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Classification of g...
Classification of genomic and proteomic data using support vector machines
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- Johansson, Peter (author)
- Lund University,Lunds universitet,Beräkningsbiologi och biologisk fysik - Genomgår omorganisation,Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation,Naturvetenskapliga fakulteten,Computational Biology and Biological Physics - Undergoing reorganization,Department of Astronomy and Theoretical Physics - Undergoing reorganization,Faculty of Science
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- Ringnér, Markus (author)
- Lund University,Lunds universitet,Beräkningsbiologi och biologisk fysik - Genomgår omorganisation,Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation,Naturvetenskapliga fakulteten,Computational Biology and Biological Physics - Undergoing reorganization,Department of Astronomy and Theoretical Physics - Undergoing reorganization,Faculty of Science
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Berrar, D. P. (editor)
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Dubitzky, W. (editor)
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Granzow, M (editor)
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(creator_code:org_t)
- Boston, MA : Springer US, 2007
- 2007
- English 16 s.
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In: Fundamentals of Data Mining in Genomics and Proteomics. - Boston, MA : Springer US. - 9781402072604 - 9781475778090 - 9780306478154 ; , s. 187-202
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Abstract
Subject headings
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- Supervised learning methods are used when one wants to construct a classifier. To use such a method, one has to know the correct classification of at least some samples, which are used to train the classifier. Once a classifier has been trained it can be used to predict the class of unknown samples. Supervised learning methods have been used numerous times in genomic applications and we will only provide some examples here. Different subtypes of cancers such as leukemia (Golub et al., 1999) and small round blue cell tumors (Khan et al., 2001) have been predicted based on their gene expression profiles obtained with microarrays. Microarray data has also been used in the construction of classifiers for the prediction of outcome of patients, such as whether a breast tumor is likely to give rise to a distant metastasis (van’t Veer et al., 2002) or whether a medulloblastoma patient is likely to have a favorable clinical outcome (Pomeroy et al., 2002). Proteomic patterns in serum have been used to identify ovarian cancer (Petricoin et al., 2002a) and prostate cancer (Adam et al., 2002); (Petricoin et al., 2002b).
Subject headings
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
Publication and Content Type
- kap (subject category)
- ref (subject category)
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