Web & Desktop Tools

Interactive applications for sequence analysis and molecular visualization

Stable

Boltz2-Notebook

Streamlined Colab-based pipeline for protein structure prediction and binding affinity analysis using Boltz2 deep learning model with interactive UI.

Cloud-Based AI-Powered
Python Jupyter Boltz2
Stable

UniDock GUI

User-friendly interface for GPU-accelerated Uni-Dock molecular docking. Simplifies high-throughput virtual screening with up to 2000x speedup.

GPU Accelerated High Performance
Python Uni-Dock CUDA
Stable

GRAVITy

A comprehensive automation pipeline for GROMACS molecular dynamics simulations. Streamlines the entire MD workflow from system setup to trajectory analysis with an integrated GUI, 3D visualization, and publication-quality analysis tools.

GPU Accelerated High Performance
Python FLASK GROMACS Shell Scripting
Production Ready

Genome Inspector Web

Interactive web-based DNA sequence analysis tool with transcription, translation, GC content analysis, melting temperature calculation, and reverse complement features.

Live Tool No Installation
HTML5 JavaScript Bootstrap
Production Ready

Genome Inspector Desktop

BioPython-based GUI desktop application for comprehensive DNA sequence analysis. Cross-platform support with advanced ORF finding and sequence validation.

Cross-Platform Offline Ready
Python BioPython Tkinter

Analysis Pipelines

Automated workflows for molecular dynamics and structural analysis

Stable

FELBuilder

Automated PCA + Free Energy Landscape analysis pipeline. Single-command execution from raw MD simulations to publication-quality 2D/3D FEL plots.

Auto-Analysis Publication Ready
Python GROMACS Matplotlib
In Development

More Tools Coming

New bioinformatics pipelines and analysis tools under active development. Stay tuned for advanced protein engineering and ML-based analysis tools.

In Progress Exciting

Open Source Contributions

Contributing to impactful research projects

Active

ThermoMPNN

Graph neural network for predicting protein stability changes from point mutations. Contributed code enhancements and bug fixes to the official repository.

Kuhlman Lab • UNC Chapel Hill
PyTorch GNN ML

How to Cite

If you use any of these tools in your research, please cite using the format below:

Tilewale, A. (2026). [Tool Name]. GitHub repository. https://github.com/AtharvaTilewale/[repo]

Need Help?

Found a bug, have a feature request, or need help using a tool?

Let's Collaborate

Building tools to advance research and make bioinformatics more accessible. I'm open to collaborations, feature requests, and innovative ideas.