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Annual Report for DMS-1440386 for Year 2015-2016

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Annual Report for DMS-1440386 for Year 2015-2016 Annual Report for DMS-1440386 For Year 2015-2016 Introduction The Mathematical Biosciences Institute (MBI) is a multi-disciplinary initiative that facilitates interaction between the mathematical sciences (which includes mathematics, statistics, and computations) and the biosciences (which includes the biological sciences, medical sciences, and environmental sciences which relate to the living world). The Institute is devoted to the mathematical biosciences, which includes all areas of research in bioscience where participation of the mathematical sciences will lead to important progress. MBI offers a vigorous program of research and education, and fosters the growth of an international community of researchers in mathematical biology. MBI Mission Statement MBI offers a vigorous program of research and education, and fosters the growth of an international community of researchers in this new field. The mission of MBI is: • To foster innovation in the application of mathematical, statistical, and computational methods in the resolution of significant problems in the biosciences; • To foster the development of new areas in the mathematical sciences motivated by important questions in the biosciences; • To engage mathematical and biological scientists in these pursuits; and • To expand the community of scholars in mathematical biosciences through education, training, and support of students and researchers. To support this mission, MBI programs are designed to reinforce and build upon existing research efforts in the mathematical biosciences, and to inspire and accelerate the expansion of the community and its intellectual growth. These include emphasis year programs, current topic workshops, education programs, and research projects. The administrative and governance structure of the MBI are designed to support the mission of the Institute. MBI addressed the following scientific challenges in its programming during 2015-2016: Need to learn the scientist’s language: In order to contribute to the solution of problems in the biosciences, mathematicians and statisticians must first learn some science. In particular, they must learn the bio-scientist’s language before they can understand the problems clearly enough to bring the power of the mathematical sciences to bear. The continuing rapid pace of research in the biosciences precludes most active biomedical researchers from devoting substantial effort to learning additional mathematics. MBI is actively encouraging mathematical scientists to learn the bio-scientists’ language, and to work with them in highly interdisciplinary teams working the boundaries of mathematics and science. 1 Need to develop new mathematical/statistical models and techniques: While we can expect that established methods in mathematical science will be of immediate use, the quantitative analysis of fundamental problems in bioscience will undoubtedly require new ideas and new techniques. Similar observations apply to diverse research areas across the biosciences ranging from the study of basic structures in the brain to the expression, regulation, and control of genes. MBI is providing a forum for scientists to begin modeling these systems in ways which are scientifically relevant yet amenable to analysis which requires skillful approximations and new techniques. Need to increase the community’s size: The current size of the mathematical bioscience community is relatively small compared to the demands of bioscience. MBI encourages the participation of established mathematicians and statisticians in mathematical bioscience and is nurturing a new generation of researchers more systematically than before. MBI activities mostly fall under five categories (scientific programs, postdoctoral fellows, national impact, education, and diversity) and MBI is developing new programs in each of these categories: workshops, institute partners and mentoring, early career awards and long-term visitors, education programs, and diversity and outreach. MBI Vision Statement The vision of the Mathematical Biosciences Institute is: • To be a national center for the Mathematical Biology community; a place where all researchers with connections to mathematical biology seek to participate. • To be the premier center for postdoctoral training in mathematical biology. • To be the central hub that motivates and facilitates the mathematical sciences and the life sciences communities to create, share, and respond to research and educational opportunities MBI Diversity Statement The MBI diversity mission is to help shape the mathematical biology community in a way that represents the diversity of our society. Historically, women, African-Americans, Hispanics, Native American, and Alaskan Natives have been underrepresented in the mathematical biology community. MBI will work at two levels. First, it is MBI policy that each of its programs should actively seek diversity among its participants in gender and ethnicity. Second, MBI will sponsor activities that promote mathematical biology and its opportunities in the academic community. To be most effective, these activities should reach the undergraduate and pre-college levels, and contribute to increasing the diversity of future mathematical biologists. The Diversity Committee helps MBI to carry out this mission. Specifically, MBI will build and maintain diversity by the following: • Boards and Advisors: Ensure representation of underrepresented groups among the Directors, the Board of Trustees, the Scientific Advisory Committee, and the 2 Local Scientific Advisory Committee. • Science Workshops and Emphasis Programs: Include members of underrepresented groups as members of emphasis year and workshop organizing committees and ensure broad representation among workshop participants. • Training of Younger Scientists: Ensure broad representation among postdoctoral fellows and build exposure of younger scientists to mathematical biology. • Awareness Workshops: Periodically host workshops on Opportunities in Mathematical Biology for Underrepresented Groups The first of these workshops occurred in 2007. In addition, MBI will pursue the following strategies: • Participate in meetings of minority scientists, such as the Society for Advancement of Chicanos and Native Americans in Science (SACNAS) and the Historically Black Colleges and Universities Undergraduate Program (HBCU-UP), to provide information about MBI, recruit participants to MBI activities, and inform young scientists about opportunities in mathematical biology. • Build relations with academic institutions having strong minority enrollments. • Advertise MBI programs both broadly and to targeted audiences, including meetings of mathematical biology societies and minority-serving science societies. Evaluate the implementation of the MBI diversity plan annually. Summary of MBI Programs in Academic Year 2015-2016 MBI hosted two Emphasis Semester programs in 2015-2016: the Autumn 2015 Emphasis Semester was on Mathematical Molecular Biosciences and the Spring 2016 semester was on Dynamics of Biologically Inspired Networks. The Organizing Committee for the Autumn 2015 Semester consisted of Emil Alexov (Computational Biophysics and Bioinformatics, Clemson University), Ridgway Scott (Computer Science and Mathematics, University of Chicago), Reidun Twarock (Mathematics and Biology, University of York), and Guowei Wei (Mathematics, Michigan State University). This one-semester program brought together researchers from mathematics, chemistry, physics, biology, computer science, and engineering to explore new ways to bridge these diverse disciplines, and to facilitate the use of mathematics to solve open problems at the forefront of the molecular biosciences. With the availability of modern biotechnologies, an important trend in traditional life sciences disciplines (such as physiology, plant biology, neuroscience etc.) is a fundamental transition from macroscopic phenomenological disciplines to molecular based biosciences ones. In parallel with this development, a major change in the life sciences in the 21st century is the transformation to quantitative and predictive sciences. Revolutionary opportunities have emerged for mathematically driven advances in biological research. In the past few decades experimental exploration of self-organizing molecular biological systems (such as HIV viruses, molecular motors and proteins in 3 Alzheimer's disease) are examples of dominating driving forces in scientific discovery and innovation. However, the emergence of excessive complexity in self-organizing biological systems poses fundamental challenges to their quantitative description, because of the excessively high dimensionality and the complexity of the processes involved. Mathematical approaches that are able to efficiently reduce the number of degrees of freedom, and model complex biological systems, are becoming increasingly popular in molecular biosciences. Multiscale modeling, manifold extraction, dimensionality reduction and machine learning techniques have been introduced to reduce the complexity of biomolecular systems while maintaining an essential and adequate description of the biomolecules of interest. Currently, a major barrier for mathematical scientists to work in this field is the lack of knowledge in molecular biology, while a major barrier for biologists is the lack of knowledge about modern mathematical tools and techniques that have been developed in the past 20 years. This semester workshop program was designed to help bridge gaps
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