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BMCBI
2006
151views more  BMCBI 2006»
13 years 4 months ago
Modeling Sage data with a truncated gamma-Poisson model
Background: Serial Analysis of Gene Expressions (SAGE) produces gene expression measurements on a discrete scale, due to the finite number of molecules in the sample. This means t...
Helene H. Thygesen, Aeilko H. Zwinderman
BMCBI
2007
147views more  BMCBI 2007»
13 years 4 months ago
Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
Scott D. Zuyderduyn
ACL
2003
13 years 6 months ago
Parametric Models of Linguistic Count Data
It is well known that occurrence counts of words in documents are often modeled poorly by standard distributions like the binomial or Poisson. Observed counts vary more than simpl...
Martin Jansche
SIGIR
2004
ACM
13 years 10 months ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny
BMCBI
2007
106views more  BMCBI 2007»
13 years 4 months ago
Modeling SAGE tag formation and its effects on data interpretation within a Bayesian framework
Background: Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Stand...
Michael A. Gilchrist, Hong Qin, Russell L. Zaretzk...