Kazuo Ishii
Tokyo University of Agriculture and Technology
Japan
Title: Statistical computing and mathematical modeling for understanding of biological functions using big data
Biography
Biography: Kazuo Ishii
Abstract
Emergence of the next generation sequencing technologies and its application to clinical and biological research opened the door of the era of genomic big data. Today, realizing the personal medicine with big data is fascinating topic in the current clinical research. For manipulation and processing of genomic big data, we are utilizing four strategies of information technology: (1) Monte-Carlo Simulation, random sampling from the genomic big data. (2) HPC (high performance computing), possessing Many Core CPU and Large Memory. (3) Cloud-based Hadoop technology containing distributed file systems (HDFS) and distributed processing systems (MapReduce) on the Amazon Web Services (AWS). (4) non-Hadoop Shell scripting technology including distributed file systems and distributed processing system without hadoop. Monte-Carlo Simulation is a powerful method for optimization and elucidation of the biological functions using genomic big data. Here we will focus on the powerful and novel application of Monte-Carlo Simulation for genomic big data.
