BigLS - Big Data in Life Sciences

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ACM International Workshop on Big Data in Life Sciences

In conjunction with the ACM Conference on Bioinformatics, Computational Biology and Health Informatics

Sunday, October 2, 2016
Seattle, WA

Advance program posted!

Call for Papers

The ever-growing volume and diversity of biological and biomedical data collections continues to pose new challenges and increasing demands on computing and data management. The inherent complexity of this Big Data forces us to rethink how we collect, store, combine and analyze it.

BigLS is a workshop series dedicated to the broad theme of Big Data in life sciences. The goal of the workshop is to bring together leading researchers and practitioners working on a diverse range of Big Data problems relating to biology and medicine, and engage them in a discussion about current Big Data problems, the state of computational tools and analytics, the challenges and the future trends within life sciences.

The workshop focus is on, but is not limited to, the following broad themes:

Cross-topic papers focusing on techniques for heterogeneous medical data, translational research big data and P4 medicine are especially welcome!

In addition to regular papers catering to the above spectrum of topics, we also invite "position papers" to highlight some of the grand challenge scientific problems from a biological standpoint, existing or emerging, that require Big Data analytics, along with related challenges and advances.

The workshop is devoted to promoting the highest standards in research and education. As a part of this mission, BigLS features keynote thematic presentations by recognized leaders and luminaries who significantly advanced the domain. This year, the workshop will feature a keynote address by Nathan Price, Professor and Associate Director of the Institute for Systems Biology. The workshop hosts also an educational session where students can interact with established researchers and principal investigators.

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Keynote Address

The BigLS workshop is devoted to promoting the highest standards in research and education. As a part of this mission, BigLS features keynote presentations by recognized leaders and luminaries who significantly advanced the domain. This year, the keynote address will be delivered by Nathan Price - Professor and Associate Director of the Institute for Systems Biology (ISB) in Seattle, WA, co-founder of Arivale, Inc.

Actionable big data for proactive healthcare

Healthcare is becoming more proactive and data-rich than anything before possible – and will increasingly focus on maintaining and enhancing wellness more than just reacting to disease. Lee Hood and I have recently launched a large-scale 100K wellness project that integrates genomics, proteomics, metabolomics, microbiomes, clinical chemistries and wearable devices of the quantified self to monitor wellness and disease. The resulting dense, dynamic personal data clouds enable the creation of a field we term Scientific Wellness that aims to help individuals take informed actions to enhance their wellness and help reduce their risk for disease. Analyses of these data — individually and in aggregate — will enable us to identify scientifically-validated metrics for wellness, see early warning signs of disease, and develop approaches to reverse disease in its early stages (such as can currently be done for e.g. pre-diabetes). I will present results from our proof-of-concept pilot study in a set of 108 individuals (the Pioneer 100 study), showing how the interpretation of these data led to actionable findings for individuals to improve health and reduce risk drivers of disease — and well as give big picture views of how this endeavor relates to the future of health.

Dr. Nathan Price is Professor & Associate Director of the Institute for Systems Biology (ISB) in Seattle, WA. He is also Affiliate Faculty in the Departments of Bioengineering, Computer Science & Engineering, and Molecular & Cellular Biology at the University of Washington. He is Co-Founder and on the Board of Directors of Arivale, Inc. (“Your Scientific Path to Wellness”), which was recently named as Geekwire‘s 2016 “Startup of the Year.” Nathan has won numerous awards for his scientific work, including a Howard Temin Pathway to Independence Award from the National Institutes of Health, a National Science Foundation CAREER award, a young investigator award from the Roy J. Carver Charitable Trust, and he was named as one of the inaugural “Tomorrow’s PIs” by Genome Technology and as a Camille Dreyfus Teacher-Scholar. Dr. Price has published over 100 peer-reviewed scientific publications and serves on editorial boards for many leading scientific journals including Science Translational Medicine and Cell Systems. Dr. Price served on the National Academy of Medicine committee to review omics based tests to predict outcomes in clinical trials. Dr. Price also serves on advisory boards for a number of companies and institutes including the Novo Nordisk Foundation Center for Biosustainability, Trelys, Inc., Cleveland Clinic’s Center for Functional Medicine, the P4 Medicine Institute, the University of Washington’s Public Health Genomics Institute, the UW Multidisciplinary Learning Disability Center, and the DOE ENIGMA program at UC Berkeley/LBNL/MIT. He is also a fellow of the European Society of Preventive Medicine.

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Invited Talks

This year, the workshop will host three invited talks by leaders in life sciences and data analytics:

David Heckerman - Embracing big data in genomics: In the last decade, genomics has seen an explosion in the production of data due to the decreasing costs and processing times associated with DNA sequencing. I will discuss how the cloud as well as techniques from mathematics and computer science help take advantage of this big data.

David Heckerman is a Distinguished Scientist and Director of Microsoft Genomics at Microsoft. In his current scientific work, he is developing machine-learning and statistical approaches for biological and medical applications including genomics and HIV vaccine design. In his early work, he demonstrated the importance of probability theory in Artificial Intelligence, and developed methods to learn graphical models from data, including methods for causal discovery. At Microsoft, he has developed numerous applications including the junk-mail filters in Outlook, Exchange, and Hotmail, machine-learning tools in SQL Server and Commerce Server, handwriting recognition in the Tablet PC, text mining software in Sharepoint Portal Server, troubleshooters in Windows, and the Answer Wizard in Office. David received his Ph.D. (1990) and M.D. (1992) from Stanford University, and is an ACM and AAAI Fellow.

William Stafford Noble - Joint Imputation of Epigenomics Data By Three Dimensional Tensor Factorization: The ENCODE and Roadmap Epigenomics projects aim to assay many different DNA-associated proteins across many different cell types in order to map cell type-specific epigenomic features. The data produced define a three dimensional tensor with the axes being cell types, assays, and position along the genome. However, most of the data in this tensor is missing. We use a tensor factorization approach to impute the missing data and. The model also learns latent patterns in the data along each axis that provide insight into the way the genome functions in different cells.

William Stafford Noble (formerly William Noble Grundy) received the Ph.D. in computer science and cognitive science from UC San Diego in 1998. After a one-year postdoc with David Haussler at UC Santa Cruz, he became an Assistant Professor in the Department of Computer Science at Columbia University. In 2002, he joined the faculty of the Department of Genome Sciences at the University of Washington. His research group develops and applies statistical and machine learning techniques for modeling and understanding biological processes at the molecular level. Noble is the recipient of an NSF CAREER award and is a Sloan Research Fellow.

Adam Margolin - Inferring genomic predictors of cancer phenotypes: machine learning, crowd-sourcing, and big data.

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Travel grants

Thanks to the generous support from the NSF, the BigLS workshop will offer the travel grants for students and postdoctoral researchers from US academic institutions. These awards are independent from the main ACM BCB conference grants, and candidates can apply only for one of them. In order to apply candidates should submit before August 5, 2016 the following materials to Dr. Jaroslaw Zola <jzola@buffalo.edu> (priority will be given to females and under-represented minorities):

  1. A statement letter from the applicant, that includes i) a brief summary of research area and achievements, ii) explains how applicant will benefit from the BigLS workshop. Candidates should demonstrate interest in Big Data problems related to life sciences.
  2. A supporting letter from the applicant's supervisor/advisor, including confirmation that the student is in good academic standing, confirmation how the BigLS scope is relevant to his/her research, and how applicant will cover potential expenses not covered by the award (e.g. per diem).
  3. Title of a paper/poster accepted for presentation at BigLS (if any).

At the minimum the award is expected to cover the entire ACM BCB conference registration and hotel lodging (two nights for the duration of the workshop). Based on funding availability, additional support will be provided to cover parts or whole of the airfare and lodging expenses for the remaining duration of the conference. All questions regarding the BigLS travel awards should be directed to Dr. Jaroslaw Zola. To avoid miscommunication (e.g. email being flagged as spam) please do not hesitate to contact Dr. Zola again if you get no confirmation of your application within one day.

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Submission Guidelines

Submitted manuscripts should not exceed 10 pages in the ACM template on 8.5x11in paper. All submissions will be evaluated based on their originality, technical soundness, significance, presentation, and interest to the workshop attendees. All accepted papers of registered authors will be included in the ACM BCB proceedings published by the ACM Digital Library. Author resources can be found on the ACM BCB web page. To submit you paper please use this link: https://easychair.org/conferences/?conf=bigls2016.

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Important Dates

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Workshop Co-chairs

Program Committee

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BigLS Archive

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