| Professor | Kengo KINOSHITA |
The Department of In Silico focuses on understanding biological systems by computational analyses of large-scale data such as genome sequence, gene expression data and protein structures.
It is a well-known fact that traditional biology has tried to enumerate as many biological phenomena as possible, resulting to thicker and thicker textbooks. Although the increase of biological information is quite useful to improve our understanding of biological systems, the increase of information makes it quite difficult to deduce useful information from raw experimental data. In other words, better data analyses are needed to lead us to a better understanding of biological systems. These considerations help us to develop new algorithms and to apply them to analyze large-scale data in this “big bang” era of biological information.
Research Topics
・Computational biology
・Multi-omics analyses
・Genome cohort study
Selected Publications
1. PNPO-PLP axis senses prolonged hypoxia in macrophages by regulating lysosomal activity
Nature Metabolism, 2024
Sekine H*, Takeda H*, Takeda N, … Kinoshita K, Motohashi H
2. Genetic architecture of alcohol consumption identified by a genotype-stratified GWAS and impact on esophageal cancer risk in Japanese people
Science Advances, 2024
Koyanagi YN, Nakatochi M, … Kinoshita K, Matsuo K
3. Simulating metabolic pathways to enhance interpretations of metabolome genome-wide association studies
Scientific Reports, 2025
Kodate S, Sato M, … Kinoshita K
4. Association of circulating metabolites and polygenic risk score with incident type 2 diabetes: a prospective community-based cohort study
Cardiovascular Diabetology, 2025
Takase M, Nakaya N, … Kinoshita K, Yamamoto M
5. Deep learning-based histopathological assessment of tubulo-interstitial injury in chronic kidney diseases
Communications Medicine, 2025
Suzuki N, Kojima K, … Kinoshita K, Shido K
Research Interests
bioinformatics, genome informatics, metabolome analysis, protein structure analyses