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Inyoul Y. Lee

dblp:99/1469 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 3

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
3 papers
Bioinformatics and computational biology · 81% Computational science and engineering · 19%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
proteomics
0.222009
Prequips - an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data · Bioinform. 2009
MS-BID: a Java package for label-free LC-MS-based comparative proteomic analysis · Bioinform. 2008
Computational science and engineering › dynamical systems
network dynamics
0.112011
Principal network analysis: identification of subnetworks representing major dynamics using gene expression data · Bioinform. 2011
Bioinformatics and computational biology › biological network › network biology
subnetwork extraction
0.112011
Principal network analysis: identification of subnetworks representing major dynamics using gene expression data · Bioinform. 2011
Bioinformatics and computational biology
systems biology
0.112011
Principal network analysis: identification of subnetworks representing major dynamics using gene expression data · Bioinform. 2011
Bioinformatics and computational biology
biomarker discovery
0.112008
MS-BID: a Java package for label-free LC-MS-based comparative proteomic analysis · Bioinform. 2008

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

principal component analysis · 0.1network analysis · 0.1mass spectrometry · 0.1peptide matching · 0.1peptide detection · 0.1discriminatory peptide selection · 0.1
YearPublicationVenuePosition
2011 Principal network analysis: identification of subnetworks representing major dynamics using gene expression data
abstract
MOTIVATION: Systems biology attempts to describe complex systems behaviors in terms of dynamic operations of biological networks. However, there is lack of tools that can effectively decode complex network dynamics over multiple conditions. RESULTS: We present principal network analysis (PNA) that can automatically capture major dynamic activation patterns over multiple conditions and then generate protein and metabolic subnetworks for the captured patterns. We first demonstrated the utility of this method by applying it to a synthetic dataset. The results showed that PNA correctly captured the subnetworks representing dynamics in the data. We further applied PNA to two time-course gene expression profiles collected from (i) MCF7 cells after treatments of HRG at multiple doses and (ii) brain samples of four strains of mice infected with two prion strains. The resulting subnetworks and their interactions revealed network dynamics associated with HRG dose-dependent regulation of cell proliferation and differentiation and early PrPSc accumulation during prion infection. AVAILABILITY: The web-based software is available at: http://sbm.postech.ac.kr/pna.
Yongsoo Kim, Taek-Kyun Kim, Yungu Kim, Jiho Yoo, Sungyong You, Inyoul Y. Lee, George Carlson, Leroy Hood, Seungjin Choi 0001, Daehee Hwang
Bioinform.6
2009 Prequips - an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data
abstract
SUMMARY: We describe an integrative software platform, Prequips, for comparative proteomics-based systems biology analysis that: (i) integrates all information generated from mass spectrometry (MS)-based proteomics as well as from basic proteomics data analysis tools, (ii) visualizes such information for various proteomic analyses via graphical interfaces and (iii) links peptide and protein abundances to external tools often used in systems biology studies. AVAILABILITY: http://prequips.sourceforge.net
Nils Gehlenborg, Wei Yan 0033, Inyoul Y. Lee, Hyuntae Yoo, Kay Nieselt, Daehee Hwang, Ruedi Aebersold, Leroy Hood
Bioinform.3
2008 MS-BID: a Java package for label-free LC-MS-based comparative proteomic analysis
abstract
UNLABELLED: MS-BID (MS Biomarker Discovery Platform) is an integrative computational pipeline for biomarker discovery using LC-MS-based comparative proteomic analysis. This platform consists of several computational tools for: (i) detecting peptides in the collected patterns; (ii) matching detected peptides across a number of LC-MS datasets and (iii) selecting discriminatory peptides between classes of samples. AVAILABILITY: MS-BID source codes, binaries and documentations are freely available under LGPL from http://tools.proteomecenter.org/msBID.php.
Daehee Hwang, Hookeun Lee, Eugene Yi, Inyoul Y. Lee, Leroy Hood, Ruedi Aebersold
Bioinform.6