Author

Shara Balakrishnan

University of California, Santa Barbara

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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Synthetic Biology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Organism:bacteria (other)· 1 Approach:deep learning· 1 Organism:E. coli· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Aqib HasnainiD· 2 shared Enoch YeungiD· 2 shared Amin Espah BorujeniiD· 1 shared Christopher A. VoigtiD· 1 shared Dennis M. JoshyiD· 1 shared Diveena Becker· 1 shared Jen Smith· 1 shared Joshua A. UrrutiaiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersSystems Biology

Aqib HasnainORCID

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2 papers

Recent·Most cited

Disentangling gene expression burden identifies generalizable phenotypes induced by synthetic gene networks

Aqib Hasnain, Amin Espah Borujeni, Yongjin Park, Diveena Becker, Paul Maschhoff, Joshua A. Urrutia, Linus Rydell, Shara Balakrishnan, Yuval Dorfan, Christopher A. Voigt, Enoch Yeung

The paper identifies synthetic gene network-induced phenotypes by analyzing gene expression in E. coli and validates them through antibiotic resistance experiments.

bioRxiv · Jun 29, 2023 · PreprintSystems Biology

Learning perturbation-inducible cell states of novel compounds from observability analysis of transcriptome dynamics

Aqib Hasnain, Shara Balakrishnan, Dennis M. Joshy, Jen Smith, Steven B. Haase, Enoch Yeung

The paper develops a machine learning approach to identify perturbation-inducible genes from time-series RNA-seq data, applying it to discover malathion-responsive promoters in Pseudomonas fluorescens.

bioRxiv · May 27, 2022 · PreprintSynthetic Biology