Advances in Genomic Sequence Analysis and Pattern Discovery by Laura Elnitski, Helen Piontkivska, Lonnie R. Welch

By Laura Elnitski, Helen Piontkivska, Lonnie R. Welch

Mapping the genomic landscapes is among the most fun frontiers of technological know-how. now we have the chance to opposite engineer the blueprints and the keep watch over structures of dwelling organisms. Computational instruments are key enablers within the interpreting technique. This ebook offers an in-depth presentation of a few of the real computational biology ways to genomic series research. the 1st component of the booklet discusses tools for locating styles in DNA and RNA. this is often by way of the second one part that displays on equipment in quite a few methods, together with functionality, utilization and paradigms.

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2008) Stability and dynamics of polycomb target sites in Drosophila development. PLoS Genetics 4(9): e1000178. Lawrence CE, Altschul SF, Boguski MS et al. (1993) Detecting subtle sequence signals: A Gibbs sampling strategy for multiple alignment. Science 262: 208–214. Lewis MA, Quint E, Glazier AM et al. (2009) An ENU-induced mutation of miR-96 associated with progressive hearing loss in mice. Nat Genet 41: 614–618. Liu X, Brutlag D, Liu J. (2002) An algorithm for finding protein — DNA binding sites with applications to chromatin-immunoprecipitation microarray experiments.

Schbath and M. Hoebeke alphabet used in the sequence according to a particular format: validchars:interruptchars:jokerchar where • valdichars is the list of allowed characters of the sequence, • interruptchars is the list of characters used to separate pieces in a concatenated sequence, • jokerchar is a single character standing for any of the valid characters. For instance, if a sequence of protein secondary structures is to be analyzed, the alphabet definition could be ABC:X:N, where A could stand for alphahelix, B for beta-sheet, C for coil and X would be used to separate pieces of sequences and N could replace any of A, B or C.

Nguyen TT, Androulakis IP. (2009) Recent advances in the computational discovery of transcription factor binding sites. Algorithms 2: 582–605. Ohler U, Liao G-C, Niemann H, Rubin GM. (2002) Computational analysis of core promoters in the Drosophila genome. Genome Biol 3: RESEARCH0087. Osada R, Zaslavsky E, Singh M. (2004) Comparative analysis of methods for representing and searching for transcription factor binding sites. Bioinformatics 20: 3516–3525. Piipari M, Down TA, Saini H et al. (2010) iMotifs: An integrated sequence motif visualization and analysis environment, Bioinformatics 26(6): 843–844.

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