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JESMITA DHAR

@jesmitadhar

Post-doctoral fellow at JIS Institute of Advanced Studies and Research (JISIASR)

Kolkata

JIS Institute of Advanced Studies and Research (JISIASR)West Bengal University Of Technology

Dr. Jesmita Dhar is a highly experienced researcher with 9 years of expertise in bioinformatics and machine learning. Her technical proficiency spans predictive modeling, clustering techniques, and advanced machine learning algorithms such as Artificial Neural Networks and Gradient Boosting. She possesses deep expertise in bioinformatics, including molecular modeling, docking, and dynamics simulations, and is skilled in programming languages like R, Python, and Perl.

Experience

Post-doctoral fellow

JIS Institute of Advanced Studies and Research (JISIASR)

Research•Invalid Date - Present•Kolkata

Working on an ICMR project focused on the automated comprehensive characterization of antibiotic resistance genes using predictive modeling and Machine Learning algorithms. Developed an ANN-based computational model applied to the CARD database for class-specific feature extraction.

Project assistant

Bose Institute

Project•Invalid Date - Invalid Date•Kolkata

Worked on a DST project involving the study of protein structure and folding, protein-protein interactions, and high-throughput screening of small molecules. Expertise included molecular modelling, molecular dynamics simulation, and quantum mechanical calculations.

Education

Calcutta University / Bose Institute

Ph.D. in Bioinformatics

Bioinformatics

Jan 2013 - Jan 2020•Grade: Prof. B.B Biswas Outstanding Student Award (2018)

Thesis focused on the analysis of local structural motifs in protein structures and theoretical calculations to understand their stability.

West Bengal University Of Technology

M.Sc.(TECH) [Dual degree]

Bioinformatics

Jan 2011

Calcutta University

B.Sc.

Chemistry, Physics, Mathematics

Jan 2007

Skills

Predictive Modeling
Logistic Regression
Decision Tree
Random Forest
Bootstrapping
KNN
Clustering
K-means
Hierarchical Clustering
Artificial Neural Network
Gradient Boosting
SVM
Molecular Modeling
Molecular Docking
Molecular Dynamics
QM techniques
R
Python
Perl
MySQL
Numpy
Pandas
matplotlib
scikit-learn
keras
Linux
Ubuntu
Bioinformatics
BLAST
Pymol
GROMACS
Gaussian09
RCSB Protein Data Bank
Machine Learning