BMCBI
2006
13 years 11 months ago
2006
Background: Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading t...
BMCBI
2006
13 years 11 months ago
2006
Background: Various statistical scores have been proposed for evaluating the significance of genes that may exhibit differential expression between two or more controlled conditio...
BMCBI
2006
13 years 11 months ago
2006
Background: The identification of chromosomal homology will shed light on such mysteries of genome evolution as DNA duplication, rearrangement and loss. Several approaches have be...
BMCBI
2006
13 years 11 months ago
2006
Background: Analysis of genomes evolving via block-interchange events leads to a combinatorial problem of sorting by block-interchanges, which has been studied recently to evaluat...
BMCBI
2006
13 years 11 months ago
2006
Background: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive unde...
BMCBI
2006
13 years 11 months ago
2006
Background: Percentage Identity (PID) is frequently quoted in discussion of sequence alignments since it appears simple and easy to understand. However, although there are several...
BMCBI
2006
13 years 11 months ago
2006
Background: Discovery of precise specificity of transcription factors is an important step on the way to understanding the complex mechanisms of gene regulation in eukaryotes. Rec...
BMCBI
2006
13 years 11 months ago
2006
Background: Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray me...
BMCBI
2006
13 years 11 months ago
2006
Background: Serial Analysis of Gene Expression (SAGE) is a powerful tool to determine gene expression profiles. Two types of SAGE libraries, ShortSAGE and LongSAGE, are classified...
BMCBI
2006
13 years 11 months ago
2006
Background: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the sea...