Machine Learning and Data Analytics for Protein Science
About
Molecular dynamics simulations of proteins have had a great impact on the understanding of biological function and pathogenic effects of mutations. The opportunity for faster simulation algorithms and GPU-parallelisation has boosted the ability to investigate proteins moving from single cases to large studies. Despite this, a great challenge remains in extracting meaningful data from larger terabyte-size trajectories. We have developed several methods to address these challenges using data analytics and machine learning.
Research papers
- Teletin, M., Czibula, G., Bocicor, M-I., Albert, S., Pandini, A. (2018) 'Deep Autoencoders for Additional Insight into Protein Dynamics'. Lecture Notes in Computer Science, 11140 pp. 79 - 89. ISSN: 0302-9743
- Tiberti, M., Pandini, A., Fraternali, F., Fornili, A. (2017) 'In silico identification of rescue sites by double force scanning'. Bioinformatics, Volume 34, Issue 2, pp. 207–214. ISSN: 1367-4803
- Chung, SS., Pandini, A., Annibale, A., Coolen, ACC., Thomas, NSB., Fraternali, F. (2015) 'Bridging topological and functional information in protein interaction networks by short loops profiling'. Scientific Reports volume 5, pp. 8540. ISSN: 2045-2322
- Fornili, A., Pandini, A., Lu, H-C., Fraternali, F. (2013) 'Specialized dynamical properties of promiscuous residues revealed by simulated conformational ensembles'. Journal of Chemical Theory and Computation, 9:11, pp. 5127 - 5147. ISSN: 1549-9618
- Pandini, A., Fornili, A., Fraternali, F., Kleinjung, J. (2012) 'Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics'. FASEB Journal, 26:2, pp. 868 - 881. ISSN: 0892-6638
- Fraccalvieri, D., Pandini, A., Stella, F., Bonati, L (2011) 'Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps'. BMC Bioinformatics, 12:158, 2011. ISSN: 1471-2105
- Pandini, A., Fornili, A., Kleinjung, J. (2010) 'Structural alphabets derived from attractors in conformational space'. BMC Bioinformatics, 11. ISSN: 1471-2105