Author

Sean H. Rice

Texas Tech UniversityORCID 0000-0003-1626-9891Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Assay:proteomics· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Saba NafeesiD· 2 shared Aaron McGeeveriD· 1 shared Ahmet Can SolakiD· 1 shared Catherine A. WakemaniD· 1 shared Miles WoollacottiD· 1 shared Olivia YooiD· 1 shared Phoenix LoganiD· 1 shared Venkata N. P. VemuriiD· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 22 mutual co-author links

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2 shared papersBioinformatics

Saba NafeesORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 14, 2022

ortho_seqs: A Python tool for sequence analysis and higher order sequence-phenotype mapping

Saba Nafees, Venkata N. P. Vemuri, Miles Woollacott…·Sean H. Rice

ortho_seqs quantifies sequence-phenotype interactions using tensor-based orthogonal polynomials, demonstrating its application to synthetic antibody sequences and other datasets.

DOI 10.1101/2022.09.14.506443

DNA methylationproteomics

𝕏 PostBluesky

BioinformaticsNAR Genomics and BioinformaticsPeer-reviewedDec 1, 2020

Analyzing Genomic Data Using Tensor-Based Orthogonal Polynomials with Application to Synthetic RNAs

Saba Nafees, Sean H. Rice, Catherine A. Wakeman

The paper introduces a tensor-based orthogonal polynomial method to analyze sequence-phenotype relationships in synthetic RNAs, showing potential for intramolecular binding detection.

1 citation

bulk RNA-seqstatistical model

𝕏 PostBluesky