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Michael J Keiser

ORCID

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 18

Top Venues

bioRxiv : the preprint server for biology

Journal of chemical information and modeling

Journal of medicinal chemistry

Nature communications

University of California San Francisco

This page only lists publications with an associated author ORCID identifier.

Affiliation History

University of California San Francisco

United States

Assistant Professor :: Pharmaceutical Chemistry

Publications

Laura M Gunsalus, Michael J Keiser, Katherine S Pollard
ChromaFactor: deconvolution of single-molecule chromatin organization with non-negative matrix factorization. bioRxiv : the preprint server for biology (2023)
Daniel R Wong, Shino D Magaki, Harry V Vinters, William H Yong, Edwin S Monuki, Christopher K Williams, Alessandra Cadete Martini, Charles Decarli, Chris Khacherian, John P Graff, Brittany N Dugger, Michael J Keiser
Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels. Communications biology 6 (1) (2023)
Daniel R Wong, Shino D Magaki, Harry V Vinters, William H Yong, Edwin S Monuki, Christopher K Williams, Alessandra C Martini, Charles Decarli, Chris Khacherian, John P Graff, Brittany N Dugger, Michael J Keiser
Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels. bioRxiv : the preprint server for biology (2023)
Daniel R Wong, Shino D Magaki, Harry V Vinters, William H Yong, Edwin S Monuki, Christopher K Williams, Alessandra C Martini, Charles Decarli, Chris Khacherian, John P Graff, Brittany N Dugger, Michael J Keiser
Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels. bioRxiv : the preprint server for biology (2023)
Daniel R Wong, Shino D Magaki, Harry V Vinters, William H Yong, Edwin S Monuki, Christopher K Williams, Alessandra C Martini, Charles Decarli, Chris Khacherian, John P Graff, Brittany N Dugger, Michael J Keiser
Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels. bioRxiv : the preprint server for biology (2023)
William Connell, Kristle Garcia, Hani Goodarzi, Michael J Keiser
Learning chemical sensitivity reveals mechanisms of cellular response. bioRxiv : the preprint server for biology (2023)
Alexandre V Fassio, Laura Shub, Luca Ponzoni, Jessica L McKinley, Matthew J O'Meara, Rafaela S Ferreira, Michael J Keiser, Raquel C de Melo Minardi
Prioritizing Virtual Screening with Interpretable Interaction Fingerprints. Journal of chemical information and modeling 62 (18) (2022)
Daniel R Wong, Ziqi Tang, Nicholas C Mew, Sakshi Das, Justin Athey, Kirsty E McAleese, Julia K Kofler, Margaret E Flanagan, Ewa Borys, Charles L White, Atul Janardhan Butte, Brittany N Dugger, Michael J Keiser
Deep learning from multiple experts improves identification of amyloid neuropathologies. Acta neuropathologica communications 10 (1) (2022)
Albert T Young, Kristen Fernandez, Jacob Pfau, Rasika Reddy, Nhat Anh Cao, Max Y von Franque, Arjun Johal, Benjamin V Wu, Rachel R Wu, Jennifer Y Chen, Raj P Fadadu, Juan A Vasquez, Andrew Tam, Michael J Keiser, Maria L Wei
Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models. NPJ digital medicine 4 (1) (2021)
Elena L Cáceres, Nicholas C Mew, Michael J Keiser
Adding Stochastic Negative Examples into Machine Learning Improves Molecular Bioactivity Prediction. Journal of chemical information and modeling 60 (12) (2020)
Kangway V Chuang, Laura M Gunsalus, Michael J Keiser
Learning Molecular Representations for Medicinal Chemistry. Journal of medicinal chemistry 63 (16) (2020)
Ziqi Tang, Kangway V Chuang, Charles DeCarli, Lee-Way Jin, Laurel A Beckett, Michael J Keiser, Brittany N Dugger
Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline. Nature communications 10 (1) (2019)
Kangway V Chuang, Michael J Keiser
Adversarial Controls for Scientific Machine Learning. ACS chemical biology 13 (10) (2019)
Matthew N McCarroll, Leo Gendelev, Reid Kinser, Jack Carson Taylor, Giancarlo Noe Bruni, Douglas Myers-Turnbull, Cole Helsell, Amanda Carbajal, Capria Rinaldi, Hye Jin Kang, Jung Ho Gong, Jason K Sello, Susumu Tomita, Randall T Peterson, Michael J Keiser, David Kokel
Zebrafish behavioural profiling identifies GABA and serotonin receptor ligands related to sedation and paradoxical excitation. Nature communications 10 (1) (2019)
Kangway V Chuang, Michael J Keiser
Comment on "Predicting reaction performance in C-N cross-coupling using machine learning". Science (New York, N.Y.) 362 (6416) (2018)
Seth D Axen, Xi-Ping Huang, Elena L Cáceres, Leo Gendelev, Bryan L Roth, Michael J Keiser
A Simple Representation of Three-Dimensional Molecular Structure. Journal of medicinal chemistry 60 (17) (2017)
John J Irwin, Garrett Gaskins, Teague Sterling, Michael M Mysinger, Michael J Keiser
Predicted Biological Activity of Purchasable Chemical Space. Journal of chemical information and modeling 58 (1) (2017)
Giancarlo Noe Bruni, Andrew J Rennekamp, Andrea Velenich, Matthew McCarroll, Leo Gendelev, Ethan Fertsch, Jack Taylor, Parth Lakhani, Dennis Lensen, Tama Evron, Paul J Lorello, Xi-Ping Huang, Sabine Kolczewski, Galen Carey, Barbara J Caldarone, Eric Prinssen, Bryan L Roth, Michael J Keiser, Randall T Peterson, David Kokel
Zebrafish behavioral profiling identifies multitarget antipsychotic-like compounds. Nature chemical biology 12 (7) (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Michael J Keiser