Integrated Open Systems Unit (Hiroaki Kitano)
Professor (Adjunct) Hiroaki Kitano
kitano at oist.jp
Paper by Dr. Hiroaki Kitano published in Molecular Systems Biology
This project aims at development of novel software platform and computational forms of biological knowledge (models and active knowledge-bases) of budding yeast, cancer cells, and developmental/reprogramming pathways, which takes full advantage of recent advantages in information science. The software platform developed will be a next generation information infrastructure for biological science, enabling development of self-sustainable, scalable, and coherent biological models and knowledge sources. “Self-sustainable” means that the system (software and its operation) can be enriched by continuous participations of users, contributors, and business entities. “Scalable” means that the system can grow to describe and execute very large models, such as whole cell models or whole human models, in the future without substantial change of its basic architecture and mode of operation. “Coherent” means a group of software functions in a consistent manner using defined standards and protocols.
Such platform shall be able to aggregate, integrate, and execute biological knowledge. It shall be noted that “execution” means that, at some point in the future, dynamical simulation of biological system can be attained through a body of knowledge encoded in the computational platform. Any change in knowledge can be automatically reflected to simulation. Progress of computational platform toward this goal shall benefit basic biological research as well as industrial use of biological knowledge by pharmaceutical companies and biotech companies.
Despite remarkable progress in computational and information science, software platforms in biological science have not been well established so far, particularly due to lack of standardization and weakness of software platform for utilizing available data and knowledge in a consistent and coherent manner. This problem has been significantly improved in the past years partly due to our efforts for standard formation and development of de facto industrial quality software development. Nevertheless, how such efforts bring benefits to a broader scientific and medical audience is yet to be confirmed. With an overwhelming accumulation of knowledge on specific protein-protein and gene regulatory interactions and a huge volume of public biological data, there is an unprecedented opportunity today that we may actually be able to create a platform and actual service that embraces comprehensive body of knowledge on biological systems. It is practically feasible that comprehensive body of knowledge in a computational form (knowledge base and model of molecular/gene interaction network) to be developed to biological systems by intense study and industrial needs.
Software Platform Development
Software platform development aims at the development of a novel and comprehensive computational platform that consists of (A) SBML (Systems Biology Markup Language) and SBGN (Systems Biology Graphical Notation) model description standard, (B) CellDesigner (CD) and its plug-in analysis tools and Payao , which are platforms for aggregating, editing, analyzing, and sharing biological models, (C) a new on-the-fly simulation platform as well as system analysis tools, and (D) a novel intelligent inference system that designs experiments to fill an information gaps to complete the model, and (E) the integration of an advanced text-mining system developed by collaborators, such as the University of Tokyo and the University of Manchester (NaCTeM), which allows users to quickly search and update publications and specific data on interactions of interest.
This system will gradually transform into a scalable dynamical simulation system that can reflect changes in each component and modular models on-the-fly, thereby enabling continuous upgrading of model precision. This requires a modular and hierarchical modeling system with a rigid mathematical and computational basis.
Biological Model Development
Modeling efforts are expected to validate efficacy of the software platform developed and to be used for further research. The budding yeast model and a part of the cancer cell model will be developed as collective efforts of the community as well as an automated integration of public knowledge and data. Open Yeast Initiative (Open Source Whole Yeast Modeling) may be the central effort of the Open Biology Unit for now.
“Open Yeast Initiative” aims to create a draft whole cell computational model of budding yeast within the next three years followed by successive improvements. “Open Yeast Initiative” that enables a whole yeast and systems biology community to get involved in collectively creating and refining the yeast model. Payao, an open-flow system, and a series of novel simulation software shall enable this unprecedented project. The Open Biology Unit of OIST, in collaboration with the System Biology Institute (SBI) will provide an initial seed map for large-scale molecular interaction of key yeast biological processes, and will be the seed to foster community annotation and improvement. The project shall move toward the integration of biological knowledge and dynamical simulation.
Hase T, Tanaka H, Suzuki Y, Nakagawa S, Kitano H, 2009 Structure of Protein Interaction Networks and Their Implications on Drug Design. PLoS Comput Biol 5(10): e1000550. [doi:10.1371/journal.pcbi.1000550]
Nicolas Le Novère, Michael Hucka, Huaiyu Mi, Stuart Moodie, Falk Schreiber, Anatoly Sorokin, Emek Demir, Katja Wegner, Mirit I Aladjem, Sarala M Wimalaratne, Frank T Bergman, Ralph Gauges, Peter Ghazal, Hideya Kawaji, Lu Li, Yukiko Matsuoka, Alice Villéger, Sarah E Boyd, Laurence Calzone, Melanie Courtot, Ugur Dogrusoz, Tom C Freeman, Akira Funahashi, Samik Ghosh, Akiya Jouraku, Sohyoung Kim, Fedor Kolpakov, Augustin Luna, Sven Sahle, Esther Schmidt, Steven Watterson, Guanming Wu, Igor Goryanin, Douglas B Kell, Chris Sander, Herbert Sauro, Jacky L Snoep, Kurt Kohn & Hiroaki Kitano, The Systems Biology Graphical Notation, Nature Biotechnol. 2009 Aug;27(7) 735 - 741 [doi:10.1038/nbt1558]
Krantz M, Ahmadpour D, Ottosson LG, Warringer J, Waltermann C, Nordlander B, Klipp E, Blomberg A, Hohmann S, Kitano H., Robustness and fragility in the yeast high osmolarity glycerol (HOG) signal-transduction pathway. Mol Syst Biol. 2009;5:281. Epub 2009 Jun 16 [doi:10.1038/msb.2009.36]
Matsuoka Y.; Ghosh S.; Kitano H. ; Consistent design schematics for biological systems: standardization of representation in biological engineering. J. R. Soc. Interface. 2009 [doi:10.1098/rsif.2009.0046.focus]
Further publications related to this Unit are available at http://sbi.jp/Publication.htm