RECOMB/ISCB Conference on Regulatory and Systems Genomics, with DREAM Challenges
KEYNOTE SPEAKER ABSTRACTS & BIOGRAPHIES
updated Oct 27, 2013
DREAM Challenges
Trey Ideker
University of California, San Diego
United States
Turning Networks Into Ontologies: Towards A Data-driven Gene Ontology
Abstract: Ontologies have been very useful for capturing knowledge as a hierarchy of concepts and their interrelationships. In biology, a prime challenge has been to develop ontologies of gene function given only partial biological knowledge and inconsistency in how this knowledge is curated by experts. I will discuss how large networks of gene and protein interaction, as are being mapped systematically for many species, can be transformed to assemble an ontology with equivalent coverage and power to the manually-curated Gene Ontology (GO). Our network-extracted ontology contains 4,123 biological concepts and 5,766 relations, capturing the majority of known cellular components as well as many additional concepts, triggering subsequent updates to GO. Using genetic interaction profiling we provide further support for novel concepts related to protein trafficking, including a link between Nnf2 and YEL043W. This work enables a shift from using ontologies to evaluate data to using data to construct and evaluate ontologies.
Biography: Trey Ideker, Ph. D. is Professor of Medicine at the University of California at San Diego. He serves as Division Chief of Medical Genetics and Director of the National Resource for Network Biology, as well as being Adjunct Professor of Bioengineering and Computer Science and Member of the Moores UCSD Cancer Center. Ideker received Bachelor’s and Master’s degrees from MIT in Electrical Engineering and Computer Science and his Ph.D. from the University of Washington in Molecular Biology under the supervision of Dr. Leroy Hood. He is a pioneer in assembling genome-scale measurements to construct network models of cellular processes and disease. His recent research activities include assembly of networks governing the response to DNA damage; development of the Cytoscape and NetworkBLAST software packages for biological network visualization and cross-species network comparison; and methods for identifying network-based biomarkers in development and disease. Ideker serves on the Editorial Boards for Bioinformatics and PLoS Computational Biology, is on the Scientific Advisory Boards of the Sanford-Burnham Medical Research Institute and the Institute for Systems Biology, and is a regular consultant for companies such as Monsanto and Mendel Biotechnology. He was named one of the Top 10 Innovators of 2006 by Technology Review magazine and was the recipient of the 2009 Overton Prize from the International Society for Computational Biology. His work has been featured in news outlets such as The Scientist, the San Diego Union Tribune, Forbes magazine and the New York Times.
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Timothy R. Hughes
University of Toronto
Canada
DNA and RNA Binding Motifs for Mapping Gene Regulation
Abstract: A challenge to our understanding of genome function is lack of accurate and complete knowledge of the sequence preferences of DNA and RNA binding proteins. Current work in my laboratory is aimed at using in vitro assays to catalogue motifs on a genomic scale, thus separating the intrinsic activities of the proteins from confounding effects present in vivo. These data are invaluable in understanding how cells recognize genomic features, how gene regulatory networks are organized, and nucleic acid-binding proteins regulate healthy and disease states. I will highlight the contributions that the DREAM framework has made to this enterprise.
Biography: Timothy R. Hughes is a Professor at the Donnelly CCBR at the University of Toronto. He studied engineering and music at the University of Iowa, and received his Ph.D. in Cell and Molecular Biology from Baylor College of Medicine, working on telomere replication proteins with Vicki Lundblad. He did his postdoctoral work at Rosetta Inpharmatics (now Merck) working on microarray technology and its applications, including the development of ink-jet arrays now available from Agilent. Since moving to Toronto in 2001, Dr. Hughes has been the recipient of a Canada Research Chair in Genome Biology, the Ontario Premier’s Research Excellence Award, the Terry Fox Young Investigator award, and an HHMI foreign scholarship. He has authored or co-authored over 100 manuscripts, and is a scholar of the Canadian Institutes For Advanced Research. His laboratory has worked in gene regulation, systems biology, functional genomics, RNA processing, and genome sequencing.
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Systems Biology
Brenda Andrews
University of Toronto
Canada
From Phenotypes to Pathways: Global Exploration of Cellular Networks Using Yeast Functional Genomics
Abstract: The entire landscape of eukaryotic genetic research has been transformed by our ability to rapidly sequence genomes – while we can now map genomes efficiently, we do not yet know how to interpret genome variation to predict inherited phenotypes. Emerging evidence suggests that we must account for genetic interactions in order to relate genotype to important phenotypes in any eukaryotic system. To systematically explore genetic interactions, our group developed a unique functional genomics platform called ‘synthetic genetic array’ (SGA) analysis that automates yeast genetics and enables the systematic construction of double mutants. We developed two powerful pipelines which combine SGA and automated microscopy for systematic and quantitative cell biological screens or phenomics. Our first pipeline uses SGA to introduce fluorescent markers of key cellular compartments, along with sensitizing mutations, into yeast mutant collections. We then perform live cell imaging on the mutant arrays using HTP confocal microscopy to quantitatively assess the abundance and localization of our fluorescent reporters, providing cell biological readouts of specific pathways and cellular structures in response to thousands of genetic perturbations. Our second pipeline exploits the yeast GFP collection, a unique resource consisting of thousands of strains with different genes uniquely tagged with GFP. This remarkable collection has been arguably underutilized for systematic analysis of the proteome, largely due to the challenges associated with analysis of large sets of cell biological data. We addressed this challenge by adopting a high-content screening approach to measure protein abundance and localization changes in an automated fashion on a genome scale. Our general approach, in particular our network analysis and visualization methods, are readily extensible to other systems.
Biography: Brenda Andrews is Professor and Chair of the Banting & Best Department of Medical Research within the Faculty of Medicine at the University of Toronto, where she holds the Charles H Best Chair in Medical Research. She is also Director of the Terrence Donnelly Center for Cellular and Biomolecular Research (the Donnelly Centre), an interdisciplinary biomedical research institute with a focus on technology development for post-genome biology, functional genomics, systems & computational biology and bioengineering.
After receiving her PhD in Medical Biophysics from the University of Toronto, Dr. Andrews obtained her early training in genetics with the late Dr. Ira Herskowitz at the University of California San Francisco. In 1991, Dr. Andrews was recruited to the Department of Medical Genetics (now Molecular Genetics) at the University of Toronto. She became Chair of the Department in 1999, a position she held for 5 years before assuming her current positions. Dr. Andrews’ current research interests analysis of genetic interaction networks in budding yeast, using automated genetics platforms that include high content microscopy for systematic analysis of cell biological phenotypes. Specific interests in the Andrews lab include mechanisms of cell cycle control, control of cell function by kinases and other enzymes and the regulation of cell polarity and morphogenesis. Her research is currently funded by the CIHR, the National Institutes of Health, the Ontario Research Fund, the Canadian Foundation for Innovation and the Canadian Institute for Advanced Research (CIFAR).
Dr. Andrews is a Fellow of the Royal Society of Canada, Fellow of the American Association for the Advancement of Science, a Fellow of the American Academy of Microbiology and Director of the Genetic Networks Program of the CIFAR.
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Levi A. Garraway
Dana-Farber Cancer Institute and the Broad Institute
Boston, United States
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Peter Jackson
Stanford University School of Medicine
United States
Building Protein Networks to Understand Human Disease: Ciliopathies Explain Retinal Degeneration, Obesity, and Cancer
Abstract: Our ability to navigate the landscape of human disease is limited because the map of functional pathways connecting proteins to specific diseases is poorly drawn. The Jackson Laboratory uses high throughput mass spectrometry methods to identify disease-linked proteins and to construct dense protein interaction maps. These improved maps provide important biological insights, and identify new diagnostics and drug targets. The presentation will explain the technology and analysis methods and show new disease maps. To exemplify the methods, our discoveries of ciliopathies, newly identified neurological and kidney diseases with links to obesity, retinal degeneration, and cancer will be presented.
Biography: Dr. Peter Jackson is Professor in the Baxter Laboratory for Stem Cell Research at Stanford, and formerly Director and Staff Scientist at Genentech. His laboratory develops cancer drug targets and pioneered proteomic network building to identify diagnostics and targets in human disease. Their discovery of new disease genes and signaling pathways in the primary cilium, a rediscovered signaling organelle, helps explain neurological and kidney disease, obesity, retinal degeneration, and cancer.
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Galit Lahav
Harvard Medical School
Cambridge,
United States
Encoding Cellular Information through p53 Dynamics in Individual Cells
Abstract: Many signaling molecules exhibit complex dynamical behaviors, yet little is known how these dynamics affect cellular responses. In this talk I will focus on the dynamics of p53, a critical tumor-suppressive protein that controls genomic integrity and cell survival. I will present our recent work on p53 dynamics in individual cells and ask how these dynamics are shaped and affect cell fate decisions
Biography: Galit Lahav received her PhD in 2001 from the Department of Biology in the Technion, Israel Institute of Technology. In 2003, she completed her postdoctoral fellowship at the Weizmann Institute of Science in Israel. She then spent a year at Harvard’s Bauer Center for Genomics Research, and in the fall of 2004, joined the Department of Systems Biology at Harvard Medical School. Her research group combines experimental and computational approaches to understand how drugs act on different cell types and organs, and to gain insight into the reasons why different cells and people respond differently to specific drugs. Lahav is also a dedicated mentor to new faculty and highly committed to furthering the advancement of women in science.
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Tony Pawson and Modular Biology: From Domains to Cell Signalling Systems
by Dr. Jeff Wrana
Mt. Sinai Hospital
Toronto, Canada
The organizers of the RECOMB ISCB DREAM Conference were saddened to learn of the passing of Dr. Tony Pawson in August. Dr. Jeff Wrana will present a special tribute lecture at the 2013 conference where Dr. Pawson was to be a featured keynote speaker.
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Bernhard Palsson
University of California, San Diego
United States
Predictive Uses of Metabolic Reconstructions
Abstract: The prediction of cellular function from a genotype is a fundamental goal in biology. Constraint-based modelling methods systematize biochemical, genetic, and genomic knowledge into a mathematical framework enabling a mechanistic description of the genotype-phenotype relationship. The deployment of constraint-based approaches has evolved over roughly 30 years and recently, there has been a critical mass of studies combining them with high-throughput datasets and prospective experimentation. These studies have led to the validation of increasingly significant and relevant biological predictions. As reviewed herein, these recent successes have tangible implications in the fields of microbial evolution, interaction networks, genetic engineering, and drug discovery.
Biography: Bernhard Palsson is the Galletti Professor of Bioengineering and the Principal Investigator of the Systems Biology Research Group in the Department of Bioengineering at the University of California, San Diego. Dr. Palsson has co-authored more than 360 peer-reviewed research articles and has authored three textbooks, with one more in preparation. His research includes the development of methods to analyze metabolic dynamics (flux-balance analysis, and modal analysis), and the formulation of complete models of selected cells (the red blood cell, E. coli, hybridoma, and several human pathogens). He sits on the editorial broad of several leading peer-reviewed microbiology, bioengineering, and biotechnology journals. He previously held a faculty position at the University of Michigan for 11 years and was named the G.G. Brown Associate Professor at Michigan in 1989, a Fulbright fellow in 1995, and an Ib Henriksen Fellow in 1996. He is the author of 40 U.S. patents, the co-founder of several biotechnology companies, and holds several major biotechnology awards. He received his PhD in Chemical Engineering from the University of Wisconsin, Madison. Dr. Palsson is a member of the National Academy of Engineering and is a Fellow of both the AAAS and the AAM.
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Olivier Pourquié
Institut de Génétique et de Biologie Cellulaire et Moléculaire (IGBMC)
Université de Strasbourg, France
Title & Abstract: Check back for updates.
Biography: Olivier Pourquié, Ph.D. is currently Professor at Strasbourg University Medical School (France). He was the director of the Institute for Genetics and Molecular and Cellular Biology in Strasbourg from 2009 to 2012 and before he was a Howard Hughes Medical Institute Investigator at the Stowers Institute for Medical Research in Kansas City, USA. His lab provided the first evidence of the existence of a molecular oscillator -the segmentation clock- associated to the rhythmic production of vertebral precursors (the somites) in the embryo. This discovery was listed as one of 25 milestones in Developmental Biology in the 20th century by Nature magazine. The work from the Pourquié laboratory has imposed vertebrate segmentation as a novel paradigm to study spatiotemporal regulation of signaling in development. Together, his discoveries have had important consequences for our understanding of the patterning of the vertebrate embryonic axis and provided a conceptual framework to explain human spine malformations such as congenital scoliosis. Pr Pourquié is an elected EMBO and Academia Europea member and is the recipient of several prestigious awards including the Lounsbery Grand Prize of the French and American Academy of Sciences, the Allianz Grand Prize of the French Academy of Sciences and a European Research Council Advanced grant.
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Peter Sorger
Harvard Medical School
Cambridge, United States
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Regulatory Genomics
Ziv Bar-Joseph
Carnegie Mellon University
Pittsburgh
United States
Algorithms in Nature
Abstract: Computer science and biology have enjoyed a long and fruitful relationship for decades. Computational methods are widely used to analyze and integrate large biological data sets while several algorithms were inspired by the high-level design principles of biological systems. However, so far these two directions did not intersect and bio-inspired computational methods rarely led to new biological insights. With our increasing understanding of biological systems it is now possible to design bi-directional studies that will mutually benefit both fields. In this talk I will discuss the similarities and differences between the mechanisms and objectives of biological and computational systems. Relying on these similarities, I will present a few example where studying in detail how information processing is carried out in biological systems leads to both, efficient algorithms and better understanding of biology. These examples include fault tolerance in distributed regulatory networks, the selection of a Maximal Independent Set (MIS) during fly development and network design in the brain. In a number of these cases, the biological algorithms employs novel ideas that improve upon state of the art computational methods.
Biography: Ziv Bar-Joseph is an Associate Professor in the Lane Center for Computational Biology and the Machine Learning Department at the School of Computer Science at Carnegie Mellon University. His work focuses on the analysis and integration of static and temporal high throughput biological data for systems biology and on bi-directional studies linking information processing in biological and computational systems. Dr. Bar-Joseph has been the co-chair of the RECOMB meeting on Regulatory Networks and Systems Biology and is currently an associate editor for Bioinformatics. He received his Ph.D. from the MIT in 2003. He was the recipient of the DIMACS-Celera Genomics Graduate Student Award in Computational Molecular Biology, the NSF CAREER award and the 2012 Overton prize in computational biology.
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Emmanouil (Manolis) Dermitzakis
University of Geneva Medical School
Switzerland
From Genome Function to Personalised Omics
Abstract: Molecular phenotypes are important phenotypes that informs about genetic and environmental effects on cellular state. The elucidation of the genetics of gene expression and other cellular phenotypes are highly informative of the impact of genetic variants in the cell and the subsequent consequences in the organism. In this talk I will discuss recent advances in three key areas of the analysis of the genomics of gene expression and cellular phenotypes in human populations and multiple tissues and how this assists in the interpretation of regulatory networks and human disease variants. I will also discuss how the recent advances in next generation sequencing and functional genomics are bringing closer our hopes for personalized medicine.
Biography: Emmanouil Dermitzakis is currently a Louis-Jeantet Professor of Genetics in the Department of Genetic Medicine and Development of the University of Geneva Medical School. He is a member of the executive board of the Institute of Genetics and Genomics in Geneva (iGE3) and is also an affiliated Faculty member at the Biomedical Research Foundation of the Academy of Athens in Greece. His current research focuses on the genetic basis of cellular phenotypes and complex traits. He has authored and coauthored more than 100 papers in peer-reviewed journals and many of them in journals such as Nature, Science and Nature Genetics. His papers have been cited more than 20000 times and his H-index is 49. His research is supported by the Louis-Jeantet Foundation, the Wellcome Trust, the Swiss National Science Foundation, the European Commission, the Juvenile Diabetes Foundation and the US National Institutes of Health (NIH). He is also the recipient of a European Research Council (ERC) grant. He has been invited to give talks and keynote lectures in most of the prestigious genetics meeting and is the organizer of training courses including the Wellcome Trust HapMap course and founder and organizer of the Leena Peltonen School of Human Genomics. He is currently an analysis co-chair in the GTex project and has served as an analysis co-chair in the pilot phase of the ENCODE (ENCyclopedia Of Dna Elements) consortium and member of the analysis group of the Mouse Genome Sequencing Consortium and the International HapMap project. He had a leading analysis role in the HapMap3 project and is a member of the analysis group of the 1000 genomes project. He has served in the Board of Reviewing Editors of Science (2006-2011), and as a Senior Editor in PLoS Genetics (2006-2012) and is currently a member of the Board of Reviewing editors for the new scientific journal eLIFE. He is also in the advisory board of DNAnexus.
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Brenton R. Graveley
University of Connecticut Health Center
Farmington
United States
The Transcriptome of Drosophila Melanogaster
Abstract: We have generated RNA-seq, CAGE, and cDNA sequences from 30 developmental time points, 29 tissues, 21 environmental perturbations and 25 cell lines from Drosophila melanogaster. These data have substantially enhanced and improved the annotation of the D. melanogaster genome and lead to the discovery of >2,000 new genes including numerous non-coding transcripts. We also examined the extent and dynamics of alternative splicing and polyadenylation. For example, we identified hundreds of genes that utilize alternative polyadenylation to express long 3' UTR extensions in neural tissues and that the majority of sex-specific splicing is gonad-specific. In summary, the Drosophila transcriptome is substantially more complex than previously recognized and arises from tissue-specific, combinatorial usage of well-defined promoter elements, splice sites, and polyadenylation sites.
Biography: Brenton R. Graveley obtained hi B.A. manga cum laude in 1991 from the Department of Molecular, Cellular, and Developmental Biology at the University of Colorado, Boulder where he performed research with David M. Prescott. He conducted his Ph.D. Research under the guidance of Gregory M. Gilmartin in the Department of Microbiology and Molecular Genetics at the University of Vermont and graduated in 1996. He was a Jane Coffin Childs postdoctoral fellow from 1996-1999 with Tom Maniatis in the Department of Molecular and Cellular Biology at Harvard University. Since 1999, he has been a faculty member in the Department of Genetics and Developmental Biology at the University of Connecticut Health Center in Farmington, CT where he is currently a Professor. He is also Associate Director of the Institute for Systems Genomics at the University of Connecticut, a Member of the Board of Directors for the RNA Society, and an Editor of the journal RNA.
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Jason D. Lieb
Princeton University
United States
Reduce, Reuse, Recycle: The Dynamics of Regulatory Information Usage in Development
Abstract: Genomic technologies have opened a window into how regulatory information is encoded in DNA, and how access to that information is controlled. I’ll discuss these issues on at least one of three scales (1) How continual competition between nucleosomes and transcription factors may act as a clutch for transcriptional regulation; (2) How the nuclear envelope acts as an organizer for regulatory information; and (3) surprising re-use of the same subset of DNA regulatory elements to control the development of wings, legs, and halteres in Drosophila.
Biography: Jason Lieb is a Professor of Molecular Biology at the Lewis-Sigler Institute for Integrative Genomics at Princeton University. Prior to coming to Princeton, Lieb was the Beverley W. Long Chapin Distinguished Professor of Biology in the UNC College of Arts and Sciences, and the Director of the Carolina Center for Genome Sciences. Research projects in the Lieb lab are united by the scientific goal of understanding relationships between chromatin, transcription factor targeting, and gene expression. In particular, Lieb studies how information is encoded and dynamically utilized in living eukaryotic genomes, focusing on those areas of the genome that serve to regulate chromosomal functions, including transcription, DNA replication and repair, recombination, and chromosome segregation. Lieb came to UNC in 2002 after completing a postdoctoral fellowship at Stanford University. He earned his undergraduate degree in biology at the University of North Carolina at Chapel Hill and his PhD in genetics at the University of California at Berkeley.
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Aviv Regev
Broad Institute
Cambridge
United States
Reconstructing Regulatory Circuits: Lessons from Immune Cells
Abstract: Check back for updates.
Biography: Aviv Regev, a computational biologist, joined the Broad Institute as a core member and MIT as a faculty member in 2006. Regev’s research centers on understanding how complex molecular networks function and evolve in the face of genetic and environ¬mental changes, over time — scales ranging from minutes to millions of years. Prior to joining the Broad Institute, Regev was a fellow at the Bauer Center for Genomics Research at Harvard University, where she developed new approaches to the reconstruction of regulatory networks and modules from genomic data. Regev also worked for several years in the biotech industry in Israel, where she established and directed a bioinfor¬matics research and development team at QBI, a functional genomics company. Regev is also an associate professor in the Department of Biology at MIT and director of the Klarman Cell Observatory at the Broad. She was named an Early Career Scientist of the Howard Hughes Medical Institute in 2009. She is a recipient of the NIH Director’s Pioneer Award, a Sloan fellowship from the Sloan Foundation, and the Overton Prize from the International Society for Computational Biology. Regev received her M.Sc. from Tel Aviv University, studying biology, computer science, and mathematics in the Interdisciplinary Program for the Fostering of Excellence, where she did research in both theoretical biology (on the evolution of development) and experimental biology (on genomic instability). She received her Ph.D. in computational biology from Tel Aviv University.
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Jussi Taipale
Karolinska Institutet
Stockholm, Sweden
Genome-wide Analysis of Protein-DNA Interactions
Abstract: Understanding the information encoded in the human genome requires two genetic codes, the first code specifies how mRNA sequence is converted to protein sequence, and the second code determines where and when the mRNAs are expressed. Although the proteins that read the second, regulatory code – transcription factors (TFs) – have been largely identified, the code is poorly understood as it is not known which sequences TFs can bind in the genome. To understand the regulatory code, we have analyzed the occupancy of the majority of all expressed TFs in human colorectal cancer cells, and analyzed the sequence-specific binding of human, mouse and Drosophila TFs using high-throughput SELEX. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. Comparison of the human binding profiles with those of house mouse and Drosophila, revealed that the monomer binding specificity of TFs evolves very slowly, and has been almost completely fixed between vertebrates and invertebrates despite complete lack of regulatory element conservation. However, TF flanking sequences, and dimer spacing and orientation preferences appear to evolve much faster than monomer binding preferences, indicating that such changes are a potential source of evolutionary novelty. A binding model that is required to understand binding of TFs to the genome, which incorporates information about protein-protein interactions induced by DNA, and inheritance of epigenetic states across cell division will be discussed.
Biography: Professor Jussi Taipale earned his Ph.D. from the University of Helsinki in 1996. He initially continued his postdoctoral work at the University of Helsinki and later at Johns Hopkins University (Baltimore, MD, USA). Since 2003, he has headed an independent research laboratory focusing on systems biology of growth control and cancer. He has published 63 articles of which thirteen are in the most prestigious scientific journals (Nature, Science, Cell), won numerous awards and grants (e.g., Anders Jahre Prize for Young Researchers, EMBO Young Investigator, ERC Advanced Grant), and is internationally recognized as a leader in the field of genomics and systems biology. The Taipale group’s main expertise is on high-throughput screening using cDNA (Varjosalo et al. Cell 2008) and RNA interference (Björklund et al. Nature 2006), and computational and experimental methods to identify causative regulatory mutations in non-protein coding DNA and to analyze genetic networks (see Jolma et al., Cell 2013; Yan et al., Cell 2013). In addition, Taipale group has extensive expertise on mouse models of gene and regulatory region function (see Dumont et al., Science 1998; Ma et al., Cell 2002; Hallikas et al. Cell 2006; Sur et al., Science 2012).