The University of Wisconsin is awarded a grant to conduct planning for an institute to advance research in phenomics through the development of software and high-throughput computational methods for capturing and analyzing data on biological form and function. A major goal in biology research is to understand how an organism?s complement of genes (the genome) contributes to the appearance, growth, development, behavior, etc. of the organism (the phenotype). Much phenotype information can be captured in digital images of organisms undergoing growth and development at scales ranging from microscopic cells to whole plants in crop fields. The rapidly growing realization of how effectively image analysis can advance the study of genotype-to-phenotype relationships adds some urgency to the need for improved computational methods. Currently, research labs adopting this experimental approach are each creating their own custom cyber infrastructures for collecting and analyzing images to achieve the necessary degree of automation and throughput. This conceptualization project will bring biologists and computer scientists together to investigate the cyber infrastructure (CI) developments needed to facilitate image-based phenotype research. The ideas to explore can be cast into general questions. How can the computational aspects of phenotype research be made routine enough for a biology research group to use without continuous support of a computer science staff? Do different research contexts (e.g. primarily undergraduate or industrial campuses) require different solutions? What can be done to increase the number of research biologists naturally inclined and academically prepared to work at the computation/math/biology interface where phenotype research resides? Invited-participation workshops and open events at key conferences will be conducted to generate informed debate. A Steering Committee consisting of diversely experienced biologists and computer scientists headed by the PI and assisted by staff will orchestrate the activities and synthesize the findings into a public report that will include recommendations about how to create an effective and easy-to-use cyberinfrastructure that would advance this important area of biology research. Plant biology research will often be the example but any field that generates and analyzes large, high-dimensional datasets, of which stacks and layers of digital images are just one example, stands to benefit from this project. Another aspect that gives this project a broad impact is the emphasis on education and preparation of the next generation of biology researchers. Biology students in general must become better prepared for work at the biology/computation/math interface or even the very best CI will be utilized by only a narrow portion of the research community that stands to benefit from it.
