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Items: 1 to 20 of 48

1.

Gene assessment and sample classification for gene expression data using a genetic algorithm/k-nearest neighbor method.

Li L, Darden TA, Weinberg CR, Levine AJ, Pedersen LG.

Comb Chem High Throughput Screen. 2001 Dec;4(8):727-39. No abstract available.

PMID:
11894805
2.

Reliable classification of two-class cancer data using evolutionary algorithms.

Deb K, Raji Reddy A.

Biosystems. 2003 Nov;72(1-2):111-29.

PMID:
14642662
3.

A CART-based approach to discover emerging patterns in microarray data.

Boulesteix AL, Tutz G, Strimmer K.

Bioinformatics. 2003 Dec 12;19(18):2465-72.

4.

Simultaneous gene clustering and subset selection for sample classification via MDL.

Jörnsten R, Yu B.

Bioinformatics. 2003 Jun 12;19(9):1100-9.

5.
6.

Improved binary PSO for feature selection using gene expression data.

Chuang LY, Chang HW, Tu CJ, Yang CH.

Comput Biol Chem. 2008 Feb;32(1):29-37.

PMID:
18023261
7.
8.

The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer.

Jaroszewicz S, Simovici DA, Kuo WP, Ohno-Machado L.

IEEE Trans Biomed Eng. 2004 Jul;51(7):1095-102.

PMID:
15248526
9.

New algorithms for multi-class cancer diagnosis using tumor gene expression signatures.

Bagirov AM, Ferguson B, Ivkovic S, Saunders G, Yearwood J.

Bioinformatics. 2003 Sep 22;19(14):1800-7.

10.

Dynamic range-based distance measure for microarray expressions and a fast gene-ordering algorithm.

Ray SS, Bandyopadhyay S, Pal SK.

IEEE Trans Syst Man Cybern B Cybern. 2007 Jun;37(3):742-9.

PMID:
17550128
11.

Cancer DNA microarray analysis considering multi-subclass with graph-based clustering method.

Kawamura T, Mutoh H, Tomita Y, Kato R, Honda H.

J Biosci Bioeng. 2008 Nov;106(5):442-8. doi: 10.1263/jbb.106.442.

PMID:
19111639
12.

Boosting for tumor classification with gene expression data.

Dettling M, Bühlmann P.

Bioinformatics. 2003 Jun 12;19(9):1061-9.

13.

A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis.

Statnikov A, Aliferis CF, Tsamardinos I, Hardin D, Levy S.

Bioinformatics. 2005 Mar 1;21(5):631-43.

14.
15.

Overcoming confounded controls in the analysis of gene expression data from microarray experiments.

Bhattacharya S, Long D, Lyons-Weiler J.

Appl Bioinformatics. 2003;2(4):197-208.

PMID:
15130791
16.

Right- and left-sided colorectal cancers display distinct expression profiles and the anatomical stratification allows a high accuracy prediction of lymph node metastasis.

Komuro K, Tada M, Tamoto E, Kawakami A, Matsunaga A, Teramoto K, Shindoh G, Takada M, Murakawa K, Kanai M, Kobayashi N, Fujiwara Y, Nishimura N, Hamada J, Ishizu A, Ikeda H, Kondo S, Katoh H, Moriuchi T, Yoshiki T.

J Surg Res. 2005 Apr;124(2):216-24.

PMID:
15820251
17.

Optimal number of features as a function of sample size for various classification rules.

Hua J, Xiong Z, Lowey J, Suh E, Dougherty ER.

Bioinformatics. 2005 Apr 15;21(8):1509-15.

18.

Differential gene expression detection and sample classification using penalized linear regression models.

Wu B.

Bioinformatics. 2006 Feb 15;22(4):472-6. Erratum in: Bioinformatics. 2006 Apr 15;22(8):1029.

19.

Improved centroids estimation for the nearest shrunken centroid classifier.

Wang S, Zhu J.

Bioinformatics. 2007 Apr 15;23(8):972-9.

20.

Classification with reject option in gene expression data.

Hanczar B, Dougherty ER.

Bioinformatics. 2008 Sep 1;24(17):1889-95. doi: 10.1093/bioinformatics/btn349.

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