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Jun-Ichiro Inoue

dblp:40/5973 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › network bioinformatics › biological network analysis
molecular network analysis
0.212016
Quantitative phosphoproteomics-based molecular network description for high-resolution kinase-substrate interactome analysis · Bioinform. 2016
Bioinformatics and computational biology › proteomics
phosphoproteomics
0.212016
Quantitative phosphoproteomics-based molecular network description for high-resolution kinase-substrate interactome analysis · Bioinform. 2016
Bioinformatics and computational biology
proteomics
0.212016
Quantitative phosphoproteomics-based molecular network description for high-resolution kinase-substrate interactome analysis · Bioinform. 2016
Bioinformatics and computational biology
systems biology
0.212016
Quantitative phosphoproteomics-based molecular network description for high-resolution kinase-substrate interactome analysis · Bioinform. 2016

Methods — techniques the papers use, named apart from their topics

protein-protein interaction integration · 0.2
YearPublicationVenuePosition
2016 Quantitative phosphoproteomics-based molecular network description for high-resolution kinase-substrate interactome analysis
abstract
MOTIVATION: Phosphorylation-dependent cellular signaling is known to play a diverse role in regulating multiple cellular processes such as proliferation, differentiation and apoptosis. Recent technological advances in mass spectrometry-based phosphoproteomics have enabled us to measure network-wide signaling dynamics in a comprehensive and quantitative manner. As conventional protein-protein interaction (PPI) information-based network analysis is insufficient to systematically analyze phosphorylation site-dependent complex interaction dynamics, here we develop and evaluate a platform to provide a high-resolution molecular network description for kinase-substrate interactome analysis. RESULTS: In this study, we developed a Cytoscape-based bioinformatical platform named 'Post Translational Modification mapper (PTMapper)' to integrate PPI data with publicly available kinase-substrate relations at the resolution of phosphorylated amino acid residues. The previous phosphoproteome data on EGF-induced cellular signaling in glioblastoma stem cells was applied to evaluate our platform, leading to discovery of phosphorylation-dependent crucial signaling modulation in the p70S6K1-related pathway. Our study revealed that high-resolution cellular network description of phosphorylation-site dependent kinase-substrate signaling regulation should accelerate phosphoproteomics-based exploration of novel drug targets in the context of each disease-related signaling. AVAILABILITY AND IMPLEMENTATION: PTMapper and the example data for construction of phosphorylation site-oriented networks are available at https://github.com/y-narushima/PTMapper CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Yuta Narushima, Hiroko Kozuka-Hata, Kouhei Tsumoto, Jun-Ichiro Inoue, Masaaki Oyama
Bioinform.4