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INTERNATIONAL CONFERENCE ON BIOINFORMATICS HongKong-Hanoi-Nansha
27 - 31 August 2007
Keynote Speakers - Hong Kong
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Professor Burkhard Rost (confirmed)
Department of Biochemistry and Molecular Biophysics
Columbia University
President, International Society for Computational Biology (ISCB)
HomePage: http://www.columbia.edu/~rost/
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Professor Minoru Kanehisa, (confirmed)
Director, Bioinformatics Center,
Institute for Chemical Research, Kyoto University, Japan
Human Genome Center, Institute of Medical Science, University of Tokyo, Japan
Website: http://kanehisa.kuicr.kyoto-u.ac.jp/
TOPIC: Genome to Life and Environment
Since the completion of the Human Genome Project, high-throughput
experimental projects have been initiated for uncovering genomic
information in an extended sense, including trascriptome and proteome
information, as well as metabolome, glycome, and other genome-encoded
information. Together with traditional genome sequencing for an increasing
number of organisms from bacteria to higher eukaryotes, we are beginning
to understand the genomic space of possible genes and proteins that make
up the biological system. In contrast, we have very limited knowledge
about the chemical space of possible chemical substances that exists as an
interface between the biological world and the natural world. Chemical
genomics is an emerging discipline for systematic analysis of the chemical
space. Experimentally, this is being achieved by high-throughput screening
of large-scale chemical compound libraries with various biological assays
at the molecular, cellular, and organism levels. In order to best utilize
the bioassay data being generated, bioinformatics methods have to be
developed to extract biological information encoded in the chemical
structures, and to understand the information in the context of molecular
interactions and reactions involving proteins and other biomolecules. This
would eventually lead to basic understanding of the chemical environment
that interacts with and drives evolution of the biological system.
KEGG (http://www.genome.jp/kegg/)
is a database of biological systems, integrating molecular building block
information (KEGG GENES and KEGG LIGAND) and higher-level functional
information (KEGG PATHWAY and KEGG BRITE). KEGG provides a reference
knowledge base for linking genome to life by the process of PATHWAY
mapping, which is to map, for example, a genomic or trascriptomic content
of genes to KEGG reference pathways to infer systemic behaviors of the
cell or the organism. In addition, KEGG now provides a reference knowledge
base for linking genome to environment, such as for the analysis of
drug-target relationships, by the process of BRITE mapping. KEGG BRITE is
a collection of hierarchically structured vocabularies representing
functional hierarchies of various biological objects, including molecules,
cells, organisms, diseases, and drugs, as well as relationships among
them. I will discuss bioinformatics methods that we have developed for
integrated analysis of genomic and chemical spaces. In particular, I will
show how KEGG can be used to understand the chemical repertoire of
endogenous molecules and also to extract reaction/interaction information
from the small molecular structures.
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Professor David Wishart, (confirmed)
Departments of Computing Science and Biological Sciences
University of Alberta, Edmonton, Alberta, Canada
Website: http://redpoll.pharmacy.ualberta.ca/
TOPIC:
How Bioinformatics Helped Reveal the Human Metabolome
ABSTRACT:
Metabolomics (or metabonomics as it is sometimes called) is a newly
emerging field of omics research concerned with the high-throughput
identification and quantification of the small molecule metabolites in the
metabolome. The metabolome can be defined as the complete collection of
all small molecule (<1500 Da) metabolites found in a specific cell, organ
or organism. It is a close counterpart to the genome, the transcriptome
and the proteome. While the technology to characterize the genome and the
proteome has only been available for the past 20 years, the technology to
characterize the metabolome has actually been around for much longer. In
fact, for the past 100 years chemists, biochemists and clinical chemists
have been "inadvertently" characterizing the human metabolome in their
quest to characterize metabolic disorders and to identify useful
biomarkers of disease. However, rather than depositing their results in a
coordinated way into electronic repositories, this metabolomic data has
been haphazardly appearing in journals, books and dissertations. As a
result, most of the information about the human metabolome was essentially
buried in dusty bookshelves.
In this presentation I will describe how we used a variety of custom
bioinformatics tools (text mining, screen scraping, prediction and machine
learning) in combination with "old-fashioned" library research to extract,
assemble and annotate the human metabolome from existing data resources.
With a first draft of the human metabolome now complete, we are now in the
process of using advanced experimental methods to confirm or validate this
draft data and to provide more complete metabolite annotations. We are
also developing a number of databases and software tools to support the
dissemination of information about the human metabolome and to facilitate
metabolomics research in general. I will describe some of these tools in
detail and provide examples of some of their applications to medical
research and systems biology.
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Professor Roderic Guigó, (confirmed)
Head, Bioinformatics and Genomics Program
Center for Genomic Regulation
Professor, Universitat Pompeu Fabra.
Barcelona, Spain.
Website: http://www1.imim.es/~rguigo/
TOPIC:
The complexity of the human genome transcriptional landscape
ABSTRACT:
Transcribed regions have been long been regarded as a distinguishing
characteristic of functional portions of the human genome. As part of the
Encyclopedia of DNA Elements (ENCODE) project, the sites of transcription
in the non-repeat sequences across a representative 1% of the human genome
has been determined in a large number of different cell line/tissue
samples using of high throughput transcription interrogation technique. In
addition, a detailed annotation of the protein coding content of the
ENCODE regions has been obtained through a combination of computational,
experimental and manual methods. Overall, at least 90% of the ENCODE
regions appear to transcribed as primary nuclear transcripts, and about
15% are present as mature processed polyadenylated transcripts.
Interestingly up to 30% of these sites of transcription have not been
previously identified.
In addition, using a combination of 5'Rapid Amplification of cDNA Ends
(RACEs) and high-density resolution tiling arrays, we have systematically
explored the transcriptional diversity of protein coding loci. RACE allows
detection of low copy number transcripts/isoforms and a high-resolution
analysis of genes individually, while pooling strategies and array
hybridization permit to reach high-throughput readout. We identified
previously unannotated and often tissue/cell line specific transcribed
fragments (RACEfrags), both 5' distal to the annotated 5' terminus and
internal to the annotated gene bounds for the vast majority (81.5%) of the
tested genes. Half of the distal RACEfrags span large segments of genomic
sequences away from the main portion of the coding transcript and often
overlap with the upstream-annotated gene. 5' most novel detected exons are
significantly associated to independently derived evidence of
transcription initiation. Notably, more than 50% of the novel transcripts
resulting from inclusion of novel exons have changes in th!
eir open reading frames. A significant fraction of distal RACEfrags show expression levels comparable to those of known exons of the same locus, suggesting that they are not part of very minority splice forms. These results might revise our current understanding of the architecture of protein-coding genes. They have significant implications for our views on locations of regulatory regions in the genome and for the interpretation of sequence polymorphisms mapping to regions hitherto considered to be "non-coding"
ultimately relating to the identification of disease-related sequence alterations.
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Professor Terry Speed (confirmed)
Head, Bioinformatics Division,
The Walter and Eliza Hall Institute of Medical Research,
Parkville Victoria 3050 Australia.
and
Department of Statistics and Program in Biostatistics
University of California at Berkeley
Berkeley, CA, USA
Email: terry --at-- wehi.edu.au; terry ++at++ stat.berkeley.edu
http://www.stat.berkeley.edu/~terry/
http://bioinf.wehi.edu.au/contacts/details_speed.html
TOPIC:
Estimating chromosomal copy number
Abstract:
Mutations in the human genome range from single base-pair
substitutions to changes in the numbers of whole chromosomes.
There are several contexts in which people are interested
in estimating chromosomal copy number from DNA samples.
In pre-natal diagnoses, testing for trisomy 21 (Down's syndrome)
is now commonplace, as is more general screening for chromosomal
abnormalities. In tumors, selective amplification and deletion of specific
chromosomal segments is frequent, with different types of cancer
being associated with different patterns of gain and loss. Determining
these patterns for particular tumors can be very relevant to the diagnosis,
prognosis and treatment of the cancer. Recently it has been shown that
there is a great deal of normal copy number variation in human populations,
and interest in the association of such variation with different human
diseases has increased.
Cytogeneticists have long had a variety of methods for detecting such changes,
including classic staining followed by microscopic visualization, fluorescence
in situ hybridization (FISH), and comparative genomic hybridization (CGH).
However, in the last few years much excitement has been generated in the
use of high-density microarray technologies for this purpose, with the
Affymetrix, Illumina and more recently NimbleGen platforms being
at the forefront.
As in all such endeavours, interest focusses on the accuracy and resolution
of these technologies, and this is inextricably linked to
the statistical/computational methods used to analyze the data
they give. In this talk I will give a general
introduction to the topic, a brief review of some analysis methods
currently used,
and finish by mentioning some challenges ahead.
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Keynote Speaker - Nansha
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Dr Emmanouil (Manolis) Dermitzakis (confirmed)
Population and Comparative Genomics
The Wellcome Trust Sanger Institute
Wellcome Trust Genome Campus
Hinxton, Cambridge, UK
TOPIC:
Causes of regulatory variation in the human genome
Abstract:
The recent comparative analysis of the human genome has revealed
a large fraction of functionally constrained non-coding DNA in
mammalian genomes. However, our understanding of the function of
non-coding DNA is very limited. In this talk I will present recent
analysis in my group and collaborators that aims at the identification
of functionally variable regulatory regions in the human genome by
correlating SNPs and copy number variants with gene expression data.
I will also be presenting some analysis on inference of trans
regulatory interactions and evolutionary consequences of gene
expression variation.
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Conference Organisers
Conference Invited Speakers
Tentative List below
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José R. Valverde, PhD MD MSci
Scientific Computing Service, CNB/CSIC
Campus Univ. Autonoma
Madrid, 28049. SPAIN
EMBnet, past, present and future | PPT/PDF |
(Final Abstract soon)
We have been working recently on EMBnet on testing and setting
up a number of advanced services and infrastructures and we are now looking
out to offer our collaboration to other groups and organizations to
share our expertise and knwoledge to build and extend cooperative projects.
Among these we would like to highlight at the conference:
- e-Learning initiative: we are trying to nucleate an e-learning
community willing to share knowledge, methods, materials and expertise
as well as to host introductory and advanced courses over the Net
- e-Science initiative: we have been participating from the
onset on a number of Grid initiatives like EMBRACE and EGEE, which already
have set out towards collaboration with asian partners, and believe it is
time now to start deploying a true production infrastructure for
Bioinformatics
- Bioinformatics standards: we have started working on designing
an open procedure that would give everybody the opportunity to
participate on an equal basis on the development and definition of standards for
Bioinformatics
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Yike Guo
Founder CEO, InforSense Ltd
Professor Imperial College London
Shanghai Bioinformatics Institute
Bioinformatics Workflow Integration | PPT/PDF |
Abstract
Bioinformatics research, database management, data mining and other
related activities are scaling up to levels which cannot be handled
efficiently with manual techniques. Many organizations handling database
curation and management are resorting to workflow integration. Many
workflow integration systems are now available for bioinformatics
applications. The experience of InforSense in delivering rapid workflow
integration solutions for researchers in academia and industry is
described. Use cases will be discussed along the concepts of workflow
integration.
About Speaker
Prof. Yike Guo founded InforSense in November 1999 to commercialize his group.s pioneering Open Discovery Workflow technology for high-performance large-scale integrative data analysis, rapid application building and process knowledge management. He has led the company.s growth since then. He is a world leading expert in large scale data mining and Grid computing and also serves as Technical Director of the Parallel Computing Center and Head of the Data Mining Group at Imperial College, University of London. Over the last four years he has led a number of significant academic and industrial research and development projects targeted at building next generation e-Science platforms for which he has gained UK and European funding in excess of £10million. He holds a PhD in Computing Science from Imperial College.
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Qiang Yang
Professor, Dept of Computer Science
Hong Kong University of Science and Technology
Data Mining for Bioinformatics: Some Challenging Problems | PPT/PDF |
Abstract
In this talk, I will give a selected overview of the intersection of data
mining for bioinformatics. I will list some challenges for both data
mining and its corresponding problems in bioinformatics, point out where
the challenges are, and survey some recent solutions. I hope to bring out
where the hot topics are in a few selected areas, such as dimensionality
reduction and feature selection.
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Tutorial Speakers
Tentative List below (To be finalised)
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José R. Valverde, PhD MD MSci
Scientific Computing Service, CNB/CSIC
Campus Univ. Autonoma
Madrid, 28049. SPAIN
EGEE Grid Computing in the Life Sciences using gLite | OpenDoc, PPT and PDF |
A course on Grid computing using gLite (the EGEE middleware)
with a short, half-day tutorial on-site integrated in an introductory
e-learning course. Hands-on tutorial with the
theoretical part imparted remotely through web-based e-learning
will also be provided. All examples will be using biological
and bioinformatics scenarios.
See http://edu.embnet.org/ for tutorial materials.
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Student Speakers
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Kang Sungsoo
KRIBB
Daejon, Korea
The Student Council of the International Society for Computational Biology ISCB-SC: Regional Student Groups | PDF |
This talk is open to all students and anyone interested in helping to form
Regional Student Groups in bioinformatics and computational biology in your
own country or region.
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