Result 1 to 20 of 35 total
Biomarker discovery using 1-norm regularization for multiclass earthworm microarray gene expression data. (English)
Neurocomputing 92, 36-43 (2012).
1
Gene expression studies with DGL global optimization for the molecular classification of cancer. (English)
Soft Comput. 15, No. 1, 111-129 (2011).
2
Clustering of multiple microarray experiments using information integration. (English)
Böhm, Christian (ed.) et al., Information technology in bio- and medical informatics. Second international conference, ITBAM 2011, Toulouse, France, August 29‒September 2, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-23207-7/pbk). Lecture Notes in Computer Science 6865, 123-137 (2011).
3
A very fast algorithm for matrix factorization. (English)
Stat. Probab. Lett. 81, No. 7, 773-782 (2011).
4
Assessment of evaluation criteria for survival prediction from genomic data. (English)
Biom. J. 53, No. 2, 202-216 (2011).
5
Noise-robust algorithm for identifying functionally associated biclusters from gene expression data. (English)
Inf. Sci. 181, No. 3, 435-449 (2011).
6
Selecting few genes for microarray gene expression classification. (English)
Meseguer, Pedro (ed.) et al., Current topics in artificial intelligence. 13th conference of the Spanish association for artificial intelligence, CAEPIA 2009, Seville, Spain, November 9‒13, 2009. Selected papers. Berlin: Springer (ISBN 978-3-642-14263-5/pbk). Lecture Notes in Computer Science 5988. Lecture Notes in Artificial Intelligence, 111-120 (2010).
7
Simulated annealing based automatic fuzzy clustering combined with ANN classification for analyzing microarray data. (English)
Comput. Oper. Res. 37, No. 8, 1369-1380 (2010).
8
Efficient mining of multilevel gene association rules from microarray and gene ontology. (English)
Inf. Syst. Front. 11, No. 4, 433-447 (2009).
9
An efficient gene selection algorithm based on mutual information. (English)
Neurocomputing 72, No. 4-6, 991-999 (2009).
10
Towards improving fuzzy clustering using support vector machine: application to gene expression data. (English)
Pattern Recognition 42, No. 11, 2744-2763 (2009).
11
Finding rule groups to classify high dimensional gene expression datasets. (English)
Comput. Biol. Chem. 33, No. 1, 108-113 (2009).
12
Nonparametric clustering of functional data. (English)
Stat. Interface 1, No. 1, 47-62 (2008).
13
Statistical significance of clustering for high-dimension, low-sample size data. (English)
J. Am. Stat. Assoc. 103, No. 483, 1281-1293 (2008).
14
Independent arrays or independent time courses for gene expression time series data analysis. (English)
Neurocomputing 71, No. 10-12, 2377-2387 (2008).
15
State-of-the-art of cluster analysis of gene expression data. (Chinese)
Acta Autom. Sin. 34, No. 2, 113-120 (2008).
16
A genetic algorithm-based method for feature subset selection. (English)
Soft Comput. 12, No. 2, 111-120 (2008).
17
Discovering biclusters by iteratively sorting with weighted correlation coefficient in gene expression data. (English)
J. VLSI Signal Process. 50, No. 3, 267-280 (2007).
18
Strategies for identifying statistically significant dense regions in microarray data. (English)
IEEE/ACM Transactions on Computational Biology and Bioinformatics 04, No. 03, 415-429 (2007).
19
Development of two-stage SVM-RFE gene selection strategy for microarray expression data analysis. (English)
IEEE/ACM Transactions on Computational Biology and Bioinformatics 04, No. 03, 365-381 (2007).
20
Result 1 to 20 of 35 total
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