Michael J. Keiser

QB3 — United States

Computer Science · Physical Sciences

32h-index8.3kcitations123works3.42yr avg
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Research Topics

Computational Drug Discovery Methods(42), Protein Structure and Dynamics(16), Receptor Mechanisms and Signaling(16), AI in cancer detection(15), Machine Learning in Materials Science(15)

Publications123 total

Automating quantitative morphometric analysis of arteriolosclerotic blood vessels using machine learning
Alzheimer s & Dementia·2025Open Access
Crowd‐powered histopathological analysis of brain samples from persons with Alzheimer disease: a Citizen Science pilot study inclusive of Hispanic communities
Alzheimer s & Dementia·2025Open Access
Deep learning finds convergent melanocytic morphology despite noisy archival slides
Cell Reports Methods·2025· 1 citedOpen Access
A Pilot Study of the Pharmacodynamic Impact of SSRI Drug Selection and Beta-1 Receptor Genotype (ADRB1) on Cardiac Vital Signs in Depressed Patients: A Novel Pharmacogenetic Approach
Psychopharmacology Bulletin·2025
Autoparty: Machine Learning-Guided Visual Inspection of Molecular Docking Results
Journal of Chemical Information and Modeling·2025
0823 Application of cutaneous melanoma multiple instance learning model for conjunctival melanoma whole slide images
Journal of Investigative Dermatology·2025Open Access
0105 Addressing generalizability and clinical utility of AI-enabled virtual-IHC for melanocytic cells
Journal of Investigative Dermatology·2025
Cell-type-directed network-correcting combination therapy for Alzheimer’s disease
Cell·2025· 20 citedOpen Access
The polypharmacology of psychedelics reveals multiple targets for potential therapeutics
Neuron·2025· 21 cited
Accelerating biomedical discoveries in brain health through transformative neuropathology of aging and neurodegeneration
Neuron·2025· 4 citedOpen Access
MIC: A deep learning tool for assigning ions and waters in cryo-EM and crystal structures
Nature Communications·2025· 5 citedOpen Access
Evolutionary-scale enzymology enables exploration of a rugged catalytic landscape
Science·2025· 12 citedOpen Access
An improved model for prediction of de novo designed proteins with diverse geometries
2025Open Access
Leveraging Protein Language Model Embeddings for Catalytic Turnover Prediction of Adenylate Kinase Orthologs in a Low-Data Regime
arXiv (Cornell University)·2025Open Access
Applying machine learning to assist in the morphometric assessment of brain arteriolosclerosis through automation
PubMed·2025Open Access
Accelerating Biomedical Discoveries in Aging and Neurodegeneration Through Transformative Neuropathology
Preprints.org·2025· 1 citedOpen Access
Adaptation of Enzyme Catalysis Across a Natural Evolutionary Landscape
Structural Dynamics·2025Open Access
ChromaFactor: Deconvolution of single-molecule chromatin organization with non-negative matrix factorization
PLoS Computational Biology·2025Open Access
Network-aware self-supervised learning enables high-content phenotypic screening for genetic modifiers of neuronal activity dynamics
2025Open Access
Fuzz Testing Molecular Representation Using Deep Variational Anomaly Generation
Journal of Chemical Information and Modeling·2025· 1 citedOpen Access
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Frequent Co-authors

Brian K. Shoichet(14), John J. Irwin(9), Bryan L. Roth(8), Kangway V. Chuang(6), Brittany N. Dugger(6), Leo Gendelev(6), David Kokel(6), Matthew N. McCarroll(5), Christian Laggner(4), Jérôme Hert(4), Jack C. Taylor(4), Vincent Setola(3), Ziqi Tang(3), Charles DeCarli(3), Randall T. Peterson(3), Douglas Myers-Turnbull(3), Laura Shub(3), Daniel R. Wong(3), Atheir I. Abbas(2), Kelan Thomas(2)