Classification of arrayCGH data using fused SVM
نویسندگان
چکیده
منابع مشابه
Classification of arrayCGH data using fused SVM
MOTIVATION Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are starting to be used as markers to improve prognosis or diagnosis of cancer, which implies that methods for automated supervised classification of arrayCGH data are needed. Like gene expression profiles, arrayCGH profil...
متن کاملClassification of arrayCGH data using a fused SVM
Motivation: Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are starting to be used as markers to improve prognosis or diagnosis of cancer, which implies that methods for automated supervised classification of arrayCGH data are needed. Like gene expression profiles, arrayCGH profi...
متن کاملClassification of Stellar Spectral Data Using SVM
In this paper a new technique is developed on stellar spectral classification. Because stellar spectral data sets are usually extremely noisy, wavelet de-noising method is proposed to reduce noise first. Then the support vector machines (SVM) is used for the classification. Experimental results show that in most cases, there will be a better performance using this composite classifier than usin...
متن کاملA Comparative Study of SVM and RF Methods for Classification of Alteration Zones Using Remotely Sensed Data
Identification and mapping of the significant alterations are the main objectives of the exploration geochemical surveys. The field study is time-consuming and costly to produce the classified maps. Therefore, the processing of remotely sensed data, which provide timely and multi-band (multi-layer) data, can be substituted for the field study. In this study, the ASTER imagery is used for altera...
متن کاملSpace Object Classification using Fused Features of Time Series Data
In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results sh...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2008
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btn188