Author

J. Goldberg

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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Cell Biology· 2 Biophysics· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Assay:imaging· 3 Approach:deep learning· 2 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Approach:comparative / phylogenetic analysis· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

B. Migliori· 2 shared D. Paull· 2 shared A. Daigavane· 1 shared a. Duren-Lubancki· 1 shared A. Duren-Lubanski· 1 shared A. Geraschenko· 1 shared A. Narayanaswamy· 1 shared A.-C. Lindner· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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2 shared papersCell Biology

B. Migliori

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

A Highly-Efficient, Scalable Pipeline for Fixed Feature Extraction from Large-Scale High-Content Imaging Screens

G. Comolet, N. Bose, J. M. Winchell, a. Duren-Lubancki, T. Rusielewicz, g. Horn, j. Goldberg, D. Paull, B. Migliori

ScaleFExSM is a scalable pipeline for extracting interpretable features from high-content imaging data, improving drug response analysis and disease profiling.

bioRxiv · Jul 6, 2023Cell Biology

Multiscale imaging of corneal endothelium damage and effects of Rho Kinase inhibitor application in mouse models of acute ocular hypertension

Z. Cai, Y. Zhang, R. Fang, B. Brenner, J. Kweon, C. Sun, J. Goldberg, H. F. Zhang

The paper uses multiscale imaging to study corneal endothelium damage in mouse models, finding that Rho Kinase inhibitors reduce fully-distorted tight junctions under acute ocular hypertension.

bioRxiv · May 18, 2023Biophysics

Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts

L. Schiff, B. Migliori, Y. Chen, D. Carter, C. Bonilla, J. Hall, M. Fan, E. Tam, S. Ahadi, B. Fischbacher, A. Geraschenko, C. J. Hunter, S. Venugopalan, S. DesMarteau, A. Narayanaswamy, , Yang

This study develops a platform combining deep learning and high-content imaging to identify disease-specific phenotypes in Parkinson's fibroblasts, achieving high accuracy in distinguishing disease subtypes.

bioRxiv · Nov 13, 2020Cell Biology

Comparative transcriptomic analysis reveals conserved transcriptional programs underpinning organogenesis and reproduction in land plants

I. Julca, M. Flores, S. Proost, A.-C. Lindner, D. Hackenberg, L. Steinbachova, C. Michaelidis, S. Gomes Pereira, C. S. Misra, T. Kawashima, M. Borg, F. Berger, J. Goldberg, M. Johnson, D. Honys, , M. Mutwil

This study generates gene expression atlases for 10 plant species to identify conserved transcriptional programs in organogenesis and reproduction, revealing gene co-option as a key mechanism for organ evolution.

bioRxiv · Oct 29, 2020Evolutionary Biology