Metabolism of Drugs at NIH Lecture
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Category Archives: Blog
Learning a Local-Variable Model of Aromatic and Conjugated Systems
Article available at: https://pubs.acs.org/doi/full/10.1021/acscentsci.7b00405.
Matthew K. Matlock, Na Le Dang, and S. Joshua Swamidass
Abstract: A collection of new approaches to building and training neural networks, collectively referred to as deep learning, are attracting attention in theoretical chemistry. Several groups aim to replace computationally expensive ab initio quantum mechanics … Continue Reading ››
Abstract: A collection of new approaches to building and training neural networks, collectively referred to as deep learning, are attracting attention in theoretical chemistry. Several groups aim to replace computationally expensive ab initio quantum mechanics … Continue Reading ›› 
Computationally Assessing the Bioactivation of Drugs by N-Dealkylation
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Openings: Grad, Postdoc, and Scientist
At this time (March 2017), we are looking for graduate students, postdoctoral fellows, and staff scientists to work on machine learning projects in medicine, chemistry and biology.
We are looking to train scientific leaders, capable of innovative computational research. Our group is working in close collaboration with leading clinicians and scientists on biomedical imaging, drug toxicity modeling … Continue Reading ››
A Computational Approach to Structural Alerts: Furans, Phenols, Nitroaromatics, and Thiophenes
A Computational Approach to Structural Alerts: Furans, Phenols, Nitroaromatics, and Thiophenes
Dang, N. L., Hughes, T. B., Miller, G. P., and Swamidass, S. J. (2017). Chemical Research in Toxicology, DOI: 10.1021/acs.chemrestox.6b00336
Abstract: Structural alerts are commonly used in drug discovery to identify molecules likely to form reactive metabolites, and … Continue Reading ››
Abstract: Structural alerts are commonly used in drug discovery to identify molecules likely to form reactive metabolites, and … Continue Reading ›› 
Deep Learning to Predict the Formation of Quinone Species in Drug Metabolism
Deep Learning to Predict the Formation of Quinone Species in Drug Metabolism
Hughes, T. B. and Swamidass, S. J. (2017). Chemical Research in Toxicology, 30(2), 642–656.
Abstract: Many adverse drug reactions are thought to be caused by electrophilically reactive drug metabolites that conjugate to nucleophilic sites within DNA and proteins,causing cancer … Continue Reading ›› 
DataEd Hackathon: Call For Participation
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Jon Marsh Joins Image Analysis Effort
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Identifying Cancer Mutations With Parsimony
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2016 CBSE Seminar Series
Dr Greg Bowman and I invite you to the Center for Systems Biology and Engineering seminar series for 2016-2017. The title of this series is “Mathematically Modeling Biological Systems”.
We hope for robust discussion, including critical feedback and scientific scrutiny of the presented work. This series is structured as a true seminar - not a colloquia … Continue Reading ››