Current and Future in Pathway Research
국제 워크숍 개최(e-Pathway)
� 행사명
○ Current and Future in Pathway Research
� 행사일시
○ 2012.07.06 (금) 9:00 AM ~ 6:00 PM
� 행사장소
○ KISTI 본원 대강당
� 행사내용
○ Pathway 연구 분야 전문가 초청 강연 및 연구 교류
� 행사필요성
○ IT-BT 분야 학제간 융합 연구 수행 및 성과 확산을 위한 글로벌
협력체제 구축
○ 전 세계적으로 활발하게 추진되고 있는 패스웨이 구축/생성/활용
연구의 국내 활성화 계기를 마련
○ 동 분야에 있어서의 국제적 연구개발 협력 네트워크 구축
� 행사 프로그램
Time
9:30-9:50
10:00-10:40
Title
Name & Affiliation
Opening
Won-Kyung Sung (KISTI)
Linking pathways to literature: PathText
Sophia Ananiadou (NaCTeM,
Manchester Univ.)
10:40-11:20
Information in New Drug Discovery research
Sung-eun Yoo
(Choongnam Univ.)
11:20-12:00
The MetaCyc Family of Pathway/Genome Databases
Ingrid Keseler (BioCyc, SRI)
and the Pathway Tools Software
12:00-13:30
Lunch
13:30-14:10
e-Pathway: A Platform for the Autonomous
Sung-Pil Choi (KISTI)
Generation and I ntegration of Biological Pathway
14:10-14:50
Kousaku Okubo (DBCLS)
14:50-15:30
Systems Metabolic Engineering
Sang Yup Lee (KAIST)
15:30-15:50
Coffee Break
15:50-16:30
KEGG: current status and its applications
Goto (KEGG, Kyoto Univ.)
16:30-17:10
Reactome – Linking pathways, networks and disease.
Robin Haw (Reactome)
17:10-17:30
Discussion & Closing
Won-Kyung Sung (KISTI)
초청 연사 소개 및 발표 주제
Systems Metabolic Engineering
Sang Yup Lee
Department of Chemical and Biomolecular Engineering
BioProcess Engineering Research Center and Bioinformatics Research Center
Center for Systems and Synthetic Biotechnology, Institute for the BioCentury
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon 305-701, Korea (leesy@kaist.ac.kr)
There has recently been much interest in developing sustainable system for the production of chemicals,
fuels, and materials from renewable resources. As microorganisms isolated from nature are often
inefficient in performing our desired tasks, metabolic engineering is employed for the improvement of
microbial performance. In this lecture, metabolic engineering based on quantitative pathway analysis will
be presented with accompanying examples of producing chemicals, fuels and materials. Focus will be
given on general strategies for systems metabolic engineering of microorganisms for successful
bioprocess development. [Our work has been supported by the Technology Development Program to
Solve Climate Changes from the Ministry of Education, Science and Technology.]
Sang Yup Lee
Sang Yup Lee received B.S. in Chem. E. from Seoul National University in 1986, and Ph.D. in Chem. E.
from Northwestern University in 1991. Currently, he is Distinguished Professor and Dean of College of
Life Science and Bioengineering at KAIST. He is also the Director of Center for Systems and Synthetic
Biotechnology, Director of BioProcess Engineering Research Center, and Director of Bioinformatics
Research Center. He has published more than 400 journal papers, and numerous patents. He received
many awards, including the National Order of Merit, Citation Classic Award, Elmer Gaden Award, and
Merck Metabolic Engineering Award. He is currently Fellow of AAAS, American Academy of
Microbiology, Society for Industrial Microbiology and Biotechnology, Korean Academy of Science and
Technology, and National Academy of Engineering of Korea. He is also Foreign Associate of National
Academy of Engineering USA, Editor-in-Chief of Biotechnology Journal, and editor and board member
of many journals. His research interests are metabolic engineering, systems and synthetic biology, and
industrial biotechnology.
Reactome – Linking pathways, networks and disease.
Robin Haw
Ontario Institute
for
Cancer
Research,
Informatics
and
Bio‐Computing, Toronto, ON, Canada
The Reactome Knowledgebase of human biological pathways and processes is
a curated and peer-reviewed knowledgebase available online as an open access
resource that can be freely used and distributed by all members of the
biological research community. Geneticists, genomics and proteomics
researchers, clinicians, molecular biologists, bioinformaticians and systems biologists use Reactome to
interpret high-throughput experimental datasets, to develop novel algorithms for data mining and
visualization, and to build predictive models of normal and abnormal pathways. The Reactome curation
system draws upon the expertise of independent researchers who author precise machine-readable
descriptions of human pathways under the guidance of a team of curators. Pathway modules are
extensively checked to ensure factual accuracy and compliance with the data model, and a system of
evidence tracking ensures that all assertions are backed by the primary literature. Recent extensions of our
data model accommodate the annotation of disease processes, allowing us to represent the altered
biological behavior of mutant variants frequently found in cancer, and to describe the mode of action and
specificity of anti-cancer therapeutics. Reactome pathways currently cover a quarter of the translated
portion of the genome, and are available on our web site for browsing, downloading, and manipulation by
in-house and third party online analysis tools. To increase protein coverage and associated annotations,
we have extended our protein coverage by offering a network of “functional interactions” (FIs) predicted
by a conservative machine-learning approach, that add an additional 25% of the translated genome, for a
combined coverage of approximately 50%. We offer several analytical tools built upon the Reactome FI
network and have begun to demonstrate the network’s usefulness for the analysis of genome-scale
datasets in human disease research.
Database URL: http://www.reactome.org
Contact email: robin.haw@oicr.on.ca
Information in New Drug Discovery research
Sung-eun Yoo
Department of New Drug Discovery
Graduate School of Drug discovery & Development
Chungnam National University
Drug discovery is the process by which drugs are discovered or designed.
At the beginning of early modern drug discovery era, numerous drugs have been
discovered from traditional natural products or by serendipitous way. However over the
years as our understanding of diseases has increased at the molecular and
pathophysiological level, we now attempt to design the molecules in a logical way
based on these informations.
This logical process of drug discovery demands joint efforts between numerous
scientific and technological disciplines classified generally as chemistry and biology. In
order the new drug discovery process to be effective, communication and exchange of
experimental information between these scientific disciplines become critical and
crucial.
In this talk, I will describe the general process of new drug discovery and emphasize the
importance of exchanging informations between various scientific disciplines and
particularly how the information from one discipline is translated into the other
disciplines.
KEGG: current status and its applications
Susumu Goto
Starting from 1995 with four core databases,
PATHWAY, GENES, ENZYME and COMPOUND,
KEGG has now 17 databases classified into three
categories:
Systems
information,
Genomic
information and Chemical information. Despite the
main objective of the KEGG system is to connect
the genomic and chemical information through the
systems information such as PATHWAY, BRITE, MODULE, the targets of KEGG are
expanding to new research fields and general public including medical information for
diseases and drugs. We also have to adopt to the new technologies. Recently
metagenomics data from next generation sequencers have been accumulated and we
have included some of the data in KEGG for the interpretation of the human gut
microbiomes.
Although manual curation is still a basis for the creation of reference pathways,
modules, and functional hierarchies, many automatic processes have been incorporated
into the functional annotation for complete genomes and metagenomes due to the
exponential growth of genome sequences. In addition, tools for annotating genomes,
predicting new pathways, and predicting genes for missing enzymes and functions have
been developed as an application of KEGG and available on the web.
The MetaCyc Family of Pathway/Genome Databases and the Pathway
Tools Software
Ingrid Keseler
Senior Scientific Database Curator (EcoCyc) and Principal
Investigator, BsubCyc project
Comprehensive knowledge of metabolic pathways is required
in a variety of biomedical and biotechnology applications. The
MetaCyc family of Pathway/Genome Databases (PGDBs) describes
the genomes and metabolic pathways of more than 1,700 organisms
with sequenced genomes. These databases share a common schema and ontologies, facilitating
interoperation and comparative analysis. Many are highly curated, including PGDBs for E. coli, yeast,
mouse, and Arabidopsis.
PGDBs in the MetaCyc family were derived computationally from
MetaCyc. MetaCyc now contains more than 1,800 experimentally elucidated metabolic pathways found
in more than 2,300 organisms. The MetaCyc data were curated from 35,000 publications.
Pathway Tools, the software used to build, update and publish the MetaCyc family of PGDBs,
contains a large suite of algorithms for manipulating biological networks and genome data.
In particular,
it includes inference modules for inferring the metabolic pathways of an organism, and for predicting
genes encoding enzymes that might fill missing reactions in the predicted pathways. Recent additions to
Pathway Tools include (a) the ability to generate steady-state metabolic flux models from PGDBs that
enable prediction of the essential genes of an organism, and of its growth under different nutrient
conditions; (b) a fast, accurate algorithm for prediction of reaction atom mappings; (c) tools for storage
and analysis of organism growth data within PGDBs, such as Phenotype Microarray data.
Linking pathways to literature: PathText
Sophia Ananiadou
full professor in Computer Science, School of Computer Science,
University of Manchester and Director of the National Centre for
Text Mining.
PathText is a text mining based system linking models encoded in
SBML with evidence from literature. The strengths of PathText
include advanced search based on NaCTeM's text mining services,
Facta+, KLEIO, MEDIE. These services include event extraction tools (EventMine), faceted search based
on named entity recognition, disambiguation components and normalisation. In addition, our one-stop
collaborative text processing workflow platform (Argo) includes annotation tools that facilitate curation
of pathways. Issues on efficient querying and ranking from models will be addressed.