ABSTRACT

The cross-disciplinary science of computational biology has transformed into a robust subject of its own, emerging out of the shadows of its parent topics - computer science and biology. Currently, computational biology is an essential part of biology, biotechnology, health care and public health in both academic and industrial research and development institutions. However, training opportunities for the specialized workforce are often limited; the field of computational biology presents a challenge to many universities because of their departmental structures and disciplinary silos. In the rapidly evolving scientific world, the practice of sharing data among science practitioners is opening up new research avenues such as containing a pandemic using multidisciplinary approaches or the development of precision medicine for the future of health care. At the same time, the wealth of biological data is accumulating faster than the research community?s ability to analyze them. One bottleneck for analysis is a shortage of computational biologists. In order to fill some of the training gaps for U.S. graduate students, we will offer two Advanced Studies Institutes (ASI) with international experts from various disciplines of computational biology. The two proposed ASIs will train the students, the majority of whom will be from EPSCoR states with a special effort to recruit minorities and women, on diverse fundamental/theoretical aspects of computational biology as well as expose them to recent applications and developments in the field. In addition, to give the participants an opportunity to learn about various career possibilities in computational biology, an experienced team of academic faculties, core service providers, scientists with experience in relevant industries and individuals working on intellectual properties and start-up companies will be invited as instructors in these ASIs. The impact of the ASIs on scientific preparedness of student participants aligns well with NSF?s mission to promote the progress of science. Training the participants on different aspects of computational biology during the ASIs will contribute to the easing of the bottleneck and aligns well to NSF?s mission to advance the national health.

One of the key factors to success as a computational biologist is versatility and the ability to align oneself with the diverse demands of the field. Typically, students are trained in only one or very few aspects of computational biology relevant to their immediate research. It is rare that graduate students are exposed, in any meaningful way, to the breadth of fields that compose computational biology. The two proposed ASIs are different from traditional ASIs, which typically cover one specific subject matter in depth. Instead, the proposed ASIs will cover multiple cross-disciplinary topics in computational biology. Learning is a complex phenomenon, and the most effective training approaches combine a balance between lectures, promotion of discussions, interactivity and practical applications. These ASIs will combine all aspects of the aforementioned learning tools by implementing instruction methods comprising of lectures, hands-on activities and projects. These workshops will be held in an international setting, which provides both exposure to culture and as well as leaders in computational biology outside of the USA. The locations in Asia are important as non-American/European science and economy continues to grow rapidly in importance, especially within computational biology. The proposed ASIs will be hosted at the University of Perdana in Malaysia and the National Supercomputing Center in Singapore (NSCC) - two dominant biotechnology hubs of Asia. The participants will have the opportunity to build professional relationships with international students, faculties and industry leaders from Asia, USA and Europe. During the workshop, participants will be encouraged to participate in cultural experiences that will expose them to the history and culture of the host country. A website will be built for the ASI and will be used for recruitment, coordination and evaluation. A summary of the activities and their effectiveness in training participants, as judged by the participants, will be reported in a peer reviewed journal. Students will be primarily selected from EPSCoR states, with emphasis on recruiting from minorities (especially Native American) and women, with the aim of increasing participation of under-represented groups in computational biology.

This project is jointly funded by the Office of International Science and Engineering (OISE), and the Established Program to Stimulate Competitive Research (EPSCoR).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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