Computational approaches to data in the life sciences
Dr. Jochen Kumm gave a talk on “Computational approaches to data in the life sciences – bringing computation and analytics to the scientist” on Friday 15th July 2016 at the Mauritius Oceanography Institute in Albion.
Dr. Jochen Kumm, has been educated at Harvard University as well as Stanford University. He worked at the Universidad San Francisco de Quito, Ecuador, the Department of Statistics at the University of Washington and at the UW Genome Centre before joining Roche Pharmaceuticals heading Computational Biology and acting as global technology lead for genomics. He led biomathematics at the Stanford Genome Technology Centre for a decade, where he built collaborations with Harvard, MIT and the CDC in diagnostics, cancer sequencing and high-performance computing.
This talk explored the potential use of novel technologies and algorithms in data-rich life sciences. Dr Kumm examined practical considerations of what analytics can and should be. Specifically, he discussed adaptations of “big data” approaches to biological, oceanographic and geographically explicit data analysis. As petaflops of computational power become available in portable data centres, massively parallel computation, deep learning and analytical efficiency play an important role in the way we approach systems biology and its applications. Dr Kumm uses genomics problems, such as flu epidemiology, pathogen diagnostics and clinical decision support, as a reference point for evaluating the potential of artificial intelligence and machine learning in the life sciences – including opportunities for simplification and cost reduction of “applied computation” – namely prediction, classification and analysis in near-real time that is relevant and useable in the clinic/field.
Eminent Professor Rob Dunbar as well as Associate Prof. Kris Seetah from Stanford University also visited the MOI to discuss of avenues of research and collaboration between both institutes. They had a working session with the MOI staff, where ideas were exchanged in view of coming up with a collaborative project and thence a Memorandum of Understanding between Stanford University and MOI.