Tim Hubbard

King’s College London, UK

Tim HubbardTim Hubbard is Director of Bioinformatics for King's Health Partners and Head of the Department of Medical & Molecular Genetics at King's College London. He is also Head of Bioinformatics at Genomics England, the company set up by the Department of Health to execute the UK 100,000 genomes project. He was formerly Head of Informatics at the Wellcome Trust Sanger Institute where he was one of the organisers of the sequencing of the human genome, co-founder of Ensembl and Sanger PI of the Genome Reference Consortium. He leads the GENCODE project that generates reference gene sets for human and mouse as part of the ENCODE consortium. Prior to working on genomes, he co-founded the SCOP database to organise protein 3D structures, and co-organised CASP (Critical Assessment of Structure Prediction), one of the first blind test competition frameworks to evaluate prediction methods in biology. He is actively involved in efforts to improve data sharing in science, develop open access publishing resources and plan for the adoption of genomic medicine. He is a member of the UK Expert Advisory Board on Data Access (EAGDA) and chair of the Advisory Board of Europe PubMedCentral. He was a member of the UK OSCHR e-health board which advised on the research use of electronic medical records, leading to the development of Clinical Practice Research Datalink (CPRD) and the creation of the Farr Institute, and working groups of the Human Genomic Strategy Group (HGSG), whose report led to the creation of the 100,000 genomes project.


Suzanna Lewis

Lawrence Berkeley National Laboratory, USA

Suzanna LewisSuzanna Lewis is a Staff Scientist in the Genomics Division at Lawrence Berkeley National Laboratory. Her current research interests are in understanding the interplay of genomic and environmental factors that give rise to individual phenotypes; in developing visual analytic tools for genomics; and in using evolutionary principles for cross-species inference of inherited traits, such as gene function. She earned dual degrees from the University of Michigan in Microbiology and in Information and Control Systems Engineering. Initially her career was in heavy industry, building real-time control robots in shipyards and factories. However in 1987, when congress made the decision to support sequencing of the human genome, she returned to the academic community to take advantage of this opportunity to return to biology. She is a member of the IEEE Standards Association, a Fellow of the American Association for the Advancement of Science, and was co-winner of the American Association for the Advancement of Science Newcomb Cleveland Prize for "The genome sequence of D. melanogaster” in 2000. In the course of her work on the D. melanogaster genome project she was instrumental in the design of the Chado database schema, producing the Apollo genome editor, and initiating the Generic Model Organism Database collaboration, and perhaps most significantly, the original impetus for the Gene Ontology and numerous related ontologies in use today throughout the research community. Biological research is built upon the ability of individual investigators to reliably locate and interpret data to extend their sphere of knowledge. This is turns is predicated on extensive content curation - the addition of connective metadata, corrections, and relational organization. It is through the efforts of curators that researchers are rapidly guided to the most informative and actionable data. Her recent work on the GO, MONARCH, and Apollo projects all focus on developing a community-standard semantic framework and interactive, Web-based tools to support biological content curation.


Patricia Babbitt

California Institute for Quantitative Biosciences (QB3), UCSF, USA

Patricia BabbittPatricia Babbitt, PhD is a Professor in the Department of Therapeutic Sciences (BTS) at the University of California San Francisco and Director of the UCSF Biological and Medical Informatics Graduate Program, a core program in the integrative Program in Quantitative Biology (iPQB), an umbrella graduate program training students with primary interests in Computational Biology/Bioinformatics, Biophysics, and Systems Biology for research at the interface of computational and experimental biology. She is a member of the California Institute for Quantitative Biosciences and holds a joint appointment in the Department of Pharmaceutical Chemistry. Dr. Babbitt’s research focuses on protein structure-function relationships in enzyme superfamilies, aiming to understand the “architectural principles” underlying how some protein scaffolds have evolved to enable many different molecular and biological functions. Recently, her group has begun to use graphical network models to summarize on a global scale structure-function relationships in very large enzyme superfamilies. Applications include functional inference, identification of misannotated proteins, and providing guidance for target selection for experimental and structural investigation. Associated with her work on functional annotation and misannotation in large public resources, she serves on the National Center for Biotechnology Information Board of Scientific Counselors and the UniProt Scientific Advisory Board. She also serves as a Deputy Editor of PLoS Computational Biology.


Lincoln Stein

Ontario Institute for Cancer Research, Canada

Lincoln SteinLincoln Stein, Director of the Informatics and Bio-computing Program at the Ontario Institute for Cancer Research is responsible for the management and analysis of large integrative cancer research projects including the International Cancer Genome Consortium and its Data Coordination Centre. His research focuses on using network and pathway-based analysis to identify common mechanisms in multiple cancer types and to devise prognostic and predictive signatures aiding in patient management. His group works on problems relating to the genome structure and function of the nematode Caenorhabditis elegans, a model organism that has yielded many insights into cancer.