Plant Omics: Advances in Big Data Biology

Author Biography

Hajime Ohyanagi (Edited By) Dr. Hajime Ohyanagi is the director of JCRAC Data Center at National Center for Global Health and Medicine, Japan. He has received a BSc and a MS from University of Tokyo and PhD from SOKENDAI (The Graduate University for Advanced Studies). He has been working on plant omics (genomics, transcriptomics, and proteomics) and plant domestication. His current project is focusing on the molecular evolution of human pathogenic virus, and the general clinical bioinformatics. Eiji Yamamoto (Edited By) Dr. Eiji Yamamoto received a BSc from Osaka Prefecture University, Japan, and MSc and PhD degrees in agriculture from Nagoya University, Japan. He worked as a Researcher at National Agriculture and Food Research Organization, Japan and at Kazusa DNA Research Institute, Japan before recruited as a Project Lecturer at Meiji University, Japan. His research interests include genetics and genomics of crop plants such as genome-wide association study and genomic selection. Currently he is working on application of advanced genetics and genomics to practical plant breeding. Ai Kitazumi (Edited By) Dr. Ai Kitazumi is a research associate of computational biology for the De los Reyes laboratory at Texas Tech University. She has received a BA from College of the Atlantic, a MS from University of Maine and PhD from Texas Tech University. Her current research is addressing the genomic basis of transgressive segregation in plants by combining genomics, transcriptome, methylome, and prediction of recombination sites and chromatin confirmation. Kentaro Yano (Edited By) Dr. Kentaro Yano is a professor in the School of Agriculture at Meiji University, Japan. After receiving a PhD degree from Graduate School of Agriculture, Kyoto University, he has been working on big data integration to advance the plant omics research. His group has developed knowledge-based databases (e.g., TOMATOMICS, PODC) that integrates high-quality expression data from re-analysis of public datasets and the literature curated information on genes in crops and model plants through natural language processing.