Institute of Development, Aging and Cancer, Tohoku University

About

Dept. In Silico

Professor(Additionl) Kengo KINOSHITA
Homepage of This Laboratory

The general focus of our research concerns understanding the biological systems by computational analyses of large-scale data such as genome sequence, gene expression data and protein structures.

Traditional biology tried to enumerate as many biological phenomena as possible and made textbooks thicker and thicker. Of course, it is very interesting to observe the details of each biological phenomenon, but biology is now going into the new era to grasp the general understandings of biological systems, according to the biological information big bang (Fig. 1), the vast accumulation of biological information.

The increase of biological information is very useful to improve our understandings of biological systems, but, at the same time, the increase of information makes it quite difficult to deduce useful information from the raw experimental data. For example, we have shown that sophisticated data treatments are required to obtain true functional relationships between genes, when we use a large number of gene expression data (Fig. 2). In other words, better data analyses lead us to better understandings of biological systems.

These considerations lead us to focus on the development of new algorithms and apply them to analyze large-scale data in the era of biological information big bang.

Fig.1
Fig.1 (Click for large image.)
Fig.2
Fig.2 (Click for large image.)

Some representative publication after 2009

  1. M Shirota, T Ishida, K Kinoshita, Absolute quality evaluation of protein model structures using statistical potentials with respect to the native and reference states, Proteins in press
  2. T Obayashi, K Nishida, K Kasahara, K Kinoshita, ATTED-II updates: condition-specific gene coexpression to extend coexpression analyses and applications to a broad range of flowering plants, PCP in press
  3. T Obayashi and K Kinoshita, COXPRESdb: a database to compare gene coexpression in seven model animals. Nucleic Acids Res, 2010 in press
  4. K Kasahara, K Kinoshita, and T Takagi, Ligand-binding site prediction of proteins based on known fragment-fragment interactions. Bioinformatics, 26, 1493-1499, 2010
  5. C Motono, J Nakata, R Koike, K Shimizu, M Shirota, T Amemiya, K Tomii, N Nagano, N Sakaya, K Misoo, M Sato, A Kidera, H Hiroaki, T Shirai, K Kinoshita, T Noguchi, and M Ota, SAHG, a comprehensive database of predicted structures of all human proteins. Nucleic Acids Res, 2010 in press
  6. W Nunomura, K Kinoshita, M Parra, P Gascard, X An, N Mohandas, and Y Takakuwa, Similarities and differences in the structure and function of 4.1G and 4.1R135, two protein 4.1 paralogues expressed in erythroid cells. Biochem J, 432, 407-416, 2010
  7. T Obayashi and K Kinoshita, Coexpression landscape in ATTED-II: usage of gene list and gene network for various types of pathways. J Plant Res, 123, 311-319, 2010
  8. A Patil, K Kinoshita, and H Nakamura, Domain distribution and intrinsic disorder in hubs in the human protein-protein interaction network. Protein Sci, 19, 1461-1468, 2010
  9. A Patil, K Kinoshita, and H Nakamura, Hub promiscuity in protein-protein interaction networks. Int J Mol Sci, 11, 1930-1943, 2010
  10. T Obayashi and K Kinoshita, Rank of correlation coefficient as a comparable measure for biological significance of gene coexpression, DNA research, 16, 249-260, 2009
  11. K Kinoshita and T Obayashi, Multi-dimensional correlations for gene coexpression and application to the large-scale data of Arabidopsis, Bioinformatics, 25, 2677-2684, 2009
  12. Y Tsuchiya, E Kanamori, H Nakamura and K Kinoshita, Classification of hetero-dimer interfaces using docking models and construction of scoring functions for the complex structure prediction, Adv. Appl. Bioinfo. Chem., 2, 79-100, 2009
  13. M Shirota, T Ishida and K Kinoshita, Analyses on hydrophobic characteristics and attractive effects induced by the different reference states in all-atom-distance-dependent potentials, Protein Sci., 18, 1906-1915, 2009
  14. M Maeda and K Kinoshita, Development of new indices to evaluate protein-protein interfaces: Assembling space volume, assembling space distance, and global shape descriptor, J. Mol. Graph. Mod., 27, 706-711, 2009
  15. T Obayashi, S Hayashi, M Saeki, H Ohta and K Kinoshita, ATTED-II provides coexpressed gene networks for Arabidopsis, Nucleic Acids Res, 37, D987-991, 2009
  16. M Higurashi, T Ishida, and K Kinoshita, PiSite: a database of protein interaction sites using multiple binding states in the PDB, Nucleic Acids Res, 37, D360-364, 2009

Page Top