Author

Elizabeth Peker

Rutgers, The State University of New Jersey

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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Genetic & Genomic Medicine· 3 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 4 Approach:machine learning (classical)· 3 Assay:whole-genome sequencing· 3 Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2

Frequent Co-Authors

Rishabh NarayananiD· 4 shared Saman ZeeshaniD· 4 shared William DeGroatiD· 4 shared Zeeshan AhmediD· 4 shared Bruce T. LiangiD· 1 shared Dinesh MendheiD· 1 shared Habiba AbdelhalimiD· 1 shared Neev Sheth· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 29 mutual co-author links

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4 shared papersGenetic & Genomic Medicine

Rishabh NarayananORCID

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4 papers

Recent·Most cited

Translational bioinformatics and machine learning framework for biomarker discovery, disease prediction, and patient profiling for precision medicine

Zeeshan Ahmed, Prithvi Govindareddy, William DeGroat, Rishabh Narayanan, Elizabeth Peker, Saman Zeeshan

medRxiv · May 27, 2026 · PreprintGenetic & Genomic Medicine

3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization

Rishabh Narayanan, Elizabeth Peker, William DeGroat, Dinesh Mendhe, Saman Zeeshan, Zeeshan Ahmed

This paper introduces 3D IntelliGenes, a tool for visualizing AI/ML results on multi-omics data to discover biomarkers and predict diseases through 3D clustering and feature analysis.

medRxiv · Mar 25, 2025 · PreprintGenetic & Genomic Medicine

VAREANT: a bioinformatics application for gene variant reduction and annotation

Rishabh Narayanan, William DeGroat, Elizabeth Peker, Saman Zeeshan, Zeeshan Ahmed

VAREANT is a bioinformatics tool that simplifies variant data preprocessing, annotation, and AI/ML preparation for genomic analysis.

Bioinformatics Advances · Dec 26, 2024Peer-reviewedGenetic & Genomic Medicine

Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases

William DeGroat, Habiba Abdelhalim, Elizabeth Peker, Neev Sheth, Rishabh Narayanan, Saman Zeeshan, Bruce T. Liang, Zeeshan Ahmed

The paper develops a multimodal AI/ML framework to identify biomarkers and predict cardiovascular disease using multi-omics data, finding a 27-component signature with high predictive accuracy.

Scientific Reports · Nov 3, 2024Peer-reviewedGenomics