Challenges and Opportunities for Bioinformatics and Computational Biology in Plant Science

Seung Rhee⁰
(0) Carnegie Institution for Science

Abstract
Plants make up the biggest biotic component of the biosphere and play essential roles in all ecosystems. Our survival and well-being depend on plants and this dependence will increase as the climate changes rapidly. To improve how we obtain food, energy, and materials from plants and steward the health of our environment for future generations, we need to understand how plants work at multiple scales from molecules to cells to ecosystems. A major challenge to achieving this goal is a limited understanding of functions of plant genes. The majority of genes in plant genomes are uncharacterized and many of them are found only in plant lineages. Traditional sequence-similarity based biochemical function inference cannot address this challenge. Another aspect of gene function that is critical but generally lacking is the spatial and temporal context under which gene products operate. These challenges have, in part, driven the spectacular advances and inventions in genomics, imaging, mass spectrometry and we are now capable of high-throughput, high-content, and high-resolution measurements of gene and protein function parameters. Along with these technologies and emerging datasets, we need advances in computational biology and bioinformatics tools, concepts, and methods. In this talk, I will describe these challenges and some of the efforts we are making in addressing them.