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» A DIAMOND Method for Classifying Biological Data
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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 7 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
BMCBI
2007
140views more  BMCBI 2007»
13 years 7 months ago
Evaluation of high-throughput functional categorization of human disease genes
Background: Biological data that are well-organized by an ontology, such as Gene Ontology, enables high-throughput availability of the semantic web. It can also be used to facilit...
James L. Chen, Yang Liu, Lee T. Sam, Jianrong Li, ...
BMCBI
2002
147views more  BMCBI 2002»
13 years 7 months ago
Expression profiling of human renal carcinomas with functional taxonomic analysis
Background: Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies...
Michael A. Gieseg, Theresa Cody, Michael Z. Man, S...
ALT
2008
Springer
14 years 4 months ago
Computational Models of Neural Representations in the Human Brain
Abstract For many centuries scientists have wondered how the human brain represents thoughts in terms of the underlying biology of neural activity. Philosophers, linguists, cogniti...
Tom M. Mitchell
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
14 years 8 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...