Author

C. Churas

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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Biophysics· 1 Cell Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:benchmark study· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

S. Liu· 2 shared A. Garcia-Sastre· 1 shared A. L. Oom· 1 shared A. M. O'Neill· 1 shared A. P. Gounder· 1 shared A. Rodriguez-Frandsen· 1 shared C. Benner· 1 shared C. Nguyen· 1 shared

Activity by Year

2018-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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Curved chords = mutual co-authorship

2 shared papersMicrobiology

S. Liu

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Functional Landscape of SARS-CoV-2 Cellular Restriction

L. Martin-Sancho, M. K. Lewinski, L. Pache, C. Stoneham, X. YIN, D. Pratt, C. Churas, S. B. Rosenthal, S. Liu, P. D. De Jesus, A. M. O'Neill, A. P. Gounder, C. Nguyen, Y. Pu, A. L. Oom, , S. Chanda

This study identifies key interferon stimulated genes (ISGs) that restrict SARS-CoV-2 infection by inhibiting viral entry, RNA synthesis, and release.

bioRxiv · Sep 29, 2020Microbiology

Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking

J. Wagner, C. Churas, S. Liu, R. Swift, M. Chiu, C. Shao, V. Feher, S. Burley, M. Gilson, R. Amaro

CELPP evaluates docking workflows by challenging participants to predict new protein-ligand structures weekly, assessing accuracy to identify strengths and weaknesses in drug docking methods.

bioRxiv · Nov 18, 2018Biophysics

CDeep3M - Plug-and-Play cloud based deep learning for image segmentation of light, electron and X-ray microscopy

M. Haberl, C. Churas, L. Tindall, D. Boassa, S. Phan, E. A. Bushong, M. Madany, R. Akay, T. J. Deerinck, S. T. Peltier, M. H. Ellisman

CDeep3M provides a cloud-based deep learning tool for image segmentation across light, electron, and X-ray microscopy, simplifying access and computation for researchers.

bioRxiv · Jun 21, 2018Cell Biology