The field of computational biology has undergone explosive in the last decade. To understand the computational challenges facing computational biology in the next 5-8 years, the PI proposes to run a special session at the next RECOMB2012 (http://recomb2012.crg.cat/) focused on emerging areas. RECOMB is an international scientific conference bridging the computational, mathematical and biological sciences, and is an excellent forum for disseminating the latest developments in computational biology.
The Sixteenth Annual International Conference on Research in Computational Molecular Biology (RECOMB 2012) was held in Barcelona, Spain on April 21-24, 2012. The conference consisted of five keynote talks (Ada Yonath, Eileen Furlong, Richard Durbin, Alfonso Valencia and Thomas Gingeras), 31 refereed papers, 6 contributed presentations corresponding to journal publications, and more than 130 poster presentations. Additionally, this grant funded a special session and a panel on 'Emerging Areas in Computational Biology.' The goal of this panel was to highlight emerging research problems and best practices for training the next generation of computational biologists. Five invited speakers gave short 20 minute talks, and a panel of 7 speakers discussed emerging areas in computational biology. The following areas were identified as being critically important in the next decade: (1) Algorithms for massive sequence datasets (2) Algorithms for personal and populationgenomics (3) Algorithms for analyzing functional genomics datasets (4) Methods for building personalized networks and understanding heterogeneity (5) Approaches for complex data integration (6) Moving from average to single-cell analyses approaches. Further, substantial discussion focused on education needs in computational biology. The panel suggested that the next generation of computational biologists need to be trained from the beginning of their undergraduate studies in computer science, statistics and biology. Overall, the panel felt that these students should not identify themselves as computer scientists, statisticians OR biologists, but instead as equally versatile on all three fields. There was a great discussion on depth versus breadth in educational training, and the importance of getting a deep knowledge of the computation and statistics. Further, the high-throughput nature of biology means that even experimentalists need to understand basic quantitative concepts (sample size, replicates, etc.) Overall, it was felt that significant further discussion was necessary on education and training.
