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ORCIDBernard Chen 0001
Person information
- affiliation: University of Central Arkansas, Department of Computer Science, Conway, AR, USA
- affiliation (former): Georgia State University, Department of Computer Science, Atlanta, GA, USA
Other persons with the same name
- Bernard Chen 0002 — Monash University, Melbourne, VIC, Australia
- Bernard Chen 0003 — University of Melbourne / Royal Victorian Eye and Ear Hospital, VIC, Australia
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2020 – today
- 2023
[b1]Bernard Chen:
Wineinformatics - A New Data Science Application. Springer Briefs in Computer Science, Springer 2023, ISBN 978-981-19-7368-0, pp. 1-69- 2020
- [j10]James Palmer, Victor S. Sheng, Travis Atkison, Bernard Chen:
Classification on grade, price, and region with multi-label and multi-target methods in wineinformatics. Big Data Min. Anal. 3(1): 1-12 (2020) - [d1]Bernard Chen:
Wineinformatics: 21st Century Bordeaux Wines Dataset. IEEE DataPort, 2020
2010 – 2019
- 2019
- [c25]Bernard Chen, David Jones, Mustafa Tunc, Kristen Chipolla, Jorge Beltrán:
Weather Impacts on Wine, A BiMax examination of Napa Cabernet in 2011 and 2012 Vintage. ICDM 2019: 242-250 - 2018
- [j9]Travis Atkison, Stanislav Ponomarev, Randy K. Smith, Bernard Chen:
Feature Extraction Optimization for Network Intrusion Detection in Control System Networks. Int. J. Netw. Secur. 20(5): 853-861 (2018) - [j8]Bernard Chen:
Editorial. Trans. Mach. Learn. Data Min. 11(1): 1 (2018) - 2017
- [j7]Bernard Chen, Hai Le, Travis Atkison, Dongsheng Che:
A Wineinformatics Study for White-box Classification Algorithms to Understand and Evaluate Wine Judges. Trans. Mach. Learn. Data Min. 10(1): 3-24 (2017) - [c24]Bernard Chen, Clifford A. Tawiah, James Palmer, Recep Erol
:
Multi-class wine grades predictions with hierarchical support vector machines. ICNC-FSKD 2017: 111-115 - [c23]Bernard Chen, Krizia Houston Buck, Caleb Lawrence, Christopher Moore, Jeremy Yeatts, Travis Atkison:
Granular computing in wineinformatics. ICNC-FSKD 2017: 1228-1232 - [c22]Dongsheng Che, Pingsheng Gao, Pu Tian, Bernard Chen:
Discovering genomic islands in microbial genomes using a genetic algorithm. ICNC-FSKD 2017: 2016-2023 - 2016
- [c21]Bernard Chen, Christopher Rhodes, Alexander Yu, Valentin Velchev:
The Computational Wine Wheel 2.0 and the TriMax Triclustering in Wineinformatics. ICDM 2016: 223-238 - [c20]Bernard Chen, Hai Le, Christopher Rhodes, Dongsheng Che:
Understanding the Wine Judges and Evaluating the Consistency Through White-Box Classification Algorithms. ICDM 2016: 239-252 - 2015
- [c19]Bernard Chen, Valentin Velchev, Bryce Nicholson, Joey Garrison, Moani Iwamura, Ryan Battisto:
Wineinformatics: Uncork Napa's Cabernet Sauvignon by Association Rule Based Classification. ICMLA 2015: 565-569 - 2014
- [c18]Bernard Chen, Christopher Rhodes, Aaron Crawford, Lorri Hambuchen:
Wineinformatics: Applying Data Mining on Wine Sensory Reviews Processed by the Computational Wine Wheel. ICDM Workshops 2014: 142-149 - 2013
- [c17]Cody Hudson, Bernard Chen:
Variable-Length Protein Sequence Motif Extraction Using Hierarchically-Clustered Hidden Markov Models. ICMLA (1) 2013: 173-178 - [c16]Bernard Chen, Roshan Doolabh, Fusheng Tang:
Determining Potential Yeast Longevity Genes via PPI Networks and Microarray Data Clustering Analysis. ICMLA (1) 2013: 370-373 - [c15]Bernard Chen, Cody Hudson, Aaron Crawford, Minwoo Kim:
Protein Local Tertiary Structure Prediction Using the Adaptively-Branching FGK-DF Model. ICMLA (1) 2013: 378-381 - 2012
- [c14]Benjamine Nordin, Chenyi Hu, Bernard Chen, Victor S. Sheng:
Interval-Valued Centroids in K-Means Algorithms. ICMLA (1) 2012: 478-481 - 2011
- [j6]Wooyoung Kim, Bernard Chen, Jingu Kim, Yi Pan, Haesun Park:
Sparse nonnegative matrix factorization for protein sequence motif discovery. Expert Syst. Appl. 38(10): 13198-13207 (2011) - 2010
- [j5]Sinan Kockara, Mutlu Mete, Bernard Chen, Kemal Aydin:
Analysis of density based and fuzzy c-means clustering methods on lesion border extraction in dermoscopy images. BMC Bioinform. 11(S-6): S26 (2010) - [j4]Bernard Chen, Jieyue He, Stephen Pellicer, Yi Pan:
Using Hybrid Hierarchical K-means (HHK) clustering algorithm for protein sequence motif Super-Rule-Tree (SRT) structure construction. Int. J. Data Min. Bioinform. 4(3): 316-330 (2010) - [c13]Bernard Chen, Michael Miller, Timothy Montgomery, Terrance Griffin:
Clustering using Positional Association Rules Algorithm on Protein Sequence Motifs. BIOCOMP 2010: 75-80 - [c12]Vincent Yip, Bernard Chen, Sinan Kockara:
Extraction of Protein Sequence Motifs Information by Bi-Clustering Algorithm. BIOCOMP 2010: 185-190 - [c11]Bernard Chen, Christopher Rhodes, Christopher Kline, Luke Irvin:
Protein Sequence Motif Information Generated by Fuzzy - Hybrid Hierarchical K-means Clustering Algorithm. BIOCOMP 2010: 198-201
2000 – 2009
- 2009
- [j3]Bernard Chen, Matthew Johnson:
Protein local 3D structure prediction by Super Granule Support Vector Machines (Super GSVM). BMC Bioinform. 10(S-11): 15 (2009) - [j2]Bernard Chen, Stephen Pellicer, Phang C. Tai, Robert W. Harrison, Yi Pan:
Novel efficient granular computing models for protein sequence motifs and structure information discovery. Int. J. Comput. Biol. Drug Des. 2(2): 168-186 (2009) - [c10]Bernard Chen, Sinan Kockara:
Mining Positional Association Super-Rules on Fixed-Size Protein Sequence Motifs. BIBE 2009: 1-8 - [c9]Tansel Halic, Sinan Kockara, Coskun Bayrak, Richard Rowe, Bernard Chen:
Soft Tissue Deformation and Optimized Data Structures for Mass Spring Methods. BIBE 2009: 45-52 - 2008
- [j1]Bernard Chen, Stephen Pellicer, Phang C. Tai, Robert W. Harrison, Yi Pan:
Efficient Super Granular SVM Feature Elimination (Super GSVM-FE) model for protein sequence motif information extraction. Int. J. Funct. Informatics Pers. Medicine 1(1): 8-25 (2008) - [c8]Bernard Chen, Jieyue He, Stephen Pellicer, Yi Pan:
Protein Sequence Motif Super-Rule-Tree (SRT) Structure Constructed by Hybrid Hierarchical K-Means Clustering Algorithm. BIBM 2008: 98-103 - [p1]Jieyue He, Hae-Jin Hu, Bernard Chen, Phang C. Tai, Robert W. Harrison, Yi Pan:
Rule Extraction from SVM for Protein Structure Prediction. Rule Extraction from Support Vector Machines 2008: 227-252 - 2007
- [c7]Bernard Chen, Stephen Pellicer, Phang C. Tai, Robert W. Harrison, Yi Pan:
Super Granular Shrink-SVM Feature Elimination (Super GS-SVM-FE) Model for Protein Sequence Motif Information Extraction. BIBE 2007: 379-386 - [c6]Bernard Chen, Stephen Pellicer, Phang C. Tai, Robert W. Harrison, Yi Pan:
Super Granular SVM Feature Elimination (Super GSVM-FE) Model for Protein Sequence Motif Informnation Extraction. CIBCB 2007: 317-322 - [c5]Xuezheng Fu, Bernard Chen, Yi Pan, Robert W. Harrison:
Statistical Estimate for the Size of the Protein Structural Vocabulary. ISBRA 2007: 530-538 - 2006
- [c4]Bernard Chen, Phang C. Tai, Robert W. Harrison, Yi Pan:
FIK Model: Novel Efficient Granular Computing Model for Protein Sequence Motifs and Structure Information Discovery. BIBE 2006: 20-26 - [c3]Bernard Chen, Phang C. Tai, Robert W. Harrison, Yi Pan:
Novel Clustering Algorithm Combined With DSSP Post Processing For Protein Sequence Motif Discovering. GrC 2006: 449-452 - 2005
- [c2]Bernard Chen, Robert W. Harrison, Yi Pan, Phang C. Tai:
Novel Hybrid Hierarchical-K-means Clustering Method (H-K-means) for Microarray Analysis. CSB Workshops 2005: 105-108 - [c1]Jieyue He, Bernard Chen, Hae-Jin Hu, Robert W. Harrison, Phang C. Tai, Yisheng Dong, Yi Pan:
Rule Clustering and Super-rule Generation for Transmembrane Segments Prediction. CSB Workshops 2005: 224-227
Coauthor Index
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