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» A DIAMOND Method for Classifying Biological Data
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BMCBI
2006
158views more  BMCBI 2006»
13 years 7 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
BMCBI
2008
106views more  BMCBI 2008»
13 years 7 months ago
Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spect
Background: Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of m...
Wouter Meuleman, Judith Y. M. N. Engwegen, Marie-C...
CEC
2007
IEEE
13 years 11 months ago
Evolving hypernetwork classifiers for microRNA expression profile analysis
Abstract-- High-throughput microarrays inform us on different outlooks of the molecular mechanisms underlying the function of cells and organisms. While computational analysis for ...
Sun Kim, Soo-Jin Kim, Byoung-Tak Zhang
BMCBI
2008
114views more  BMCBI 2008»
13 years 7 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
ICPR
2006
IEEE
14 years 8 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen