-
1
-
-
0347625462
-
Status of tumor markers in ovarian cancer screening
-
Bast RC, Status of tumor markers in ovarian cancer screening, J Clin Oncol 21:200-205, 2003.
-
(2003)
J Clin Oncol
, vol.21
, pp. 200-205
-
-
Bast, R.C.1
-
2
-
-
33846511305
-
Serum proteomic profiling to predict early relapse in ovarian cancer
-
Knowles LM, Nandi A, Gurnani P et al., Serum proteomic profiling to predict early relapse in ovarian cancer, Gynecol Oncol 96:926, 2005.
-
(2005)
Gynecol Oncol
, vol.96
, pp. 926
-
-
Knowles, L.M.1
Nandi, A.2
Gurnani, P.3
-
3
-
-
0037862963
-
Paclitaxel plus platinum-based chemotherapy versus conventional platinum-based chemotherapy in women with relapsed ovarian cancer: The ICON4/AGO-OVAR-2.2 trial
-
Parmar MK, Ledermann JA, Colombo N et al., Paclitaxel plus platinum-based chemotherapy versus conventional platinum-based chemotherapy in women with relapsed ovarian cancer: The ICON4/ AGO-OVAR-2.2 trial, Lancet 361:2099-2106, 2003.
-
(2003)
Lancet
, vol.361
, pp. 2099-2106
-
-
Parmar, M.K.1
Ledermann, J.A.2
Colombo, N.3
-
4
-
-
11144254100
-
Quantifying reproducibility for differential proteomics: Noise analysis for protein liquid chromatography-mass spectrometry of human serum
-
Anderle M, Roy S, Lin H et al., Quantifying reproducibility for differential proteomics: Noise analysis for protein liquid chromatography-mass spectrometry of human serum, Bioinformatics 20:3575-3582, 2004.
-
(2004)
Bioinformatics
, vol.20
, pp. 3575-3582
-
-
Anderle, M.1
Roy, S.2
Lin, H.3
-
5
-
-
0036324715
-
Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer
-
Li J, Zhang Z, Rosenzweig J et al., Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer, Clin Chem 48:1296-1304, 2002.
-
(2002)
Clin Chem
, vol.48
, pp. 1296-1304
-
-
Li, J.1
Zhang, Z.2
Rosenzweig, J.3
-
6
-
-
1542329047
-
Serum proteomics in cancer diagnosis and management
-
Rosenblatt KP, Bryant-Greenwood P, Killian JK et al., Serum proteomics in cancer diagnosis and management, Annu Rev Med 55:97-112, 2004.
-
(2004)
Annu Rev Med
, vol.55
, pp. 97-112
-
-
Rosenblatt, K.P.1
Bryant-Greenwood, P.2
Killian, J.K.3
-
7
-
-
0034828488
-
Proteomics in early detection of cancer
-
Srinivas PR, Srivastava S, Hanash S et al., Proteomics in early detection of cancer, Clin Chem 47:1901-1911, 2001.
-
(2001)
Clin Chem
, vol.47
, pp. 1901-1911
-
-
Srinivas, P.R.1
Srivastava, S.2
Hanash, S.3
-
8
-
-
0038662530
-
Proteomic applications for the early detection of cancer
-
Wulfkuhle JD, Liotta LA, Petricoin EF, Proteomic applications for the early detection of cancer, Nat Rev Cancer 3:267-275, 2003.
-
(2003)
Nat Rev Cancer
, vol.3
, pp. 267-275
-
-
Wulfkuhle, J.D.1
Liotta, L.A.2
Petricoin, E.F.3
-
9
-
-
0037116832
-
Use of proteomic patterns in serum to identify ovarian cancer
-
Petricoin EF, Ardekani AM, Hitt BA et al., Use of proteomic patterns in serum to identify ovarian cancer, Lancet 359:572-577, 2002.
-
(2002)
Lancet
, vol.359
, pp. 572-577
-
-
Petricoin, E.F.1
Ardekani, A.M.2
Hitt, B.A.3
-
10
-
-
0036791428
-
Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients
-
Qu Y, Adam BL, Yasui Y et al., Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients, Clin Chem 48:1835-1843, 2002.
-
(2002)
Clin Chem
, vol.48
, pp. 1835-1843
-
-
Qu, Y.1
Adam, B.L.2
Yasui, Y.3
-
11
-
-
0742269626
-
Probabilistic disease classification of expression-dependent proteomic data from mass spectrometry of human serum
-
Lilien RH, Farid H, Donald BR, Probabilistic disease classification of expression-dependent proteomic data from mass spectrometry of human serum, J Comput Biol 10(6):925-946, 2003.
-
(2003)
J Comput Biol
, vol.10
, Issue.6
, pp. 925-946
-
-
Lilien, R.H.1
Farid, H.2
Donald, B.R.3
-
12
-
-
0141743613
-
Machine learning approaches to lung cancer prediction from mass spectra
-
Hilario M, Kalousis A, Muller M et al., Machine learning approaches to lung cancer prediction from mass spectra, Proteomics 3:1716-1719, 2003.
-
(2003)
Proteomics
, vol.3
, pp. 1716-1719
-
-
Hilario, M.1
Kalousis, A.2
Muller, M.3
-
13
-
-
0347362474
-
SELDI ProteinChip® array technology: Protein-based predictive medicine and drug discovery applications
-
Reddy G, Dalmasso EA, SELDI ProteinChip® array technology: Protein-based predictive medicine and drug discovery applications, J Biomed Biotechnol 2003(4):237-241, 2003.
-
(2003)
J Biomed Biotechnol
, vol.2003
, Issue.4
, pp. 237-241
-
-
Reddy, G.1
Dalmasso, E.A.2
-
14
-
-
0036855519
-
SELDI proteinchip MS: A platform for biomarker discovery and cancer diagnosis
-
Wright GL Jr., SELDI proteinchip MS: A platform for biomarker discovery and cancer diagnosis, Expert Rev Mol Diagn 2(6):549-563, 2002.
-
(2002)
Expert Rev Mol Diagn
, vol.2
, Issue.6
, pp. 549-563
-
-
Wright Jr., G.L.1
-
15
-
-
3543076921
-
Application of the GA/KNN method to SELDI proteomics data
-
Li L, Umbach DM, Terry P et al., Application of the GA/KNN method to SELDI proteomics data, Bioinformatics 20:1638-1640, 2004.
-
(2004)
Bioinformatics
, vol.20
, pp. 1638-1640
-
-
Li, L.1
Umbach, D.M.2
Terry, P.3
-
16
-
-
0036645099
-
Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men
-
Adam BL, Qu Y, Davis JW et al., 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.
-
(2002)
Cancer Res
, vol.62
, pp. 3609-3614
-
-
Adam, B.L.1
Qu, Y.2
Davis, J.W.3
-
17
-
-
0942265518
-
Diagnosis of ovarian cancer using decision tree classification of mass spectral data
-
Vlahou A, Schorge JO, Gregory BW et al., Diagnosis of ovarian cancer using decision tree classification of mass spectral data, J Biomed Biotechnol 5:308-314, 2003.
-
(2003)
J Biomed Biotechnol
, vol.5
, pp. 308-314
-
-
Vlahou, A.1
Schorge, J.O.2
Gregory, B.W.3
-
18
-
-
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 et al., 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.
-
(2002)
Bioinformatics
, vol.18
, pp. 395-404
-
-
Ball, G.1
Mian, S.2
Holding, F.3
-
19
-
-
0141738784
-
Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data
-
Wu B, Abbott T, Fishman D et al., Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data, Bioinformatics 19:1636-1643, 2003.
-
(2003)
Bioinformatics
, vol.19
, pp. 1636-1643
-
-
Wu, B.1
Abbott, T.2
Fishman, D.3
-
20
-
-
0033636139
-
Support vector machine classification and validation of cancer tissue samples using microarray expression data
-
Furey TS, Cristianini N, Duffy N et al., Support vector machine classification and validation of cancer tissue samples using microarray expression data, Bioinformatics 16:906-914, 2000.
-
(2000)
Bioinformatics
, vol.16
, pp. 906-914
-
-
Furey, T.S.1
Cristianini, N.2
Duffy, N.3
-
22
-
-
0035224384
-
Feature selection for DNA methylation based cancer classification
-
Model F, Adorjan P, Olek A et al., Feature selection for DNA methylation based cancer classification, Bioinformatics 17:S157-S164, 2001.
-
(2001)
Bioinformatics
, vol.17
-
-
Model, F.1
Adorjan, P.2
Olek, A.3
-
23
-
-
0036161259
-
Gene selection for cancer classification using support vector machines
-
Guyon I, Weston J, Barnhill S et al., Gene selection for cancer classification using support vector machines, Machine Learning 46:389-422, 2002.
-
(2002)
Machine Learning
, vol.46
, pp. 389-422
-
-
Guyon, I.1
Weston, J.2
Barnhill, S.3
-
24
-
-
45749090298
-
SVM-RFE peak selection for cancer classification with mass spectrometry data
-
Duan K, Rajapakse JC, SVM-RFE peak selection for cancer classification with mass spectrometry data, Proc 3rd Asia-Pacific Bioinf Conf, pp. 191-200, 2005.
-
(2005)
Proc 3rd Asia-Pacific Bioinf Conf
, pp. 191-200
-
-
Duan, K.1
Rajapakse, J.C.2
-
27
-
-
24744455665
-
Automatic quality assessment of peptide tandem mass spectra
-
Bern M, Goldberg D, McDonald WH et al., Automatic quality assessment of peptide tandem mass spectra, Bioinformatics 20:i49-i54, 2004.
-
(2004)
Bioinformatics
, vol.20
-
-
Bern, M.1
Goldberg, D.2
McDonald, W.H.3
-
28
-
-
27144489164
-
A Tutorial on support vector Machines for pattern recognition
-
Burges CJC, A Tutorial on support vector Machines for pattern recognition, Data Mining Knowledge Discov 2:121-167, 1998.
-
(1998)
Data Mining Knowledge Discov
, vol.2
, pp. 121-167
-
-
Burges, C.J.C.1
-
29
-
-
0345166891
-
Detection of cancer-specific markers amid massive mass spectral data
-
Zhu W, Wang X, Ma Y et al., Detection of cancer-specific markers amid massive mass spectral data, Proc Nat Acad Sci 100:14666-14671, 2003.
-
(2003)
Proc Nat Acad Sci
, vol.100
, pp. 14666-14671
-
-
Zhu, W.1
Wang, X.2
Ma, Y.3
-
30
-
-
0000959484
-
CLIFF: Clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts
-
Xing EP, Karp RM, CLIFF: Clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts, Bioinformatics 17:S306-S315, 2001.
-
(2001)
Bioinformatics
, vol.17
-
-
Xing, E.P.1
Karp, R.M.2
-
31
-
-
0002593344
-
Multi-interval discretization of continuous-valued attributes for classification learning
-
Fayyad U, Irani K, Multi-interval discretization of continuous-valued attributes for classification learning, Proc 13th Intl Joint Conf Artif Intell, pp. 1022-1029, 1993.
-
(1993)
Proc 13th Intl Joint Conf Artif Intell
, pp. 1022-1029
-
-
Fayyad, U.1
Irani, K.2
-
32
-
-
0002714543
-
Making Large-Scale SVM Learning Practical
-
in: Schölkopf B, Burges C, Smola A (eds.), MIT-Press
-
Joachims T, Making Large-Scale SVM Learning Practical, in: Schölkopf B, Burges C, Smola A (eds.), Advances in Kernel Methods - Support Vector Learning, MIT-Press, 1999.
-
(1999)
Advances in Kernel Methods - Support Vector Learning
-
-
Joachims, T.1
-
36
-
-
0003957032
-
-
2nd ed., Morgan Kaufmann, San Francisco
-
Witten IH, Frank E, Data Mining: Practical Machine Learning Tools and Techniques, 2nd ed., Morgan Kaufmann, San Francisco, 2005.
-
(2005)
Data Mining: Practical Machine Learning Tools and Techniques
-
-
Witten, I.H.1
Frank, E.2
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