Author

Valeriia Sherina

University of Rochester Medicine

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

Biology Disciplines

Click to filter author papers

Bioinformatics· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Research Focus:deconvolution· 1 Research Focus:differential expression· 1 Organism:human· 1

Frequent Co-Authors

Matthew N. McCalliD· 3 shared Avi Z. RosenbergiD· 1 shared Benjamin Hsu· 1 shared Hartmut LandiD· 1 shared Helene R. McMurrayiD· 1 shared Marc K. HalushkaiD· 1 shared Tanzy LoveiD· 1 shared Winslow Powers· 1 shared

Activity by Year

2017-2022 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 17 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 papersBioinformatics

Matthew N. McCallORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Considerations for Deconvolution: A Case Study with GTEx Coronary Artery Tissues

Zachary Brehm, Valeriia Sherina, Avi Z. Rosenberg, Marc K. Halushka, Matthew N. McCall

The paper performs deconvolution on GTEx coronary artery data using CIBERSORT to assess challenges and limitations in estimating tissue composition from gene expression data.

bioRxiv · May 17, 2022 · PreprintBioinformatics

Auto-regressive modeling and diagnostics for qPCR amplification

Benjamin Hsu, Valeriia Sherina, Matthew N. McCall

The paper introduces a Smooth Transition Autoregressive model to improve qPCR data analysis by addressing autocorrelation in residuals caused by sequential dependence in fluorescence measurements.

Bioinformatics · Nov 18, 2020Peer-reviewedBioinformatics

Statistical Approaches to Decreasing the Discrepancy of Non-detects in qPCR Data

Valeriia Sherina, Helene R. McMurray, Winslow Powers, Hartmut Land, Tanzy Love, Matthew N. McCall

The paper introduces statistical methods to handle non-detects in qPCR data by modeling missing data mechanisms and using multiple imputation to reduce bias in gene expression estimation.

bioRxiv · Dec 8, 2017 · PreprintBioinformatics