
Journal of chemical information and modeling 58 (8), 1483-1500, 2018
Deep learning quantification of percent steatosis in donor liver biopsy frozen sections
L Sun, JN Marsh, MK Matlock, L Chen, JP Gaut, EM Brunt, SJ Swamidass, ...
EBioMedicine 60, 2020
The metabolic rainbow: deep learning phase I metabolism in five colors
NL Dang, MK Matlock, TB Hughes, SJ Swamidass
Journal of chemical information and modeling 60 (3), 1146-1164, 2020
‘Black box’to ‘conversational’machine learning: Ondansetron reduces risk of hospital-acquired venous thromboembolism
A Datta, MK Matlock, N Le Dang, T Moulin, KF Woeltje, EL Yanik, ...
IEEE Journal of Biomedical and Health Informatics 25 (6), 2204-2214, 2020
Effective tag mechanisms for evolving coordination
M Matlock, S Sen
Proceedings of the 6th international joint conference on Autonomous agents …, 2007
Learning a local-variable model of aromatic and conjugated systems
MK Matlock, NL Dang, SJ Swamidass
ACS Central Science 4 (1), 52-62, 2018
Scaffold network generator: a tool for mining molecular structures
MK Matlock, JM Zaretzki, SJ Swamidass
Bioinformatics 29 (20), 2655-2656, 2013
Effective tag mechanisms for evolving cooperation.
MK Matlock, S Sen
AAMAS (1), 489-496, 2009
Dual mechanisms suppress meloxicam bioactivation relative to sudoxicam
DA Barnette, MA Schleiff, LR Osborn, N Flynn, M Matlock, SJ Swamidass, ...
Toxicology 440, 152478, 2020
Deep learning long-range information in undirected graphs with wave networks
MK Matlock, A Datta, N Le Dang, K Jiang, SJ Swamidass
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
Combined analysis of phenotypic and target-based screening in assay networks
SJ Swamidass, CN Schillebeeckx, M Matlock, MR Hurle, P Agarwal
Journal of Biomolecular Screening 19 (5), 782-790, 2014
Sharing chemical relationships does not reveal structures
M Matlock, SJ Swamidass
Journal of Chemical Information and Modeling 54 (1), 37-48, 2014
Systematic redaction for neuroimage data
M Matlock, N Schimke, L Kong, S Macke, J Hale
International Journal of Computational Models and Algorithms in Medicine …, 2012
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