Author

Md. Adnan Munim

Noakhali Science and Technology UniversityORCID 0009-0006-7600-3162Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:protein sequence· 1 Assay:protein structure· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Md. Shahadat HossainiD· 3 shared Arpita Singha RoyiD· 2 shared Atqiya Fariha· 2 shared Hasan Al RezaiD· 2 shared Mahafujul Islam Quadery TonmoyiD· 2 shared Mohammad Rahanur AlamiD· 2 shared Newaz Mohammed BahaduriD· 2 shared A. Q. M. Sala Uddin PathaniD· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersBioinformatics

Md. Shahadat HossainORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 16, 2023

A Computational Approach for Structural and Functional Analyses of Disease-associated Mutations in the Human CYLD Gene

Arpita Singha Roy, Tasmiah Feroz, Md. Kobirul Islam…·Md. Shahadat Hossain

The paper identifies deleterious nsSNPs in the CYLD gene using computational tools and highlights two significant mutations affecting CYLD-ubiquitin interaction and protein stability.

DOI 10.1101/2023.11.16.567342

humanprotein structure

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BioinformaticsInformatics in Medicine UnlockedPeer-reviewedJan 1, 2021

Genome-wide identification and prediction of SARS-CoV-2 mutations show an abundance of variants: Integrated study of bioinformatics and deep neural learning.

Md. Shahadat Hossain, A. Q. M. Sala Uddin Pathan, Md Nur Islam…·Md. Mizanur Rahaman

This study identifies and predicts SARS-CoV-2 mutations using bioinformatics and deep learning, finding high mutation rates and future trends in mutation types.

19 citations

viruswhole-genome sequencing

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BioinformaticsbioRxivPreprintJun 13, 2020

Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach

Arpita Singha Roy, Mahafujul Islam Quadery Tonmoy, Atqiya Fariha…·Md. Shahadat Hossain

This study designs a multi-epitope peptide vaccine against SARS-CoV-2 using immunoinformatics tools, identifying three epitopes with high binding affinity and global population coverage.

3 citations

protein sequencestatistical model

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