Novel Computational Methods that Facilitate Development of Cyanofactories for Free Fatty Acid Production by Olaa Motwalli Olaa A. Motwalli, Ph.D., Computer Science Apr 9, 16:00 - 17:00 B3 L5 R5209 machine learning bioinformatics graph mining genomics Abstract Finding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of FFA production for it to be commercially viable. Thus, new chassis strains that require less engineering are needed
Novel Data Mining Methods for Virtual Screening of Biological Active Chemical Compounds by Othman Soufan Othman Soufan, Ph.D., Computer Science Nov 16, 14:00 - 15:00 H2 B9 machine learning data mining Computational biology biomedical applications Chemical compounds visualization Abstract Drug discovery is a process that takes many years and hundreds of millions of dollars to reveal a con dent conclusion about a specific treatment. Part of this sophisticated process is based on preliminary investigations to suggest a set of chemical compounds as candidate drugs for the treatment. Computational resources have been playing a significant role in this part through a step known as virtual screening. From a data mining perspective, the availability of rich data resources is key in training prediction models. Yet, the difficulties imposed by big expansion in data and its
