**Author details**

**4. Development of advanced bioinformatical platforms for complicated** 

Although shotgun proteomics strategy based on advanced nanoLC‐MS/MS system can provide us with large‐scale information on various kinds of PTMs, there are only a few PTM‐ based network analysis tools available compared to conventional protein‐protein interaction (PPI). Recently, CEASAR: connecting enzymes and substrates at amino acid resolution [39] and PhosphoPath [40] were developed to visualize kinase‐substrate interactions in a phosphorylation site‐oriented manner. CEASAR was designed to provide a high‐resolution map of kinase‐phosphorylation networks based on functional protein microarrays and bioinformatics analysis. On the other hand, PhosphoPath was developed as a Cytoscape app [41] to visualize both quantitative proteome and phosphoproteome data using PPI information extracted from BioGRID [42] and PhosphoSitePlus [17]. Recently, we also have developed a Cytoscape‐based bioinformatical platform named 'post‐translational modification mapper (PTMapper)' to visualize kinase‐substrate interactions regarding multiple phosphorylation sites on signalling molecules (**Figure 6**) [12]. The kinase‐phosphorylation site interaction dataset for this platform was integratively generated from PhosphoSitePlus [17], Phospho.ELM [43], PhosphoNetworks [44] and Uniprot KB [45], leading to construction of phosphorylation site‐oriented PPI networks using Pathway Commons [46]. We applied this platform to extract crucial kinase‐substrate interactions from the quantitative phosphoproteome data on EGF‐stimulated GSCs [29]. As a result, p70S6K and Lyn were significantly extracted as key

The bioinformatical description of GSC signalling dynamics based on the global quantitative phosphoproteome data led to network‐wide extraction of critical molecules and their related pathways for defining stemness characteristics. Further integrative description of multiple PTM dynamics in GSCs will deepen our understanding of the nature of their cell signalling complexity at the network level. We believe that shotgun proteomics‐based quantitative analyses of cancer stem cell signalling networks in combination with various statistical and mathematical platforms will pave the way to establish new directions towards systematic

We thank Dr. Yuta Narushima for his technical support. We are also thankful to all the members of Medical Proteomics Laboratory, The Institute of Medical Science, The University of Tokyo. This work was supported by grants‐in‐aid for scientific research on innovative areas (integrative understanding of biological signalling networks based on mathematical science)

**kinase‐substrate interaction networks**

274 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

regulators (**Figure 7**).

**Acknowledgements**

**5. Perspectives and conclusions**

evaluation of drug targets in a cell‐type specific manner.

and grant‐in‐aid for scientific research (C).

Hiroko Kozuka‐Hata and Masaaki Oyama\*

\*Address all correspondence to: moyama@ims.u‐tokyo.ac.jp

Medical Proteomics Laboratory, The Institute of Medical Science, The University of Tokyo, Minato‐ku, Tokyo, Japan
