Author

She Zhang

University of PittsburghORCID 0000-0001-9265-4498Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Systems Biology· 2 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Research Focus:gene regulatory network inference· 2 Assay:ATAC-seq· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Assay:ChIP-seq· 1 Research Focus:clustering· 1

Frequent Co-Authors

İvet BahariD· 3 shared Anne‐Ruxandra CarvunisiD· 1 shared Carl KingsfordiD· 1 shared Christopher ChurasiD· 1 shared Dexter R. PrattiD· 1 shared Fan ZhengiD· 1 shared Natalie SauerwaldiD· 1 shared Omer AcariD· 1 shared

Activity by Year

2017-2022 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 16 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersSystems Biology

İvet BaharORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Systems BiologyPLoS Computational BiologyPeer-reviewedMay 31, 2022

Elastic Network Modeling of Cellular Networks Unveils Sensor and Effector Genes that Control Information Flow

Omer Acar, She Zhang, İvet Bahar, Anne‐Ruxandra Carvunis

The paper uses elastic network modeling to identify sensor and effector genes in yeast that control information flow through long-range interactions.

7 citations

yeaststatistical model

𝕏 PostBluesky

Systems BiologyGenome biologyPeer-reviewedJan 7, 2021

Identifying persistent structures in multiscale 'omics data

Fan Zheng, She Zhang, Christopher Churas…·Trey E. Ideker

This paper introduces a method to identify persistent structures in multiscale omics data, expanding cell type catalogs and revealing SARS-COV-2 protein interactions.

48 citationstop 5%

mousebulk RNA-seq

𝕏 PostBluesky

GenomicsNucleic Acids ResearchPeer-reviewedMar 6, 2017

Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings

Natalie Sauerwald, She Zhang, Carl Kingsford, İvet Bahar

The paper uses a Gaussian Network Model (GNM) to predict chromosomal dynamics from Hi-C data, showing correlations with accessibility and gene coexpression.

28 citations

𝕏 PostBluesky