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» Modeling Microarray Data: Interpreting and communicating the...
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BMCBI
2010
113views more  BMCBI 2010»
13 years 6 months ago
Probabilistic Principal Component Analysis for Metabolomic Data
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
Gift Nyamundanda, Lorraine Brennan, Isobel Claire ...
BMCBI
2010
240views more  BMCBI 2010»
13 years 6 months ago
TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs
Background: MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challe...
Ming Lu, Bing Shi, Juan Wang, Qun Cao, Qinghua Cui
BMCBI
2005
116views more  BMCBI 2005»
13 years 6 months ago
Which gene did you mean?
Computational Biology needs computer-readable information records. Increasingly, meta-analysed and pre-digested information is being used in the follow up of high throughput exper...
Barend Mons
BMCBI
2010
132views more  BMCBI 2010»
13 years 6 months ago
Next generation tools for genomic data generation, distribution, and visualization
Background: With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the ...
David A. Nix, Tonya L. Di Sera, Brian K. Dalley, B...
BIOINFORMATICS
2004
119views more  BIOINFORMATICS 2004»
13 years 6 months ago
Analysis of variance components in gene expression data
Motivation: A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and t...
James J. Chen, Robert R. Delongchamp, Chen-An Tsai...