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Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks Javed Khan1,2, Jun S. Wei1, Markus Ringnér1,3, Lao H. Saal1, Marc Ladanyi4, Frank Westermann5 , Frank Berthold6, Manfred Schwab5, Cristina R. Antonescu4, Carsten Peterson3, and Paul S. Meltzer1 |
- Cancer Genetics
Branch, National Human Genome Research Institute, National Institutes
of Health, Bethesda, Maryland, USA
- Pediatric Oncology
Branch, Advanced Technology Center, National Cancer Institute,Gaithersburg,
Maryland, USA
- Complex Systems
Division, Department of Theoretical Physics, Lund University, Lund,
Sweden
- Department of Pathology,
Memorial Sloan-Kettering Cancer Center, New York, New York, USA
- Department of Cytogenetics,
German Cancer Research Center, Heidelberg, Germany
- Department of Pediatrics,
Klinik für Kinderheilkunde der Universität zu Köln, Köln, Germany
J.K., J.S.W. and M.R. contributed equally to this study.
Correspondence should be addressed to J.K. or P.S.M.; email: khanjav@mail.nih.gov or pmeltzer@nhgri.nih.gov
NATURE MEDICINE · VOLUME 7 · NUMBER
6 · JUNE 2001
Supplemental information:
- Supplemental Data:
List of 2308 genes included in data analysis after filtering.
Download tab-delimited text file
- Supplemental Table
A: The results of ANN calibration for training samples. Download
PDF file
- Supplemental Table
B: Known molecular characteristics of all samples. Download
PDF file
- Supplemental
Methods. Download PDF file
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Supplementary information for Javed Khan, et. al, Nature Medicine, 7(6):673-679, 2001. |
The Nature Medicine paper: Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks is available here. |
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