Academics
Faculty
Dr. Ankita AgarwalAssistant Professor
Bio
Dr. Ankita Agarwal is an experienced academician and researcher who holds a PhD in Computational Biology from IIT Kharagpur and Gold medal in M. Tech. (Bioinformatics) from West Bengal University of Technology. With a background in Chemistry and Bioinformatics, she has transitioned into the field of Bioengineering and Chemical Engineering, and joined as faculty at MIT-WPU. She brings a unique blend of expertise in both experimental and computational techniques, and has published research articles in leading scientific journals. Dr. Agarwal teaches a professional elective course of Bioinformatics and regular courses such as Data Science for engineers, Python for Bioinformatics and Artificial Intelligence and Machine Learning in Biology to undergraduate students. With more than six year of previous research experience in DBT and CSIR-funded projects on computational analysis and prediction of protein-RNA interactions in human RNA-binding proteins, Dr. Agarwal’s current interest of research is to understand the sequence-structure-function paradigm of protein-RNA complexes especially in human RNA-binding proteins. With demonstrated expertise in computational biology, Dr. Agarwal is committed to fostering innovative approaches in teaching and research, and mentoring students towards achieving their full potential.
Research Focus
Computational Biology, Bioinformatics, Computational Modelling, Molecular Dynamics Simulation, Machine-learning algorithms for disease prediction with special emphasis on neurodegenerative diseases and cancers associated with human RNA-binding proteins.
Publications List
1. Agarwal, A., Kant, S., & Bahadur, R.P. (2023). Efficient mapping of RNA-binding residues in RNA-binding proteins using local sequence features of binding site residues in protein-RNA complexes. Proteins: Structure, Function and Bioinformatics, 91(9), 1361-1379. https://doi.org/10.1002/prot.26528.
2. Agarwal, A., & Bahadur, R.P. (2023). Modular architecture and functional annotation of human RNA-binding proteins containing RNA recognition motif. Biochimie, 209, 116-130. https://doi.org/10.1016/j.biochi.2023.01.017
3. Agarwal, A., Alagar, S., Kant, S., & Bahadur, R. P. (2023). Molecular insights into binding dynamics of tandem RNA recognition motifs (tRRMs) of human antigen R (HuR) with mRNA and the effect of point mutations in impaired HuR-mRNA recognition. Journal of biomolecular structure & dynamics, 41(11), 4830–4846. https://doi.org/10.1080/07391102.2022.2073270.
4. Agarwal, A., Singh, K., Kant, S., & Bahadur, R.P. (2022). A comparative analysis of machine learning classifiers for predicting protein-binding nucleotides in RNA sequences. Computational and Structural Biotechnology Journal, 20, 3195–3207. https://doi.org/10.1016/j.csbj.2022.06.036.
5. Ray, A., Agarwal, A. & Bhattacharyya, D. (2017). Effect of single-residue bulges on RNA double-helical structures: crystallographic database analysis and molecular dynamics simulation studies. J Mol Model, 23, 311. https://doi.org/10.1007/s00894-017-3480-z.
Google Scholar Link
https://scholar.google.com/citations?user=fWp5sc0AAAAJ&hl=en
Scopus Link
https://www.scopus.com/authid/detail.uri?authorId=57196399281
ORCID Link