Nano]°[Biostructures Research Group
Research Group Project Portfolio
Copyright 2025 by Flavio F. Contreras-Torres
Published by Tecnológico de Monterrey
Welcome. This site showcases the computational projects and tools developed by our group for data-driven molecular discovery in metabolic disorders.
Projects
- MOLRAPTOR — A pipeline for fetching, curating, and encoding molecular datasets into machine-learning-ready fingerprints.
- NPSCORER — An RDKit-based implementation of the P. Ertl (2008) algorithm to quantify the NP-likeness of chemical libraries.
- MOSAIC — A machine learning benchmarking toolkit for classification and model selection on tabular data.
- CHAMANP — A framework for curating and hierarchically organizing natural product molecular datasets.
Tutorials
- NumPy Tutorial — An introductory tutorial to NumPy covering linear algebra, testing, and debugging code in Python.
- AutoDock Tutorial — An introductory tutorial to AutoDock Vina covering the basics of molecular docking and result analysis.