Author

Sayantani Basu

University of Illinois Urbana-Champaign

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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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:database / resource· 1 Approach:deep learning· 1 Assay:metagenomics· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Abhishake LahiriiD· 1 shared Anupam GautamiD· 1 shared Daniel H. HusoniD· 1 shared Debaleena Bhowmik· 1 shared Roy H. CampbelliD· 1 shared Sandip PauliD· 1 shared Wenhuan ZengiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 15 mutual co-author links

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1 shared paperBioinformatics

Abhishake LahiriORCID

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2 papers

Recent·Most cited

BioinformaticsBriefings in BioinformaticsPeer-reviewedSep 22, 2023

Microbiome Metabolome Integration Platform (MMIP): a web-based platform for microbiome and metabolome data integration and feature identification.

Anupam Gautam, Debaleena Bhowmik, Sayantani Basu…·Sandip Paul

MMIP integrates microbiome and metabolome data to identify features and predict metabolite signatures from amplicon sequencing data without requiring initial metabolomic analysis.

6 citations

metagenomicsstatistical model

𝕏 PostBluesky

BioinformaticsSpringer series in reliability engineeringPeer-reviewedJul 25, 2022

Classifying COVID-19 variants based on genetic sequences using deep learning models

Sayantani Basu, Roy H. Campbell

This paper proposes an alignment-free LSTM model for classifying 20 COVID-19 variants using k-mer sequences, achieving up to 92.5% test accuracy with one-vs-all classifiers.

21 citationstop 1%

whole-genome sequencingdeep learning

𝕏 PostBluesky