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Yung-Keun Kwon
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2020 – today
- 2021
- [j22]Hung-Cuong Trinh, Yung-Keun Kwon:
A novel constrained genetic algorithm-based Boolean network inference method from steady-state gene expression data. Bioinform. 37(Supplement): 383-391 (2021) - 2020
- [c12]Shohag Barman, Hira Lal Gope, Yung-Keun Kwon:
A Boolean network inference from time-series gene expression data using a statistical method. ICCA 2020: 27:1-27:5
2010 – 2019
- 2018
- [j21]Shohag Barman, Yung-Keun Kwon:
A Boolean network inference from time-series gene expression data using a genetic algorithm. Bioinform. 34(17): i927-i933 (2018) - [j20]Thuy-An Dinh, Yung-Keun Kwon:
An Empirical Study on Importance of Modeling Parameters and Trading Volume-Based Features in Daily Stock Trading Using Neural Networks. Informatics 5(3): 36 (2018) - 2017
- [j19]Cong-Doan Truong, Yung-Keun Kwon:
Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks. BMC Syst. Biol. 11(S-7): 57-68 (2017) - [j18]Maulida Mazaya
, Hung-Cuong Trinh
, Yung-Keun Kwon:
Construction and analysis of gene-gene dynamics influence networks based on a Boolean model. BMC Syst. Biol. 11(S-7): 101-111 (2017) - 2016
- [j17]Hung-Cuong Trinh
, Yung-Keun Kwon:
Edge-based sensitivity analysis of signaling networks by using Boolean dynamics. Bioinform. 32(17): 763-771 (2016) - [j16]Yung-Keun Kwon
:
Properties of Boolean dynamics by node classification using feedback loops in a network. BMC Syst. Biol. 10: 83 (2016) - [j15]Cong-Doan Truong, Tien-Dzung Tran, Yung-Keun Kwon:
MORO: a Cytoscape app for relationship analysis between modularity and robustness in large-scale biological networks. BMC Syst. Biol. 10(4): 521-530 (2016) - [j14]Yung-Keun Kwon, Junil Kim
, Kwang-Hyun Cho:
Dynamical Robustness against Multiple Mutations in Signaling Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 13(5): 996-1002 (2016) - 2015
- [j13]Hung-Cuong Trinh
, Yung-Keun Kwon:
Effective Boolean dynamics analysis to identify functionally important genes in large-scale signaling networks. Biosyst. 137: 64-72 (2015) - 2014
- [j12]Tien-Dzung Tran
, Yung-Keun Kwon:
Hierarchical closeness efficiently predicts disease genes in a directed signaling network. Comput. Biol. Chem. 53: 191-197 (2014) - [c11]Duc-Hau Le, Nguyen Xuan Hoai, Yung-Keun Kwon:
A Comparative Study of Classification-Based Machine Learning Methods for Novel Disease Gene Prediction. KSE 2014: 577-588 - 2013
- [j11]Duc-Hau Le, Yung-Keun Kwon:
A coherent feedforward loop design principle to sustain robustness of biological networks. Bioinform. 29(5): 630-637 (2013) - [j10]Duc-Hau Le, Yung-Keun Kwon:
Neighbor-favoring weight reinforcement to improve random walk-based disease gene prioritization. Comput. Biol. Chem. 44: 1-8 (2013) - 2012
- [j9]Duc-Hau Le, Yung-Keun Kwon:
GPEC: A Cytoscape plug-in for random walk-based gene prioritization and biomedical evidence collection. Comput. Biol. Chem. 37: 17-23 (2012) - 2011
- [j8]Duc-Hau Le, Yung-Keun Kwon:
The effects of feedback loops on disease comorbidity in human signaling networks. Bioinform. 27(8): 1113-1120 (2011) - [j7]Duc-Hau Le, Yung-Keun Kwon:
NetDS: a Cytoscape plugin to analyze the robustness of dynamics and feedforward/feedback loop structures of biological networks. Bioinform. 27(19): 2767-2768 (2011)
2000 – 2009
- 2008
- [j6]Yung-Keun Kwon, Kwang-Hyun Cho:
Quantitative analysis of robustness and fragility in biological networks based on feedback dynamics. Bioinform. 24(7): 987-994 (2008) - [j5]Yung-Keun Kwon, Kwang-Hyun Cho:
Coherent coupling of feedback loops: a design principle of cell signaling networks. Bioinform. 24(17): 1926-1932 (2008) - 2007
- [j4]Yung-Keun Kwon, Kwang-Hyun Cho:
Analysis of feedback loops and robustness in network evolution based on Boolean models. BMC Bioinform. 8 (2007) - [j3]Yung-Keun Kwon, Sun Shim Choi, Kwang-Hyun Cho:
Investigations into the relationship between feedback loops and functional importance of a signal transduction network based on Boolean network modeling. BMC Bioinform. 8 (2007) - [j2]Sung-Soon Choi, Yung-Keun Kwon, Byung Ro Moon:
Properties of Symmetric Fitness Functions. IEEE Trans. Evol. Comput. 11(6): 743-757 (2007) - [j1]Yung-Keun Kwon, Byung Ro Moon:
A Hybrid Neurogenetic Approach for Stock Forecasting. IEEE Trans. Neural Networks 18(3): 851-864 (2007) - 2006
- [c10]Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon:
Nonlinear parametric regression in genetic programming. GECCO 2006: 943-944 - [c9]Sung-Soon Choi, Yung-Keun Kwon, Byung Ro Moon:
Properties of symmetric fitness functions. GECCO 2006: 1117-1124 - 2005
- [c8]Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon:
Stock prediction based on financial correlation. GECCO 2005: 2061-2066 - [c7]Yung-Keun Kwon, Byung Ro Moon:
Nonlinear feature extraction using a neuro genetic hybrid. GECCO 2005: 2089-2096 - 2004
- [c6]Yung-Keun Kwon, Byung Ro Moon:
Evolving Features in Neural Networks for System Identification. GECCO (2) 2004: 404-405 - [c5]Yung-Keun Kwon, Byung Ro Moon:
Evolutionary Ensemble for Stock Prediction. GECCO (2) 2004: 1102-1113 - 2003
- [c4]Yong-Hyuk Kim, Yung-Keun Kwon, Byung Ro Moon:
Problem-Independent Schema Synthesis for Genetic Algorithms. GECCO 2003: 1112-1122 - [c3]Yung-Keun Kwon, Byung Ro Moon:
Daily Stock Prediction Using Neuro-genetic Hybrids. GECCO 2003: 2203-2214 - [c2]Seung-Jin Yang, Yong-Geon Kim, Yung-Keun Kwon, Byung Ro Moon:
Assignment Copy Detection Using Neuro-genetic Hybrids. GECCO 2003: 2426-2427 - 2002
- [c1]Yung-Keun Kwon, Sung-Deok Hong, Byung Ro Moon:
A Genetic Hybrid For Critical Heat Flux Function Approximation. GECCO 2002: 1119-1125
Coauthor Index
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