Masaaki Oyama

By Hiroko Ao-Kondo, Hiroko Kozuka-Hata and Masaaki Oyama

Part of the book: Computational Biology and Applied Bioinformatics

By Tadashi Yamamoto, Makoto Saito, Kentaro Kumazawa, Ayano Doi, Atsuka Matsui, Shiori Takebe, Takuya Amari, Masaaki Oyama and Kentaro Semba

Part of the book: Breast Cancer

By Hiroko Kozuka-Hata, Yumi Goto and Masaaki Oyama

Part of the book: Oncogenomics and Cancer Proteomics

By Hiroko Kozuka‐Hata and Masaaki Oyama

Post‐translational modifications, such as phosphorylation, acetylation and ubiquitination, are widely known to play various important roles in cellular signalling. Recent significant advances in mass spectrometry‐based proteomics technology enable us not only to comprehensively identify expressed proteins but also to unveil their post‐translational modifications with high sensitivity. In our advanced proteome bioinformatics frameworks, statistical network analyses of large‐scale information on various post‐translational modification dynamics were conducted to define the key machinery for cancer stem cell properties. The bioinformatical approaches using IPA (ingenuity pathway analysis), NetworKIN and a newly developed platform named PTMapper (post‐translational modification mapper) allowed us to perform network‐wide prediction of upstream interactors/kinases with the related information on the diseases and functions, leading to systematic finding of novel drug candidates to regulate aberrant signalling in cancer stem cells. In this chapter, we apply patient‐derived glioblastoma stem cells as a representative model of cancer stem cells to introduce some useful platforms for statistical and mathematical network analyses based on the large‐scale phosphoproteome data.

Part of the book: Applications of RNA-Seq and Omics Strategies