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» Analysis of variance components in gene expression data
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ICPR
2004
IEEE
15 years 10 months ago
Classification Probability Analysis of Principal Component Null Space Analysis
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...
Namrata Vaswani, Rama Chellappa
BMCBI
2010
165views more  BMCBI 2010»
14 years 9 months ago
Bayesian integrated modeling of expression data: a case study on RhoG
Background: DNA microarrays provide an efficient method for measuring activity of genes in parallel and even covering all the known transcripts of an organism on a single array. T...
Rashi Gupta, Dario Greco, Petri Auvinen, Elja Arja...
BMCBI
2006
118views more  BMCBI 2006»
14 years 9 months ago
Gene Expression Profiles Distinguish the Carcinogenic Effects of Aristolochic Acid in Target (Kidney) and Non-target (Liver) Tis
Background: Aristolochic acid (AA) is the active component of herbal drugs derived from Aristolochia species that have been used for medicinal purposes since antiquity. AA, howeve...
Tao Chen, Lei Guo, Lu Zhang 0013, Leming M. Shi, H...
71
Voted
IDA
2002
Springer
14 years 9 months ago
A framework for modelling virus gene expression data
Short, high-dimensional, Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would b...
Paul Kellam, Xiaohui Liu, Nigel J. Martin, Christi...
82
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BMCBI
2008
95views more  BMCBI 2008»
14 years 9 months ago
Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method
Background: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but ...
Joseph W. Foley, Fumiaki Katagiri