Author

Mohammad Kawsar Sharif Siam

BRAC UniversityORCID 0000-0001-8882-6381Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1 Organism:virus· 1

Frequent Co-Authors

Mohammad Umer Sharif ShohaniD· 3 shared Easin Uddin SyediD· 1 shared Kazi Injamamul HoqueiD· 1 shared Mirza Ashikul Beg· 1 shared Mohammad Ali MoniiD· 1 shared Umar Faruq ChowdhuryiD· 1 shared Zaira Zafroon· 1 shared

Activity by Year

2020-2020 · peak 3/yr

Co-Author Collaboration Network

7 top collaborators · 12 mutual co-author links

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3 shared papersBioinformatics

Mohammad Umer Sharif ShohanORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

BioinformaticsGenomicsPeer-reviewedDec 13, 2020

A Computational Approach to Design Potential siRNA Molecules as a Prospective Tool for Silencing Nucleocapsid Phosphoprotein and Surface Glycoprotein Gene of SARS-CoV-2

Umar Faruq Chowdhury, Mohammad Umer Sharif Shohan, Kazi Injamamul Hoque…·Mohammad Ali Moni

This study designs 8 siRNA molecules targeting SARS-CoV-2's nucleocapsid phosphoprotein and surface glycoprotein genes using sequence conservation and thermodynamic properties.

97 citationstop 2%

virusstatistical model

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BioinformaticsbioRxivPreprintApr 28, 2020

Investigation of the anti-TB potential of selected alkaloid constituents using molecular docking approach

Mohammad Kawsar Sharif Siam, Mohammad Umer Sharif Shohan, Zaira Zafroon

This study uses molecular docking to evaluate the anti-TB potential of alkaloid compounds against three Mycobacterium tuberculosis proteins, identifying promising candidates with high binding affinity.

3 citations

machine learning (classical)drug response / drug discovery

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GeneticsbioRxivPreprintApr 10, 2020

Combinatorial analysis of gene regulatory network reveals the causal genetic basis of breast cancer and gene-specific personalized drug treatments

Mohammad Kawsar Sharif Siam, Mohammad Umer Sharif Shohan, Easin Uddin Syed

This study uses genomic and proteomic data to analyze gene regulatory networks in breast cancer, identifying key genes and pathways involved in disease development and suggesting potential drug targets.

2 citations

humanbulk RNA-seq

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