Current featured research
Can we predict human pathology in time and space from splicing and SNP information? We recently set out to answer this question using data integration and machine learning on published data. To our surprise it seems that human malady is predictable with accuracies reaching 80%. This is of course but the beginning and we are trying to see how far we can go with more sophisticated models and much more information...
In another recent collaborative effort we developed models that predict protein half-life and other protein parameters based largely on sequence data alone. Astoundingly we were able to predict fundamental biological processes within 90% of the measurements. Can we stop measuring and start predicting soon? We currently feed the models with large amounts of quantitative information and use deep learning to reach the boundaries of what is currently possible...
- 15th International Symposium on Bioinformatics Research and Applications (ISBRA)
Technical University of Catalonia, Barcelona, Spain
June 3 - 6, 2019
- ISMB/ECCB 2019
July 21 - July 25, 2019
We are constantly looking for talented people who would like to use computational approaches to understand disease. If you are a bioinformatician, a machine learning expert that is interested in biomedicine, a Biologist with a strong computational background, or just really interested in our research, please let us know and contact us.