{"product_id":"9783319879024","title":"Computational Biology","description":"\u003ch1\u003eComputational Biology\u003c\/h1\u003e \u003ch2\u003eDeBlasio, Dan; Kececioglu, John\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis book develops a new approach called \u003ci\u003eparameter advising\u003c\/i\u003e for finding a parameter setting for a sequence aligner that yields a quality alignment of a given set of input sequences. In this framework, a parameter\u003ci\u003e advisor\u003c\/i\u003e is a procedure that automatically chooses a parameter setting for the input, and has two main ingredients:\u003c\/p\u003e    \u003cp\u003e(a)         the \u003ci\u003eset \u003c\/i\u003eof parameter choices considered by the advisor, and\u003c\/p\u003e  \u003cp\u003e(b)         an \u003ci\u003eestimator\u003c\/i\u003e of alignment accuracy used to rank alignments produced by the aligner.\u003c\/p\u003e    \u003cp\u003eOn coupling a parameter advisor with an aligner, once the advisor is trained in a learning phase, the user simply inputs sequences to align, and receives an output alignment from the aligner, where the advisor has automatically selected the parameter setting.\u003c\/p\u003e    \u003cp\u003eThe chapters first lay out the foundations of parameter advising, and then cover applications and extensions of advising. The content\u003c\/p\u003e    \u003cp\u003e•   examines formulations of parameter advising and their \u003ci\u003ecomputational complexity\u003c\/i\u003e,\u003c\/p\u003e  \u003cp\u003e•   develops methods for learning good \u003ci\u003eaccuracy estimators\u003c\/i\u003e,\u003c\/p\u003e  \u003cp\u003e•   presents approximation algorithms for finding good sets of \u003ci\u003eparameter choices\u003c\/i\u003e, and \u003c\/p\u003e  \u003cp\u003e•   assesses \u003ci\u003esoftware implementations\u003c\/i\u003e of advising that perform well on real biological data.\u003c\/p\u003e    \u003cp\u003eAlso explored are applications of parameter advising to\u003c\/p\u003e    \u003cp\u003e•   \u003ci\u003eadaptive local realignment\u003c\/i\u003e, where advising is performed on local regions of the sequences to automatically adapt to varying mutation rates, and\u003c\/p\u003e  \u003cp\u003e•   \u003ci\u003eensemble alignment\u003c\/i\u003e, where advising is applied to an ensemble of aligners to effectively yield a new aligner of higher quality than the individual aligners in the ensemble.\u003c\/p\u003e    \u003cp\u003eThe book concludes by offering future directions in advising research.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2019-06-06\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9783319879024\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-319-64918-4\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 152\u003c\/p\u003e ","brand":"Springer International Publishing","offers":[{"title":"Default Title","offer_id":45227826348172,"sku":"9783319879024","price":49.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783319879024.jpg?v=1776433488","url":"https:\/\/lateknightbooks.com\/products\/9783319879024","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}