Author

Shehab Sarar Ahmed

Bangladesh University of Engineering and TechnologyORCID 0000-0002-6063-2689Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:protein sequence· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

M. Sohel RahmaniD· 2 shared Zaara T. RifatiD· 2 shared Aarno V. PalotieiD· 1 shared Arthur J. CampbelliD· 1 shared David HokszaiD· 1 shared Dennis LaliD· 1 shared Eduardo Pérez‐PalmaiD· 1 shared Florence F. WagneriD· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

M. Sohel RahmanORCID

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2 papers

Recent·Most cited

Succinylated lysine residue prediction revisited

Shehab Sarar Ahmed, Zaara T. Rifat, Mohammad Saifur Rahman, M Sohel Rahman

The paper proposes deep learning models for predicting succinylated lysine residues using biochemical and physicochemical properties, achieving improved sensitivity and specificity through threshold tuning.

Briefings in Bioinformatics · Oct 28, 2022Peer-reviewedBioinformatics

Burden analysis of missense variants in 1,330 disease-associated genes on 3D provides insights into the mutation effects

Sumaiya Iqbal, Jakob Berg Jespersen, Eduardo Pérez‐Palma, Patrick May, David Hoksza, Henrike Heyne, Shehab Sarar Ahmed, Zaara T. Rifat, M. Sohel Rahman, Kasper Lage, Aarno V. Palotie, Jeffrey R. Cottrell, Florence F. Wagner, Mark J. Daly, Arthur J. Campbell, Dennis Lal

The paper analyzes missense variants in 1,330 disease genes using 3D protein structures to identify mutational hotspots and their functional impact.

bioRxiv · Mar 5, 2020 · PreprintGenetics