Sutanu Bhattacharya

Assistant Professor

Auburn University at Montgomery

United States

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Sutanu Bhattacharya is an Assistant Professor at Auburn University at Montgomery, specializing in computational biology and protein structure research. His recent work includes the development of tools for protein contact map analysis, quality estimation, and protein folding simulations. Dr. Bhattacharya's contributions to the field also encompass advancements in modeling SARS-CoV-2 proteins and improvements in protein homology detection methodologies.

Articles (11)

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2024

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2022

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2022

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2021

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2021

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2021

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2021

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2020

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2020

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2020

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2020

Collaborators (6)

alberto Perez

Assistant Professor

University of Florida

UNITED STATES

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Rahmatullah Roche

Assistant Professor

Columbus State University

UNITED STATES

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Torsten Schwede

Professor

University of Basel

SWITZERLAND

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Dennis Della Corte

Brigham Young University

UNITED STATES

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Tsukasa Nakamura

Postdoctoral Research Fellow

JAPAN

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Sergei Grudinin

FRANCE

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Sutanu Bhattacharya

Research Interests

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About

Articles (11)

An interactive visualization tool for educational outreach in protein contact map overlap analysis

rrQNet : Protein contact map quality estimation by deep evolutionary reconciliation

DisCovER : distance‐ and orientation‐based covariational threading for weakly homologous proteins

Modeling SARS‐CoV‐2 proteins in the CASP‐commons experiment

Recent Advances in Protein Homology Detection Propelled by Inter-Residue Interaction Map Threading

Hybridized distance- and contact-based hierarchical structure modeling for folding soluble and membrane proteins

Hybridized distance-and contact-based hierarchical structure modeling for folding soluble and membrane proteins

PolyFold: An interactive visual simulator for distance-based protein folding

QDeep: distance-based protein model quality estimation by residue-level ensemble error classifications using stacked deep residual neural networks

Evaluating the significance of contact maps in low-homology protein modeling using contact-assisted threading

QDeep: Distance-based protein model quality estimation by residue-level ensemble error classifications using stacked deep residual neural networks

Collaborators (6)

alberto Perez

Rahmatullah Roche

Torsten Schwede

Dennis Della Corte

Tsukasa Nakamura

Sergei Grudinin

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