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One way to visualize the similarity between two protein or nucleic acid sequences is to use a similarity matrix, known as a dot plot. These were introduced by Gibbs and McIntyre in 1970 [1] and are two-dimensional matrices that have the sequences of the proteins being compared along the vertical and horizontal axes.
The concept of gene co-expression networks was first introduced by Butte and Kohane in 1999 as relevance networks. [6] They gathered the measurement data of medical laboratory tests (e.g. hemoglobin level ) for a number of patients and they calculated the Pearson correlation between the results for each pair of tests and the pairs of tests which showed a correlation higher than a certain level ...
Here two different gap penalties are applied for opening a gap and for extending a gap. Typically the former is much larger than the latter, e.g. -10 for gap open and -2 for gap extension. This results in fewer gaps in an alignment and residues and gaps are kept together, traits more representative of biological sequences.
In the context of gene finding, the start-stop definition of an ORF therefore only applies to spliced mRNAs, not genomic DNA, since introns may contain stop codons and/or cause shifts between reading frames. An alternative definition says that an ORF is a sequence that has a length divisible by three and is bounded by stop codons.
Stage 2 builds a splice graph representation of a gene, by connecting the exons (vertices) via introns (edges) extracted from spliced read alignments. Stage 3 selects a subset of the candidate transcripts encoded in the graph that can explain all the reads, using either a parsimonius (SET_COVER) or a dynamic programming optimization approach.
The plot visualizes the differences between measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scales, then plotting these values. Though originally applied in the context of two channel DNA microarray gene expression data, MA plots are also used to visualise high-throughput sequencing analysis.
Ab Initio gene prediction is an intrinsic method based on gene content and signal detection. Because of the inherent expense and difficulty in obtaining extrinsic evidence for many genes, it is also necessary to resort to ab initio gene finding, in which the genomic DNA sequence alone is systematically searched for certain tell-tale signs of protein-coding genes.
GeneNetwork is a combined database and open-source bioinformatics data analysis software resource for systems genetics. [1] This resource is used to study gene regulatory networks that link DNA sequence differences to corresponding differences in gene and protein expression and to variation in traits such as health and disease risk.