Author

M. A. Moni

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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Bioengineering· 1 Cancer Biology· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:differential expression· 2 Assay:proteomics· 2 Approach:statistical model· 2 Assay:clinical cohort / trial· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

A. Barua· 1 shared A. T. Moin· 1 shared B. Sarkar· 1 shared D. U. S. Chowdhury· 1 shared F. Huq· 1 shared J. M. W. Quinn· 1 shared J. Q. Quinn· 1 shared K. C. Howladar· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 13 mutual co-author links

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1 shared paperBioengineering

A. Barua

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Exploring different virulent proteins of human respiratory syncytial virus for designing a novel epitope-based polyvalent vaccine: Immunoinformatics and molecular dynamics approaches

A. T. Moin, M. A. Ullah, R. B. Patil, N. A. Faruqui, B. Sarkar, Y. Araf, S. Das, K. M. K. Uddin, M. S. Hossain, M. F. Miah, M. A. Moni, D. U. S. Chowdhury, S. Islam

This study uses immunoinformatics and molecular dynamics to design a polyvalent epitope-based vaccine against RSV-A and RSV-B, selecting conserved epitopes and validating structural stability.

bioRxiv · Feb 2, 2022 · PreprintImmunology

Protein Expression Patterns in ovarian cancer cells Associated with Monofunctional Platinums Treatment

L. Arzuman, M. A. Moni, P. Beale, J. Q. Quinn, M. Molloy, J. M. W. Quinn, F. Huq

The paper identifies proteins associated with platinum resistance in ovarian cancer cells and links their expression to patient survival.

bioRxiv · May 7, 2019 · PreprintCancer Biology

Mining Significant Features of Diabetes Mellitus Applying Decision Trees: A Case Study In Bangladesh

K. C. Howladar, M. S. Satu, A. Barua, M. A. Moni

This study uses decision tree models to predict diabetes severity and identify significant features from a Bangladeshi dataset, finding plasma glucose, glucose 2hr after glucose, and HDL-cholesterol as key predictors.

bioRxiv · Nov 30, 2018 · PreprintBioengineering