Lydia Kavraki
William Marsh Rice University
http://www.kavrakilab.org/nsf-dbi-2033262.html
https://www.cov-irt.org
The pipeline developed in this project is expected to support multidisciplinary researchers interested in analyzing SARS-CoV-2 protein sequence regions and its conservancy along time. It will also provide researchers a way to build three-dimensional models of a peptide and a Human Leukocyte Antigen (HLA) of interest, allowing the investigation of molecular basis for cellular immune response. The pipeline will be provided as Jupyter notebook workflows. Our computational environment and the new integrated pipeline for peptide discovery will be made available to the research community as a Docker container, freely available for download from Docker Hub. The pipeline will be constructed based on Jupyter notebooks.
- Protein-protein binding: we are interested in new ways to evaluate and rank protein-protein scoring functions, especially when it involves small peptides (8-10 amino acids) and HLA receptors.
- We are open to collaborate with students and researchers interested in developing new tools towards COVID-19 drug- and vaccine-development.
- Seeking scientific expertise in language programming, machine learning, homology modeling, protein sequence alignment, and structural bioinformatics.
- Robotics
- Computational Biomedicine
- AI
- Algorithms
predictive analytics bioinformatics machine learning structural bioinformatics genetic variants HLA T-cell immunity immunology nucleocapsid (N) protein mutations