Author

D. L. Taylor

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell-cell communication· 2 Approach:deep learning· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

F. Pullara· 2 shared S. C. Chennubhotla· 2 shared S. Furman· 2 shared S. Uttam· 2 shared A. Gough· 1 shared A. H. Gough· 1 shared A. M. Stern· 1 shared A. Stern· 1 shared

Activity by Year

2019-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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2 shared papersCancer Biology

F. Pullara

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Unsupervised cellular phenotypic hierarchy enables spatial intratumor heterogeneity characterization, recurrence-associated microdomains discovery, and harnesses network biology from hyperplexed in-situ fluorescence images of colorectal carcinoma

S. Furman, A. Stern, S. Uttam, D. L. Taylor, F. Pullara, S. C. Chennubhotla

LEAPH identifies spatial microdomains and recurrence-associated signaling networks in colorectal carcinoma using hyperplexed fluorescence images.

bioRxiv · Oct 2, 2020 · PreprintCancer Biology

Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks

S. Uttam, A. M. Stern, S. Furman, F. Pullara, D. Spagnolo, L. Nguyen, A. H. Gough, C. Sevinsky, F. Ginty, D. L. Taylor, S. C. Chennubhotla

The paper develops a spatial analytics platform to predict colorectal cancer recurrence and infer tumor microenvironment networks from spatial data.

bioRxiv · Dec 11, 2019Cancer Biology

Applications of the Microphysiology Systems Database for Experimental ADME-Tox and Disease Models

M. Schurdak, L. Vernetti, L. Bergenthal, Q. K. Wolter, T. Y. Shun, S. Karcher, D. L. Taylor, A. Gough

The paper introduces a database for managing and analyzing microphysiological systems data, demonstrating its use in drug development and disease modeling.

bioRxiv · Sep 25, 2019Pharmacology & Toxicology