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Keynotes - Invited Talks - Luncheon Session

Video Clips
  1. VideoDownload .flv (34 Mbytes) | Watch .flv APBioNet President: Shoba Ranganathan Opening Ceremony
  2. VideoDownload .flv (12 Mbytes) | Watch .flv IMMS President: Vladimir Brusic Opening Ceremony
  3. VideoDownload .flv (9 Mbytes) | Watch .flv InCoB CoChair: Christian Schonbach Opening Speech
  4. VideoDownload .flv (8 Mbytes) | Watch .flv CBI Chair: Akihiko Konagaya Opening Speech


Featured InCoB2010 Distinguished Speaker (Sep 26, 2010, 10:00-11:00 Keynote 1

Clyde A. Hutchison III Clyde A. Hutchison III

J. Craig Venter Institute (West Coast), San Diego, California, USA

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Biosketch: Hutchison graduated with a B.S. in Physics from Yale (1960). As an undergraduate, he worked on bacterial spore germination with Carl Woese, then a postdoctoral fellow in the lab of Harold Morowitz. His Ph.D. research, in the laboratory of Robert L. Sinsheimer at Cal Tech, concerned the genetics of bacteriophage phiX174.

In 1968 he joined the faculty of The University of North Carolina at Chapel Hill. There he collaborated with Marshall Edgell to analyze the DNA and the virion proteins of phiX174. They developed a marker-rescue assay for specific DNA fragments, which they used to associate phiX genes with specific restriction fragments. They also used restriction enzymes to analyze mammalian mitochondrial DNA, identifying restriction fragment length polymorphisms, and demonstrating maternal inheritance of mitochondrial DNA in mammals.
   Hutchison spent a sabbatical in Sanger's lab in Cambridge, England (1975-6). There he took part in sequencing the genome of phiX174, the first DNA molecule completely sequenced.
   Hutchison met Michael Smith in Sanger's lab. Upon Hutchison's return to Chapel Hill, they collaborated to develop the method of site-directed mutagenesis (1978).
   Hutchison continued his collaboration with Marshall Edgell to clone and sequence the beta-globin gene cluster in the mouse. They also discovered and characterized L1, the most abundant transposable element in the mammalian genome.

In 1990 he began work with Mycoplasma genitalium, the organism with the smallest known genome for an independently replicating cell. A survey of the genome by shotgun sequencing led to a collaboration with TIGR to sequence the entire genome (1995). On sabbatical at TIGR (1996-7) he worked to define the minimal set of genes required for cellular life by developing the method of global transposon mutagenesis.
   In 2003 he began to collaborate with Hamilton Smith, Craig Venter and others to work on the chemical synthesis of genomes. In July 2005 he joined the synthetic biology group at the J. Craig Venter Institute, where he is a Distinguished Professor. A major goal of the group has been to produce a "synthetic cell" programmed by a chemically synthesized minimal cellular genome.

Hutchison is a member of the National Academy of Sciences and a fellow of the American Academy of Arts and Sciences.
   He is presently located at the J. Craig Venter Institute - West in San Diego, California.

Title: Building a Synthetic Cell

Abstract: Using a computer analogy, one can think of a cell's cytoplasm as the hardware and the genome as the operating system. A synthetic cell is created by designing and synthesizing a genome and installing it into a recipient cytoplasm. Original components of the recipient cytoplasm are replaced in subsequent divisions and the synthetic cell takes on a phenotype determined by the synthetic genome.
    We chose Mycoplasma genitalium as our model for a synthetic cell. It is the smallest known bacterium that can grow independently in the laboratory. Its genome is 580kb in size with 485 protein coding genes and 43 RNA genes. Overlapping DNA cassettes were chemically synthesized to completely span the natural M. genitalium genome. These were assembled up to 1/4 genome size using an in vitro assembly reaction. Final assembly was accomplished using yeast recombination, and the complete genome was propagated as a yeast centromeric plasmid.
    To produce a synthetic cell, the synthetic genome must be introduced into a suitable cytoplasm where it can be expressed. To do this we developed methods for transplanting a natural genome from one mycoplasma species into recipient cells of a related, but easily distinguishable, species. Because of the slow growth of M. genitalium we developed transplantation using two more rapidly growing species: donor genomes isolated from M. mycoides are transplanted into M. capricolum recipient cells.
    Genomes prepared from donor mycoplasma cells under conditions that minimize mechanical shear are mixed with recipient cells, using a procedure optimized for transformation with plasmid DNA. Selection for a marker on the donor genome routinely yields several hundred transplant colonies per experiment. The resulting cells are genotypically and phenotypically identical to the donor strain. Controls in which donor genomes or recipient cells are omitted are consistently negative.
    To establish procedures for installing synthetic genomes propagated in yeast, we cloned the M. mycoides genome in yeast, and then successfully transplanted it back into M. capricolum. The power of yeast genetics can be applied to the mycoplasma genome during propagation in yeast. This opens a new approach to engineering bacterial genomes, and also a tool for synthetic genome installation.

(Comment by organizers: related to the topic is Science article Creation of a Bacterial Cell Controlled by a Chemically Synthesized Genome", originally published in Science Express on 20 May 2010.)

Featured InCoB2010 Distinguished Speaker (Sep 27, 2010, 11:45-12:45 Keynote 2)

Hiroaki Kitano Hiroaki Kitano

The Systems Biology Institute, Tokyo, Japan
Concurrent affiliation:
Okinawa Institute of Science and Technology, Onna-son, Japan

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Watch .flv Kitano Keynote

Biosketch: Hiroaki Kitano is a President of The Systems Biology Institute, Tokyo, a Principal Investigator at Okinawa Institute of Science and Technology, Okinawa, and a Director at Sony Computer Science Laboratories, Inc., Tokyo. He received a B.A. in physics from the International Christian University, Tokyo, and a Ph.D. in computer science from Kyoto University. Since 1988, he has been a visiting researcher at the Center for Machine Translation at Carnegie Mellon University. His research career includes a Project Director at Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation followed by a Project Director at Kitano Symbiotic Systems Project, ERATO-SORST, Japan Science and Technology Agency.
Understanding biological systems at the system-level has been his long standing research agenda. He has been working on systems biology since mid 90s. For systems-approach to be successful, one must integrate theory, computational infrastructure, and experiments in a coordinated manner. On the theory front, he has been trying to develop a "theory of biological robustness" which sheds lights on robustness and its trade-offs in biological systems. For computational infrastructure is concerned, his team, together with international collaborators, has been working on development and standard formation of SBML ( and SBGN ( as well as software complying with these standards: CellDesigner (
He is also a visiting professor of the University of Tokyo and of Keio University, a Manager of Division of Systems Biology, Cancer Institute, Japanese Foundation for Cancer Research, and a Founding President of The RoboCup Federation. Kitano received The Computers and Thought Award from the International Joint Conferences on Artificial Intelligence in 1993, Prix Ars Electronica 2000, Japan Design Culture Award 2001, Good Design Award 2001, and Nature's 2009 Japan Mid-career Award for Creative Mentoring in Science, as well as being an invited artist for Biennale di Venezia 2000 and Museum of Modern Art (MoMA) New York in 2001

Title: Systems Drug Discovery and Software Platform for Healthcare Research and Services

Abstract: Discovery of drugs and appropriate therapeutic interventions are complex enterprises. It is inherently complex as biological systems evolved to be complex in order to cope with broad range of perturbations and to maintain various functionalities. Multiple coordinated interventions are key for successful drugs to coming decades.
    However, designing multi-component multi-target drugs requires powerful computational approach to overcome its combinatorial explosion problems. it also requires principles that guides the discovery process. Nevertheless, lack of common platform hinders efficient development of tools that can potentially speed up drug discovery process. This talk outlines principles for systems drug discovery and efforts to develop unified and versatile software platform to enhance the process.

Featured InCoB2010 Distinguished Speaker (Sep 27, 2010, 16:45-17:45 Keynote 3)

Yoshiyuki Nagai Yoshiyuki Nagai

RIKEN Center of Research Network for Infectious Diseases (RIKEN CRNID), Tokyo, Japan

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Watch .flv Nagai Keynote

Biosketch: Yoshiyuki Nagai was born in Gifu Prefecture, Japan, in 1939. He graduated from the Faculty of Medicine at Nagoya University in 1965, started his research career in the field of virology at the graduate school of the same university and earned his Ph. D. in 1973. He made a research stay at the Institut fuer Virologie, Giessen, Germany from 1974 to 1976 as a Scholarship Investigator of Alexander von Humboldt Foundation. His academic career involves assignment to Professor of the Research Institute for Disease Mechanism and Control, Nagoya University in 1984, Professor of the Institute of Medical Science, the University of Tokyo in 1993 and Director of AIDS Research Center, National Institute of Infectious Diseases in 1998. He further served in the field of public health as Director at Toyama Institute of Health from 2001 to 2005 and returning to Tokyo in 2005, he is taking an active part in constructing Japan's Asian-African research network for infectious diseases as Director of the Center of Research Network for Infectious Diseases (CRNID), RIKEN. For his great deal of scientific contribution, especially to the understanding of molecular basis of paramyxovirus replication and pathogenicity, he was awarded Humboldt Research Award in 1990, Hideyo Noguchi Memorial Award for Medical Sciences in 1994, Chunichi Cultural Award in 1995, Takeda Prize for Medical Sciences in 2000, the Medal with Purple Ribbon in 2001 and the Japan Academy Prize in 2008. He received the titles of Professor Emeritus from Nagoya University and the University of Tokyo in 2000 and 2009, respectively. His administrative roles have also been greatly appreciated as exemplified by the assumption to President of the Japanese Society for Virology (2004-2005) and inauguration to Vice President of the International Union of Microbiological Societies (2008-present).

Title: Technology Innovation in Pathogen Identification in the Asian-African Research Network for Infectious Diseases

Yoshiyuki Nagai1, Kazuhisa Okada2, Yoshihide Hayashizaki3 and Toshihiro Horii4

1Center of Research Network for Infectious Diseases, RIKEN, 2Thailand-Japan Research Collaboration Center on Emerging and Re-emerging Infections, 3Omics Science Center, RIKEN, and 4Research Institute for Microbial Diseases, Osaka University

Abstract: While infectious diseases heed no national borders, there are borders in research on infectious diseases. In order to enhance collaboration across the borders, Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT) launched the Program of Founding Research Centers for Emerging and Reemerging Infectious Diseases as a five-year project (2005-2009). As of the end of FY 2009, 12 research centers were established on a bilateral collaboration basis in 8 countries (6 in Asia and 2 in Africa) by the participation of 8 universities and 2 institutions of Japan. They were connected to create the Asian-African Research Network for Infectious Diseases. This network is expected to remain active for at least another 5 years (2010-2014). The network's missions are to (1) enhance our understanding on infectious diseases of regional/global importance, (2) spur technological innovation in diagnosis, therapy and prophylaxis, and (3) foster human resources in the research field.

We will illustrate here the applications of state-of-the-art biotechnologies within our network, which include isothermal gene amplification by LAMP (loop-mediated amplification) and SmartAmp for rapid and accurate detection of pathogens on-site. We will also report our preliminary experiments with RAPID (robotics assisted pathogen identification) system that uses a high throughput sequencer and a strong database of pathogen genomes and will be useful to narrow down the candidate causative agents on a disease outbreak.


Luncheon Speaker (Sponsor: EpiVax, Inc.) Sep 28, 2010, 12:30-13:30, Conference Room 2

Anne S. De Groot

Update Sep. 23, 2010: Unfortunately, the speaker cannot be present. The presentation will be delivered by Leslie Cousens, Director of Protein Therapeutics, EpiVax, Inc.

Anne S. De Groot

EpiVax, Inc., Providence, RI, USA

Abstract as PDF

Title: Putting Immunoinformatics to Work to Develop Better Vaccines and Protein Therapeutics

Anne S. De Groot1,2,3, Leonard Moise1,2, Tobias Cohen1, Matthew Ardito1 and William Martin1

1EpiVax, 146 Clifford Street, Providence, RI 02903, USA, 2Institute for Immunology and Informatics, University of Rhode Island, Providence, RI 02903, USA, and 3Alpert Medical School, Brown University, Providence, RI 02903, USA

Abstract: The contributions of effector T cell epitopes to the immunogenicity of vaccines, protein therapeutics, and to autoimmunity are now broadly accepted. In the context of vaccine design, efforts are now devoted to increasing immunogenicity by selecting proteins based on T cell epitope content; and in the clinical development of protein therapeutics, efforts are now directed towards modulating the presence of T cell epitopes in protein therapeutics by screening and deimmunizing (removing T cell epitopes) prior to further development of the protein for clinical use. In allergy and autoimmunity, efforts are directed at identifying T cell epitopes for use in cell-mediated therapy of autoimmune and allergic responses. T cell epitopes are also emerging as key players in the induction of tolerance; discovery of natural regulatory T cell epitopes in the sequence of therapeutic monoclonals represents a paradigm shift for protein therapeutics, allergy, autoimmunity and transplantation.

For both vaccine and therapeutic design, we have developed a suite of computer algorithms; this suite includes EpiMatrix, ClustiMer, Conservatrix, BlastiMer, Aggregatrix, OptiMatrix, and VaccineCAD. Two very useful programs for vaccine and therapeutics are EpiMatrix and ClustiMer. EpiMatrix employs HLA class I and class II "pocket profiles" that describe HLA pocket binding coefficients, and applies these coefficients to the prediction of overlapping 9- and 10-mer peptide epitopes, while ClustiMer identifies T cell epitope "clusters" which range from 9 to roughly 25 amino acids in length and, considering their affinity to multiple alleles and across multiple frames, can contain anywhere from 4 to 40 binding motifs. Using these two programs, we have developed a system to score proteins based on their epitope content (both effector and regulatory) and use those scores to evaluate the immunogenicity of vaccines and protein therapeutics.

Enhanced use of T cell epitope mapping tools may improve our ability to identify T cell epitopes that can be useful for vaccine development (T effector epitopes) and for therapeutics (immunogenic and regulatory epitopes) and enable us to harness these important mediators of immune response. Effective integration of these epitopes into vaccines and removal of epitopes from therapeutics will facilitate development of improved immunotherapies for human health.


Featured InCoB-3rdBCII Invited Speaker (Sep. 28, 2010 13:45-14:40 Conference Room 2)

Nikolai Petrovsky Nikolai Petrovsky

Flinders Medical Centre, Bedford Park, SA, Australia,
Flinders University, School of Medicine, Adelaide, SA, Australia

Biosketch: Nikolai Petrovsky is Director of Endocrinology and Professor of Medicine at Flinders Medical Centre and Flinders University, respectively, and Secretary-General of the International Immunomics Society, of which he was a founder. He is also the Research Director of Vaxine Pty Ltd, a successful Australian biotech company funded by the US National Institutes of Health to develop novel biodefense vaccines. In July 2009, he pulled off the coup of leading the first group in the world to commence clinical trials of a novel adjuvanted recombinant swine flu (H1N1/2009) vaccine. For these achievements his team won the 2009 AMP Innovation Award at the Telstra Business Awards and the AusIndustry Innovation Award at the Australian Anthill magazine. In the last four years Prof. Petrovsky has taken four novel vaccines against seasonal influenza, pandemic influenza, hepatitis B and insect sting allergy from the laboratory to the clinic. In addition to being an inventor on a number of key vaccine patents he has authored over 90 scientific papers and book chapters in the area of immunomics, autoimmunity and vaccines.

Title: Challenges in Intelligent Vaccine Design; the Swine Flu Story

Abstract: The H1N1/2009 swine flu pandemic virus has so far fortunately turned out to be less lethal than originally foreseen. It has provided, however, a real-life opportunity to perform rigorous assessment of many recent claims of vaccine breakthroughs. In the end, few of these claimed breakthroughs in vaccine design and manufacture translated into useful vaccines, with the pandemic vaccines actually used almost exclusively utilising 50 year old egg-based influenza vaccine technology. So where were all the new and improved cutting-edge vaccines talked about before the pandemic? This talk will give an overview of where intelligent vaccine design is headed.
    Attempts will be made to explain why intelligent vaccine design failed to have a significant impact in the face of a real influenza pandemic. The key barriers that need to be overcome for smart new technologies in pandemic influenza vaccine design and manufacture to become a reality will also be discussed.

Featured InCoB-CBI Invited Speaker (Sep. 28, 2010, 9:35-10:30, Conference Room 1)

Dennis P. Wall Dennis P. Wall

Computational Biology Initiative Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA

Biosketch: Dr. Wall is Assistant Professor of Pediatrics and Director of the Computational Biology Initiative at Harvard Medical School, where his lab is developing novel approaches in systems biology to decipher the molecular pathology of autism spectrum disorder and related neurological disease. Dr. Wall received his doctorate in Integrative Biology from the University of California, Berkeley, where he pioneered the use of fast evolving gene sequences to trace population-scale diversification across islands. Then, with a postdoctoral fellowship award from the National Science Foundation, he went on to Stanford University to address broader questions in systems biology and computational genomics, work that resulted in comprehensive functional models for both protein mutation and protein interaction. Since joining the faculty at the Center for Biomedical Informatics at Harvard Medical School in 2006, he has been translating systems biology thinking to the field of autism research with the intent to develop effective early-stage diagnostics and targets for therapeutic intervention. Dr. Wall has acted as science advisor to several biotechnology and pharmaceutical companies, has developed cutting-edge approaches to cloud computing, and has received numerous awards, including an NSF postdoctoral fellowship, the Fred R. Cagle Award for Outstanding Achievement in Biology, the Vice Chancellor's Award for Research, three awards for excellence in teaching, and the Harvard Medical School Leadership award.

Title: False Positives in Personalized Genomics

Abstract: With the emergence of direct-to-consumer personalized genomics and the $1000 genome on the imminent horizon, the number of individuals undergoing genetic testing is accelerating. Concomitant with this rise is an increasing awareness that our methodologies and our current clinical knowledgebases may be inadequate to accurately measure risk of disease. Mutations that are marked in authoritative genetic databases as highly penetrant in causing disease congenitally or in early childhood are being discovered in asymptomatic, healthy adults. The number of these false positives findings is projected to rise dramatically because many of the current annotations for known mutations have not been developed for the asymptomatic, well population. In this talk, I will discuss our efforts to determine the frequency of false positives in present day genetic testing and their likely impact on the practice of personalized medicine. I will also discuss our work on clinical-grade annotation of human genetic variation, and related efforts in educating future doctors on the potential of genomics on individualized healthcare.

Featured InCoB-CBI Invited Speaker (Sep. 28, 2010, 13:45-14:40, Conference Room 1)

Chun-Hsi Huang Chun-Hsi Huang

University of Connecticut, Department of Computer Science and Engineering, Storrs, CT, USA

Biosketch:Chun-Hsi Huang is an Associate Professor at the Department of Computer Science and Engineering of the University of Connecticut in US. He received his BS, MS and PhD, all in Computer Science, from the National Chiao-Tung University in Taiwan, the University of Southern California in US and the State University of New York at Buffalo in US in 1989, 1994 and 2001, respectively. His current research areas include high-performance computing, cyber-infrastructure, life-science informatics, computational biology, algorithm design and analysis and experimental algorithmics.

Title: Peta-Scale Computing in Network Biology

Abstract: Many levels of the biological processes can be modeled by networks. Microscopically, such networks can be used to model gene regulation, signal transduction, protein interaction, and molecular metabolism. In the macroscopic setting, there are ecological and phylogenic networks as well. Distinct from each other with their own special characteristics, these networks, however, share common properties. The analysis of large-scale biological networks usually reduces to computation-heavy graph problems. In addition, recent advances in experimental methodology, particularly in genome sequencing and high-throughput technologies, have led to an unprecedented growth in network sizes. In this talk, we will discuss the use of efficient graph mining and partitioning techniques in the network analysis to identify structures or properties of biological significance. We will also discuss the deployment of modern distributed computing and information infrastructures in support of research work of this nature, namely research problems arising from life-science disciplines that are both computation- and data-intensive.

Featured InCoB-3rdBCII Invited Speaker (Day 3, 09:35-10:30 Conference Room 2)

Nebojsa Jojic Nebojsa Jojic

Microsoft Research, eScience Group, Redmond, WA, USA

Biosketch: Nebojsa Jojic received his PhD in electrical and computer engineering from the University of Illinois at Urbana-Champaign (UIUC) in 2001, where he was also the recipient of the Robert T. Chien Award for excellence in research in 2000, and the Microsoft Graduate Fellowship in 2000 and 2001. Since 2000, he has been with Microsoft Research, Redmond, where he has conducted research in the areas of signal processing, computer vision, machine learning, computational biology, and immunology/virology. Among more than 50 publications in these areas, several have been cited over 100 times. Dr. Jojic was one of the pioneers who introduced generative graphical models to the computer vision community, and introduced the models which jointly capture the appearance and image transformation in a way that reduces a variety of vision tasks, such as detection, recognition, segmentation and tracking to statistical inference. In machine learning, Nebojsa has innovated on variational inference techniques which allowed for tractable analysis of graphical models that more realistically capture evolutionary trees, and in his recent work, he is tackling a ubiquitous problem of large but sparse and heavy-tailed datasets encountered in a variety of sciences today. Dr. Jojic was also one of the thought leaders at Microsoft Research who helped steer the organization towards the decision to be more significantly involved in computational biology and in particular vaccine design and virology/immunology in general. His research typically crosses field boundaries when opportunities arise for cross-fertilization. For example, Dr. Jojic has recognized that some speech modeling techniques can benefit from the image deformation models used in computer vision if these are applied to audio spectrograms. He also saw analogies between the HIV vaccine design problem and the models of signal or image patches in signal processing on the one hand and on the other, the smallest superstring problem of the theoretical computer science.
Dr. Jojic has been awarded two awards for his research - one by his Alma Mater, University of Illinois, for an outstanding thesis, and another by a top computer vision conference, CVPR.
In addition to UIUC and Microsoft, Dr. Jojic was also briefly employed by the Hong Kong University of Science and Technology as a consultant in the area of computer vision and computer graphics, and has had an advisory role on the Genome Canada advisory board, where he is responsible for providing feedback on the ongoing research at the University of Toronto.

Title: HLA targeting of viruses

Abstract: Over the last couple of decades, a number of studies reported that the outcomes of viral infections often associate with patients' HLA types. It is likely that such associations would be even more frequently discovered, if it were not for the fact that HLA is one of the most diverse regions of the human genome. Molecules encoded in the HLA region present viral peptides on the cellular surface, allowing immune surveillance and clearing of the infected cells. Thousands of different HLA types have been catalogued to this day, and as a consequence, the appropriate association studies are statistically possible only for a small subset of those HLA types which are found frequently enough in the patient population. Many HLA binding properties, however, are shared across different HLA types, and new HLA binding estimation techniques can thus be used to more accurately characterize HLA differences among the patients. In particular, I will describe how HLA targeting of the peptides derived from viral proteins can be used to differentiate patients, as well as viruses (50+ genomes of DNA and RNA viruses), and predict viral load and immune pressure points in HIV infections. We have demonstrated that by combining machine learning techniques and applying them to database entries (both viral proteomes, and collections of HLA-binding peptides) we have enabled high- throughput screening in real-time, with potential applications in health policy, vaccine design an elsewhere in immunology.