-
2
-
-
0035824501
-
Proteomics
-
1). Proteomics. Science, 294, 2074-2085.
-
(2001)
Science
, vol.294
, pp. 2074-2085
-
-
-
3
-
-
18344396961
-
An integrated approach utilizing artificial neural networks and seldi mass spectrometry for the classification of human tumors and rapid identification of potential biomarkers
-
Ball,G., Mian,S., Holding,F., Allibone,R.O., Lowe,J., Ali,S., Li,G., McCardle,S., Ellis,I.O., Creaser,C. and Rees,R.C. (2002). An integrated approach utilizing artificial neural networks and seldi mass spectrometry for the classification of human tumors and rapid identification of potential biomarkers. Bioinformatics, 18, 395-404.
-
(2002)
Bioinformatics
, vol.18
, pp. 395-404
-
-
Ball, G.1
Mian, S.2
Holding, F.3
Allibone, R.O.4
Lowe, J.5
Ali, S.6
Li, G.7
McCardle, S.8
Ellis, I.O.9
Creaser, C.10
Rees, R.C.11
-
4
-
-
0036645099
-
Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men
-
Bao-Ling,A., Yinsheng,Q., John,W.D., Michael,D.W., Mary,A.C., Lisa,H.C., John,O.S., Paul,F.S., Yutaka,Y., Ziding,F. and George,L.W.J. (2002). Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men. Cancer Res., 62, 3609-3614.
-
(2002)
Cancer Res.
, vol.62
, pp. 3609-3614
-
-
Bao-Ling, A.1
Yinsheng, Q.2
John, W.D.3
Michael, D.W.4
Mary, A.C.5
Lisa, H.C.6
John, O.S.7
Paul, F.S.8
Yutaka, Y.9
Ziding, F.10
George, L.W.J.11
-
5
-
-
0030211964
-
Bagging predictors
-
Breiman,L. (1996). Bagging predictors. Mach. Learning, 24, 123-140.
-
(1996)
Mach. Learning
, vol.24
, pp. 123-140
-
-
Breiman, L.1
-
6
-
-
0346786584
-
Arcing classiers
-
Breiman,L. (1998). Arcing classiers.Ann. Statistics, 26, 801-824.
-
(1998)
Ann. Statistics
, vol.26
, pp. 801-824
-
-
Breiman, L.1
-
8
-
-
4143073317
-
Classification and Regression Trees
-
Breiman,L., Friedman,J.H., Olshen,R.A. and Stone,C. (1983). Classification and Regression Trees, Chapman & Hall.
-
(1983)
Chapman & Hall
-
-
Breiman, L.1
Friedman, J.H.2
Olshen, R.A.3
Stone, C.4
-
9
-
-
0000343716
-
Submodel selection and evaluation in regression: The x-random case
-
Breiman,L. and Spector,P. (1992). Submodel selection and evaluation in regression: the x-random case. Int. Stat. Rev., 60, 291-319.
-
(1992)
Int. Stat. Rev.
, vol.60
, pp. 291-319
-
-
Breiman, L.1
Spector, P.2
-
10
-
-
27144489164
-
A tutorial on support vector machines for pattern recognition
-
June)
-
Burges,C.J.C. (1998, June). A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2(2), 121-167.
-
(1998)
Data Mining and Knowledge Discovery,
, vol.2
, Issue.2
, pp. 121-167
-
-
Burges, C.J.C.1
-
11
-
-
0036489046
-
Comparison of discrimination methods for the classification of tumors using gene expression data
-
Dudoit,S., Fridlyand,J. and Speed,T.P. (2002). Comparison of discrimination methods for the classification of tumors using gene expression data. J. Am. Stat. Assoc., 97(457), 77-87.
-
(2002)
J. Am. Stat. Assoc.
, vol.97
, Issue.457
, pp. 77-87
-
-
Dudoit, S.1
Fridlyand, J.2
Speed, T.P.3
-
12
-
-
0031536511
-
Improvements on cross-validation: The .632+ bootstrap method
-
Efron,B. and Tibershirani,R. (1997). Improvements on cross-validation: the .632+ bootstrap method. J. Am. Stat. Assoc., 92, 548-560.
-
(1997)
J. Am. Stat. Assoc.
, vol.92
, pp. 548-560
-
-
Efron, B.1
Tibershirani, R.2
-
13
-
-
0000764772
-
The use of multiple measurements in taxonomic problems
-
Fisher,R.A. (1936). The use of multiple measurements in taxonomic problems.An. Eugenics, 7, 179-188.
-
(1936)
An. Eugenics
, vol.7
, pp. 179-188
-
-
Fisher, R.A.1
-
14
-
-
0031211090
-
A decision-theoretic generalization of on-line learning and an application to boosting
-
Freund,Y. and Schapire,R. (1997). A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci., 55, 119-139.
-
(1997)
J. Comput. Syst. Sci.
, vol.55
, pp. 119-139
-
-
Freund, Y.1
Schapire, R.2
-
15
-
-
0034526162
-
Proteomic strategies for biomarker identification: Progress and challenges
-
Fung,E.T., Wright,G.L.J. and Dalmasso,E.A. (2000). Proteomic strategies for biomarker identification: progress and challenges. Curr. Opin. Mol. Therap., 2, 643-650.
-
(2000)
Curr. Opin. Mol. Therap.
, vol.2
, pp. 643-650
-
-
Fung, E.T.1
Wright, G.L.J.2
Dalmasso, E.A.3
-
16
-
-
0035992398
-
Proteomic analysis of lung adenocarcinoma: Identification of a highly expressed set of proteins in tumors
-
Guoan,C., Tarek,G.G., Chiang-Ching,H., Dafydd,G.T., Kerby,A.S., Jeremy,M.G.T., Sharon,L.R.K., David,E.M., Thomas,J.G., Mark,D.I. et al. (2002). Proteomic analysis of lung adenocarcinoma: identification of a highly expressed set of proteins in tumors. Clin. Cancer Res., 8, 2298-2305.
-
(2002)
Clin. Cancer Res.
, vol.8
, pp. 2298-2305
-
-
Guoan, C.1
Tarek, G.G.2
Chiang-Ching, H.3
Dafydd, G.T.4
Kerby, A.S.5
Jeremy, M.G.T.6
Sharon, L.R.K.7
David, E.M.8
Thomas, J.G.9
Mark, D.I.10
-
17
-
-
0035827588
-
Genome, expression profiling in Escherichia coli k12: Improved statistical inference from DNA microarray data using analysis of variance and a bayesian statistical framework
-
Long,A.D., Mangalam,H., Chan,B.Y.P., Tolleri,L., Hatfield,G.W. and Baldi,P. (2001). Genome, expression profiling in Escherichia coli k12: improved statistical inference from DNA microarray data using analysis of variance and a bayesian statistical framework.J. Biol. Chem., 276, 19937-19944.
-
(2001)
J. Biol. Chem.
, vol.276
, pp. 19937-19944
-
-
Long, A.D.1
Mangalam, H.2
Chan, B.Y.P.3
Tolleri, L.4
Hatfield, G.W.5
Baldi, P.6
-
18
-
-
0003607151
-
-
Academic Press, Inc., San Diego
-
Mardia,K.V., Kent,J.T. and Bibby,J.M. (1979).Multivariate Analysis. Academic Press, Inc., San Diego.
-
(1979)
Multivariate Analysis
-
-
Mardia, K.V.1
Kent, J.T.2
Bibby, J.M.3
-
20
-
-
0037116832
-
Use of proteomic patterns in serum to identify ovarian cancer
-
Petricoin,E.F., Ardekani,A.M., Hitt,B.A., Levine,P.J., Fusaro,V.A., Steinberg,S.M., Mills,G.B., Simine,C., Fishman,D.A., Kohn,E.C. and Liotta,L.A. (2002). Use of proteomic patterns in serum to identify ovarian cancer. The Lancet, 359, 572-577.
-
(2002)
The Lancet
, vol.359
, pp. 572-577
-
-
Petricoin, E.F.1
Ardekani, A.M.2
Hitt, B.A.3
Levine, P.J.4
Fusaro, V.A.5
Steinberg, S.M.6
Mills, G.B.7
Simine, C.8
Fishman, D.A.9
Kohn, E.C.10
Liotta, L.A.11
|