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  2. Dot plot (bioinformatics) - Wikipedia

    en.wikipedia.org/wiki/Dot_plot_(bioinformatics)

    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.

  3. Open reading frame - Wikipedia

    en.wikipedia.org/wiki/Open_reading_frame

    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.

  4. Sequence alignment - Wikipedia

    en.wikipedia.org/wiki/Sequence_alignment

    To construct a dot-matrix plot, the two sequences are written along the top row and leftmost column of a two-dimensional matrix and a dot is placed at any point where the characters in the appropriate columns match—this is a typical recurrence plot. Some implementations vary the size or intensity of the dot depending on the degree of ...

  5. Gene prediction - Wikipedia

    en.wikipedia.org/wiki/Gene_prediction

    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.

  6. List of RNA-Seq bioinformatics tools - Wikipedia

    en.wikipedia.org/wiki/List_of_RNA-Seq...

    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.

  7. Gene co-expression network - Wikipedia

    en.wikipedia.org/wiki/Gene_co-expression_network

    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 ...

  8. Microarray analysis techniques - Wikipedia

    en.wikipedia.org/wiki/Microarray_analysis_techniques

    Example of an approximately 40,000 probe spotted oligo microarray with enlarged inset to show detail. Microarray analysis techniques are used in interpreting the data generated from experiments on DNA (Gene chip analysis), RNA, and protein microarrays, which allow researchers to investigate the expression state of a large number of genes – in many cases, an organism's entire genome – in a ...

  9. MA plot - Wikipedia

    en.wikipedia.org/wiki/MA_plot

    By minimizing these systematic variations, true biological differences can be found. To determine whether normalization is needed, one can plot Cy5 (R) intensities against Cy3 (G) intensities and see whether the slope of the line is around 1. An improved method, which is basically a scaled, 45 degree rotation of the R vs. G plot is an MA-plot. [4]