Collaborative Research: CDI Type-1: A Computer Framework for Modeling Complex Pattern Formation
Collaborative Research: CDI Type-1: A Computer Framework for Modeling Complex Pattern Formation
批准号:
1124665
负责人:
Jeffrey Habig
金额:
$30.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-01 至 2015-08-31
中文摘要
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英文摘要
The mechanisms living systems use to establish and maintain complex 3-dimensional shapes during embryonic development are poorly understood even though molecular and cell biologists have generated mountains of data about genes and their effects on organisms. Fundamental advances in controlling biological form are stymied by the difficulty of obtaining shape information through the analysis of gene networks such that it is currently difficult or impossible for scientists to generate testable models of shape based on experimental results from current biological research. These investigators will apply state-of-the-art computational science and artificial intelligence to create a novel suite of computational tools that will fundamentally integrate numerous areas of biology and engineering to promote research into the mechanisms used by organisms for establishing and maintaining their 3-dimensional shape. This "Bioinformatics of Shape" project will integrate experimental data, a new mathematical language, a system for storing and mining data, a modeling environment within which rule sets for regulatory mechanisms can be simulated on computers, and an artificial intelligence module that will help scientists discover and test novel ideas about how shape is generated through genetics. The benefits to society of this new kind of collaboration between computer scientists and biologists include the translation of molecular and cell biological data into a new level of understanding that could have implications for regenerative medicine, adaptive and self-repairing devices for robotics and other engineering applications. The work will provide unique training opportunities for students, establish a proof-of-principle for new educational tools at the boundary between artificial intelligence and biology, and facilitate data to knowledge production in a number of fields, such as developmental biology, evolutionary biology, and the engineering of complex adaptive systems.
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