Student Travel Support: International Workshop on Big Data in Life Sciences, Atlanta, GA, September 9, 2015

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Big Data problems and challenges have become a reality in modern day computational biology and bioinformatics. The objective of this proposal is to request funds that will be used to support students and postdoctoral researchers from U.S. institutions to travel to the Association for Computing Machinery (ACM) International Workshop on Big Data in Life Sciences (BigLS), to be held on September 9, 2015 in Atlanta, GA, in conjunction with the 2015 ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB). This travel award will help orient students and postdoctoral researchers in the emerging area of Big Data analytics in life sciences. It will create a unique opportunity for supported students to present their on-going work, network with experts and peers in the field, receive mentoring, while contributing to the workshop's technical program. It will help to prepare the future generation scientific workforce to meet the challenges of this critical area of life sciences.Funds will be used to support up to 10 students and postdoctoral researchers, working in areas at the intersection of Big Data and life sciences. Recipients of the support will be selected via a widely advertised competitive process involving the submission of a travel grant application, and review by the workshop's organizational committee. Preference will be given to women and underrepresented minority groups, first-generation college students, and undergraduate researchers. The workshop will feature peer-reviewed papers and invited talks on five key research themes that underline Big Data research in life sciences: i) scalable algorithms and techniques for Big Data analytics in molecular biology, ii) statistical and integrative approaches to Big Data biology and informatics, iii) high performance computing methods and software for Big Data biology, iv) scientific workflows and platforms for Big Data in life sciences, v) software and hardware solutions for managing Big Data in biomedical informatics. This year's special emphasis theme is on scientific workflows for Big Data analytics, including workflows design, optimization, management and execution in HPC and cloud environments.