About iGECE
Program News
and the Team
Infectious Disease
and Biodefense
Cancer Systems and
Network Biology
Bird Genomics and
Systems Biology
Super-computers for
Bioinformatics Processing
Legume Systems and Network Biology
Soybean Transcription
Factor Knowledgebase
- Soy-TFKB
Wild Legumes as
Novel Source for
Biofuel Production
Purple False Brome WRKY Knowledgebase
Systems Biologys for Energy and Environment
Novel Genes and Networks for Phytoremediation
Chemical Toxicity, Biomarker Discovery, and Environmental Risk Assessment
of Munitions on
Sentinel Species
RDX Toxicity and
Biomarker Discovery
Systems Genomics of Environmental
Sentinel Species

Cyberinfrastructure Establishment for Achieving Predictive and Systems Level Understanding of Complex Biological and Environmental Systems

  • The term ---cyberinfrastructure was first used by a National Science Foundation (NSF) Blue-Ribbon Committee in 2003 in response to question on how NSF can remove existing barriers to rapid evolution of high performance computing via supercomputers and make it truly usable by all nationís scientists and citizens.

  • As large-scale omics-based systems biology experiments grow, the quantity of data generated from these sources is also growing. The world generated 800,000 petabytes and 1.2 million petabytes (or 1.2 zettabytes) of digital information in 2009 and 2010, respectively. These datasets must be processed, analyzed, and transformed to yield information of value, however, many of the standard approaches in scientific computing and visualization break down at the petabyte-scales of many of the datasets of interest to the scientific communities.

  • Cyberinfrastructure refers to the new research environments that support advanced data acquisition, data storage, data management, data integration, data mining, data visualization and other high throughput computing and information processing services over the internet. In scientific usage, cyberinfrastructure is a technological solution to the problem of efficiently connecting data, computers, and people with the goal of enabling derivation of novel scientific theories and knowledge.

  • Systems Biology is enabling researchers with an integrated approach to biology research to merge insights from many individual efforts to more completely understanding of how biological components work together as a system. Systems biologists use computational algorithm and modeling to collectively investigate and integrate all the dynamic components and interactions underlying the behavior of a living system from a single cell, to multicellular organism and to the complex community.

  • Bioinformatics and computational biology truly shifted its focus from individual genes, proteins, structures and search algorithms to large-scale networks often denoted as -omes such as biome, interactome, genome and proteome. Now biologists are finding the links between the Internet and metabolic pathways, signal transduction pathway and regulatory network, structural interactions of proteins via a network topology or scale-free network. Complex biological systems may be represented and analyzed as computable networks. For example, ecosystems can be modelled as networks of interacting species or individuals. Similarly, a protein can be modelled as a network of amino acids with nodes and edges. Amino acids can be represented as a network of atoms such as carbon, nitrogen and oxygen.

  • Systems Biology Knowledgebase and High Performance Computing are effective cyberinfrastructure components, which consist of networked supercomputing systems for collecting and computing of high valume systems biology datasets, data organizational methods and standards, data analysis tools and visulization interfaces, representing a body of biological knowledge for systems biology research, data mining and knowledge discovery.

  • Driven by the ever-increasing wealth of biological data resulting from new generations of genomics or omics-based technologies, systems biology is demanding an intensive computational environment for comparing and integrating large, heterogeneous datasets and using this information to develop predictive models for product development concepts.

  • iGECE is currenlty developing an open computational environment of Systems Biology Knowledgebases supporting agriculture, bioenergy, environmental science, and systems biology-based medical science for sharing and integrating diverse biological data types, accessing software for systems biology data analysis, and providing resources for modeling and simulation.

  • We promote a cultural change in biology from a focus on individual project-based and isolated efforts to open community and team science with integration of diverse expertises for national critical missions such as energy security, clean environment, strategy on climate change, food security, and biodefense to pathogens, and human health.

  • Besides our technical team's traditonal strength on infectious disease and cancer systems biology projects, iGECE currently also has genomics, systems and network biology, and synthetic biology projects focusing on plants for bioenergy and environment science, and animals of environmental sentinel species, such as earthworm, fish, bird, and lizard etc., for evaluating possible effort on ongoing climate change and environmental quality monitoring for the Department of Defense guarded lands.

This is project development site, last updated by Dr. Jeff Chen on November 5, 2010.

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