Machine learning in bioinformatics: prediction of target proteins based on sequence analysis.
Investigate molecular mechanism and binding free energy using molecular dynamics simulation.
Development of coarse-grained model of bio-molecules.
Parameterization of force-field.
Find relation between protein's structure-dynamics-function.
5/4/2017 - 4/4/2019 - "Investigation of Staphylococcus Aureaus Protein A Adsorption on Mixed Self-Assembled Monolayers for Biosensor Development Using Computer Simulations", 066/2016/A, Science and Technology Development Fund, Macao S.A.R. (FDCT), MOP 351,850 (Postdoct Fellow).
"Molecular dynamics information improves cis-peptide based function annotation of proteins." Sreetama Das, Bhadra, Pratiti , S. Ramakumar and Debnath Pal. Journal of Proteome Research, 16, 2936-2946 2017 . DOI: 10.1021/acs.jproteome.7b00217 link
"Pipeline for inferring protein function from dynamics using coarse-grained molecular mechanics forcefield" Bhadra, Pratiti Pal, Debnath; Computer in Biology and Medicine.83, 134-142 (2017) DOI: 10.1016/j.compbiomed.2017.02.00 link
“De novo inference of protein function from coarse-grained dynamics” Bhadra, Pratiti; Pal, Debnath Protiens:
Structure, Function and Bioinformatics. 2014; 82:2443–2454 (link)
Publication under review
"A machine learning approach to anticancer peptide prediction using amino acid composition, prole similarity and water-membrane partitioning free energy" Pratiti Bhadra and Shirley W.I. Siu
"distrAMP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest" Pratiti Bhadra , Jielu Yan, Jinyan Li, Simon Fong, and Shirley W. I. Siu
"Comparison of Biomolecular Force Fields for Alkanethiol Self-Assembled Monolayer Simulations" Pratiti Bhadra and Shirley W.I. Siu
June 2014-December 2015, Research Associate, Biomolecular Computational Laboratory, Indian Institute of Science, Bangalore, India.
April 2008 – July 2009; Research Assistant, Department of Electrical Communication Engineering, IISc (laboratory of Dr. Neelesh B. Mehta.
Oral Presentation 1. “Comparing Lipid Force Fields for the Simulation of Self-Assembled Monolayer (SAM) and Protein-Surface Interaction” The 10th International Conference on Computational Physics (ICCP10), 2017 (16-20) January)
"Highly accurate sequenced-based antimicrobial peptide prediction using random forest" - 4th Macau Symposium on Biomedical Sciences 2017 “A new Ca atom based force-field for coarse-grained protein dynamics correlated well with experimental data” - International Conference on Bio-molecular Forms and Functions (ICBFF2012)“Protein dynamics and function correlation using a new knowledge based coarse grained force field” - Humboldt kollege on Interdisciplinary Science: Catalyst for Sustainable Progress, IISc, Bangalore 2014
Acknowledgment: Dr. Anirban Mukhopadhyay (My supervisor of B-Tech final year project) acknowledged me for small contribution at his book "Introduction to Computer graphics and Multimedia”
Volunteer: Humboldt kollege on Interdisciplinary Science: Catalyst for Sustainable Progress, IISc, Bangalore
DynFunc : Find functional important region from dynamics match.
CGMM : Coarse Grained Molecular Mechanics forcefield for protein dynamics
distrAMP (available soon): Sequence-based identification of Antimicrobial peptides
August 2007- March 2008; Associate System Engineer, IBM India Pvt Ltd, Kolkata, India
Room: E11-1048 (Computaional Biology and Bioinformatics Laboratory, Department of Computer and Information Science ) Faculty of Science and Technology
University of Macau, E11
Avenida da Universidade, Taipa,