By Jake Y. Chen, Stefano Lonardi

ISBN-10: 1420086847

ISBN-13: 9781420086843

Like a data-guzzling faster engine, complicated facts mining has been powering post-genome organic reviews for 2 many years. Reflecting this progress, organic info Mining provides finished facts mining thoughts, theories, and purposes in present organic and scientific learn. each one bankruptcy is written through a exceptional group of interdisciplinary information mining researchers who conceal state of the art organic topics.

The first part of the ebook discusses demanding situations and possibilities in examining and mining organic sequences and buildings to achieve perception into molecular services. the second one part addresses rising computational demanding situations in analyzing high-throughput Omics facts. The booklet then describes the relationships among information mining and comparable components of computing, together with wisdom illustration, info retrieval, and knowledge integration for based and unstructured organic facts. The final half explores rising information mining possibilities for biomedical applications.

This quantity examines the thoughts, difficulties, development, and developments in constructing and utilizing new facts mining ideas to the swiftly turning out to be box of genome biology. via learning the options and case reviews awarded, readers will achieve major perception and enhance useful suggestions for related organic facts mining initiatives sooner or later.

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Sample text

5 Benchmark applications . . . . . . . . . . . . . . . . . . . . 4 Statistical Analysis of Triplets and Quartets of Secondary Structure Element (SSE) . . . . . . . . . . . . . . . . . . . . . . . 1 Methodology for the analysis of angular patterns . . . . . . . 2 Results of the statistical analysis . . . . . . . . . . . . . . . 3 Selection of subsets containing secondary structure element (SSE) in close contact . . . . . . . . .

4 Building the hash table . . . . . . . . . . . . . . . . . . . . 3 The Use of Geometric Invariants for Three-Dimensional (3D) Structures Comparison . . . . . . . . . . . . . . . . . . . . . . . . 1 Retrieving similarity from the table . . . . . . . . . . . . . . 2 Pair-wise alignment of secondary structures . . . . . . . . . 3 Ranking candidate proteins . . . . . . . . . . . . . . . . . . 4 Atomic superposition .

The structure of sperm whale Met-myoglobin (ODB:ID 1L2K) is shown has: (a) all atoms represented as spheres; (b) Cα atoms chain trace; (c) ribbon diagram. Helical ribbons represent α-helices; (d) helices are substituted by segments, each of them corresponding to the axis of the helix. To further simplify the representation, connections among SSEs have been neglected. similarities, a simplified representation is desirable and necessary. One of the reasons is that amino acids side chains differ in similar proteins; moreover, the protein fold is defined by the torsion angles of the polypeptide main chain, making side chains useless.

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Biological Data Mining by Jake Y. Chen, Stefano Lonardi


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