Session chair:

 

Steven E. Brenner, Ph.D. – University of California, Berkeley, CA

Relevant to this session, Dr. Brenner was the 2010 ISCB Overton Prize recipient, and NIGMS has supported his research on alternative splicing, function prediction, and structure analysis.

 

Abstract:

 

Under a series of visionary leaders and program officers, the National Institute of General Medical Sciences (NIGMS) has supported groundbreaking science of profound impact for 50 years.  NIGMS is distinctive within NIH for the breadth of its mandate, with a mission to support research that

increases the understanding of life processes and lays the foundation for advances in disease diagnosis, treatment and prevention.   In particular, NIGMS has long taken a leading role in funding computational biology, in part because research in this field has an intrinsic breadth and diverse medical impacts.  This session celebrates the 50th anniversary of NIGMS and the 20th anniversary of ISMB with a selection of outstanding research from researchers supported by the NIGMS.

 

Presentations:

Speaker 1: Ed Marcotte

Title: Linking genes to traits (efficiently)

Speaker 2 : Katie Pollard
Title: When do mutations in mammal conserved noncoding sequences alter enhancer activity in vivo?

Speaker 3: Russ Altman
Title: Pharmacogenomics: using informatics to integrate molecular biology with clinical genomics

 

Speaker 4: Peter Lyster
Title: NIH Update on Biomedical Informatics and Computational Biology (BICB)

 

 

Session Speakers:

 

Russ Altman, M.D., Ph.D. – Stanford University, CA

Dr. Altman was named an ISCB Fellow in 2010, is a past President of ISCB (2000-2001), and served as a Co-Chair of the second ISMB in 1994. He runs the Helix Group at Stanford University, which creates computational tools that can be applied to solve problems in biology and medicine by using knowledge representation, database design, machine learning, natural language processing, physics-based simulation and graph-based modeling/analysis. As Principal Investigator of the NIGMS-funded PharmaGKB project, Dr. Altman focuses on the emerging field of personalized medicine by using individual genetics to optimize the selection and dosing of medications in order to advance the understanding of the genetics of drug response. In short, the Helix Group has constructed a pharmacogenomics database that integrates mutation information and knowledge about the impact of variation on drug metabolism. The group aims to build a tool that accepts a person’s genome as input, determines which drugs may or may not work, and recommends appropriate drugs and dosage levels for that person for their particular disease.

 

Edward Marcotte, Ph.D. – The University of Texas at Austin, TX

Dr. Marcotte’s research focuses on mining biological data for the large-scale organization of proteins to diagram the “wiring” of cells by learning how all of the proteins encoded by a genome are associated into functional pathways, systems, and networks. The emphasis of one of his NIGMS-funded projects, “Network-Directed Discovery of Disease Genes,” is to better define the functions of genes, thereby linking genes to traits and diseases, and in particular those genes underlying neural tube defects (NTDs), which are the second most common cause of human birth defects world-wide and the most common permanently disabling birth defect in the United States. At the other end of the scale, Dr. Marcotte is the PI on the NIGMS grant entitled, “Proteomics of Widespread, Reversible Protein Assemblies in Aging and Aggregation,” that investigates protein assemblies and their impact on aggregation-based diseases such as Alzheimer’s, Parkinson’s, and Huntington’s diseases, as well as aging itself, to determine if the assemblies are functional or catastrophic. From birth to old age, Dr. Marcotte’s research is focused on investigating genetic defects that might shed light on the path to new therapies that could improve the quality of life at all stages and ages.

 

Katie Pollard, Ph.D. – The University of California, San Francisco, CA

The Pollard Group develops statistical and computational methods for the analysis of massive genomic datasets. Under Dr. Pollard’s leadership the group investigates genome evolution, in particular identifying genome sequences that differ significantly between or within species and their relationship to biomedical traits of interest. Many of these sequences are non-coding, such as regulatory signals, structural sites, and RNA genes. The aim is to identify specific DNA alterations that are responsible for novel functionality, such as variation in gene expression. Dr. Pollard has been the PI on a multi-year NIGMS grant entitled, “What made us human?”

Peter Lyster, Ph.D. - National Institutes of Health (NIH) National Institute of General Medical Sciences (NIGMS)
As Program Director of the Division of Biomedical Technology, Bioinformatics, and Computational Biology at the NIH/NIGMS, Dr. Lyster has been directly involved in the role NIGMS has played in the past ten years in the cross-NIH Biomedical Information Science and Technology Initiative (BISTI). Among other activities, BISTI has maintained the Biomedical Informatics and Computational Biology (BICB) initiative, managed the Common Fund National Centers for Biomedical Computing, and offered a number of smaller announcements such as the Continued Development and Maintenance of Software, which are all itemized in the BISTI Funding Page. Dr. Lyster's talk will focus on BISTI activities, including summarizing the types and amounts of key awards noted in the recent editorial in the Biocomputational Review, and presenting updates on the inventory of BICB awards at NIH.

In this special session we will examine the social and technical underpinnings of successful efforts to harness community intelligence in bioinformatics.

 

‘Community intelligence’ efforts use the Web to enable volunteers to contribute to projects that would traditionally be accomplished solely by paid professionals. Successful products of such initiatives include Wikipedia, the Linux operating system, the Apache web server and the video collection on YouTube. The astounding scale and low cost of these and other successes has inspired many efforts to emulate these models in the life sciences. However, the majority of these efforts have largely failed because they have not managed to attract enough contributions from the community.

 

In this session, we will invite presentations from the leaders of community intelligence initiatives in bioinformatics that have succeeded in establishing a critical mass of contributors. Each of the four presentations will focus on one resource and will attempt to expose critical factors, such as incentives, interface design, outreach efforts, and community context, which have contributed to their success.

 

With increasing volumes of data and decreasing volumes of funding, many research groups in bioinformatics are now being asked to find ways to involve the larger (unpaid) research community in tasks related to the organization and dissemination of scientific information. This session will provide such groups with useful lessons that can be applied directly to their own initiatives.

 

Presenters:

 

Session 1: Alex Bateman, Wellcome Trust Sanger Institute, United Kingdom

URL: http://www.sanger.ac.uk/research/faculty/abateman/
Title: Assessing the contribution of scientists to Wikipedia for Pfam and Rfam annotation
Abstract: In this presentation I will show the latest survey of the scientific community's engagement with Wikipedia and its relevance to the annotation in Pfam and Rfam. Major challenges remain in: (1) educating experts in the field that Wikipedia contributions are a valuable communication tool; (2) giving non-technical scientists the confidence and knowledge of how to edit Wikipedia content.

Session 2: Alexander Pico, Gladstone Institutes, United States
URL: http://wikipathways.org
Title: WikiPathways and How to Change the World (or at least your small corner of the world)
Abstract: WikiPathways is a collaborative platform for collecting, curating and distributing biological pathway knowledge in the research community. We started WikiPathways with almost a decade of experience archiving pathway models as a conventional resource maintained by a small internal team of experts. Switching to a community curation approach has dramatically increased the size, quality and relevance of our content. Increased relevance is a particularly unique advantage of ‘community intelligence’ efforts that directly engage researchers in real-time. More and more, we are finding research communities eager to participate in data and knowledge repositories that utilize their contributions directly and transparently. Over the past 4 years, WikiPathways has grown from 100 registered users to over 2000, with a steadily increasing percentage making edits and contributing new content. The number of visits has doubled in the last year to over 10,000 per month. In this special session, we will present the lessons we have gleaned from launching and developing WikiPathways as a ‘community intelligence’ effort: how to set milestones for early success, how to utilize open source code and culture, how to tap into already established communities and resources, how to build data mining and analytical tools and services around your content, how to make use of new models of data sharing and publishing.

Session 3: Andrew Su, The Scripps Research Institute, La Jolla, United States
URL: http://sulab.org
Title: The Gene Wiki: Crowdsourcing the annotation of human gene function
Abstract: Comprehensively annotating the function of human genes is a formidable challenge for the biomedical research community. The goal of the Gene Wiki project is to create a continuously updated, community-reviewed and collaboratively-written review article for every human gene. The Gene Wiki currently takes the form of 10,000 articles in the online encyclopedia Wikipedia. This collection of articles is viewed over 50 million times and edited over 15,000 times per year. In this talk, we will describe our efforts to create a critical mass of users, to mine structured gene annotations from Gene Wiki text, and to integrate these data in bioinformatics analyses.

Session 4: Firas Khatib, University of Washington, United States
URL: http://fold.it/portal/info/science
Title: Distributed Community Intelligence through the Scientific Discovery Game Foldit
Abstract: Foldit is a graphical user interface representation of the Rosetta algorithm where players manipulate protein structures with the corresponding Rosetta energy shown in real time as their score. By leveraging human puzzle solving, pattern-recognition, and 3D spatial reasoning, humans are able to outperform many state of the art prediction methods. Foldit players have generated models accurate enough for successful molecular replacement and subsequent structure determination of a monomeric retroviral protease, despite not being given any experimental data. Foldit players have also been provided tools to encode their folding strategies, and within seven months one of these player-developed folding algorithms outperformed a previously published algorithm. Most recently, players were challenged to remodel the backbone of a computationally designed bimolecular Diels-Alderase to enable additional interactions with substrates. Several iterations of design and characterization generated a 24 residue helix-turn-helix motif, including a 13 residue insertion, that increased enzyme activity over 18-fold. X-ray crystallography showed that the large insertion adopts a helix-turn-helix structure positioned as in the Foldit model. The ability of an online gaming community to successfully guide large-scale protein structure prediction and design problems suggests that human creativity can extend down to molecular scale when given the appropriate tools.