California

Pritam Kumar Panda

Elite
@pritampanda15

Bioinformatician @ Stanford | AI Research Scientist (LLMs, Deep Learning) for Protein Modeling & Drug Discovery | Open-Source Developer

PandaDock. PandaDock: Physics based Molecular Docking with GNN Scoring

98

PandaMap. Ligand-Protein Interaction Mapping

81

Molecular-Dynamics. Self explained tutorial for molecular dynamics simulation using gromacs

59

Siesta. FDF files for relaxation, PDOS and Denchar calculations in SIESTA 4.0.2 version as well as 4.1v and PSML supported version

29

ADMET-Prediction-System-Graph-Neural-Networks-with-RAG. A deep learning system that predicts Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties from molecular structures. The system combines Graph Neural Networks with a RAG-based LLM explainer to provide both predictions and mechanistic interpretations.

16

wxDragon. Automated DFT Input File Generator using wxDragon

15

PandaProt. A tool for mapping protein-protein, protein-nucleic acid, and antigen-antibody interactions

14

Omixium_YouTube_Channel. Tutorial Files

12

AtomicDockExplain. Post-docking atom-level energy attribution and explainable rescoring framework

10

Literature-Intelligence. Track, index, and analyze scientific papers from PubMed and bioRxiv for specific drug targets, compounds, or therapeutic areas.

9

Seqcore. High-performance biological sequence analysis library for Python. A unified, GPU-accelerated library for genomics, proteomics, structural biology, and drug design.

8

Bioinformatics-Scripts-R-Python. Bioinformatics Scripts in R and Python

7

Drug-Repurposing-Intelligence-System. An AI-powered system for discovering novel drug-disease relationships using Relational Graph Convolutional Networks (R-GCN) and Retrieval-Augmented Generation (RAG). This project integrates heterogeneous biomedical knowledge graphs with natural language processing to predict and explain potential drug repurposing candidates.

7

PandaMap-Color. PandaMap-Color: Protein-Ligand Interaction Mapper with customizable color schemes

5

pritampanda15. Profile stats

5

Grid-Box-Generator. This app helps you to generate or define grid box for Autodock Vina and Autodock4

4

PandaCite. A Python-based citation manager

4

Structify-Chemical-Structure-Converter. Structify is a lightweight and efficient tool for converting chemical structure file formats. Structify simplifies the process of converting between formats commonly used in computational chemistry and molecular docking workflows.

4

GROMACS-StepWizard. Calculate exact number of steps for your GROMACS molecular dynamics simulations .mdp files

3

Gromacs-Command-Finder. Gromacs Command Finder is a tool to search for gromacs specific comands like topology, trajectory analysis, PME, etc.

3

Drug-Designing. Drug Discovery Methods | Drug Designing Pipelines

3

Proteomics. Flow Cytometry analysis in R | Proteomics

3

Oncology-Drug-Response-Prediction-System_DL-RAG. This project implements a clinical decision support system that uses Deep Learning (DL) to predict cancer cell line response to various drugs and employs a Retrieval-Augmented Generation (RAG) pipeline to provide human-readable, context-specific explanations for the predictions.

3

Anthropic_codesignal_test. Anthropic Code Signal Test (90 minutes)

3

NGS-Workflows. Next-generation Sequencing workflows

2

PandaDock-GUI. Graphical Version of PandaDock

2

YouTube-Tutorials. Tutorials on bioinformatics, computational biology, molecular dynamics, and other specialized scientific tools and workflows.

2

ML-Genomics. Machine learning in Genomics

2

pdbprep. A comprehensive GUI application for preparing protein structures for molecular dynamics (MD) simulations with special focus on drug design applications.

2

single-cell-analysis-blueprint. NVIDIA

1

Optimus_Chemical_Analyzer. Optimus Chem - Comprehensive Chemical Analysis Package

1

ChemStudioPro. Swift

1

Visualization-Tools. Bioinformatics tools for schematics, data analytics and visualization

1

SSN-Sigil-Structured-Notation. A token-efficient notation format for LLM communication. Reduces token usage by 60-75% compared to JSON and NLP

1

AI-glossary. AI Concepts Glossary - Interactive Learning Platform

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