Titlebook: Comparative Gene Finding; Models, Algorithms a Marina Axelson-Fisk Book 2015Latest edition Springer-Verlag London 2015 Algorithms.Bioinform

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書目名稱Comparative Gene Finding影響因子(影響力)




書目名稱Comparative Gene Finding影響因子(影響力)學(xué)科排名




書目名稱Comparative Gene Finding網(wǎng)絡(luò)公開度




書目名稱Comparative Gene Finding網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Comparative Gene Finding被引頻次




書目名稱Comparative Gene Finding被引頻次學(xué)科排名




書目名稱Comparative Gene Finding年度引用




書目名稱Comparative Gene Finding年度引用學(xué)科排名




書目名稱Comparative Gene Finding讀者反饋




書目名稱Comparative Gene Finding讀者反饋學(xué)科排名

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disciplined

Lqg design of ship steering control systems,ibutions, sequence compositional measures, and splice site detection models. Each section details a number of the most commonly used algorithms for the characteristic in question. In particular, the splice site section includes various Markovian models, neural networks, linear discriminant analysis, Bayesian networks, and support vector machines.

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gruelling

Sequence Alignment,lexity. As a result, a flora of heuristic alignment algorithms have evolved. In the second part of the chapter, we give an account of the most common of these models, including progressive alignments, iterative methods, hidden Markov models, genetic algorithms, simulated annealing, and alignment profiles.

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conifer

Gene Structure Submodels,of a candidate exon or intron. In this chapter we describe some of the main submodels used in gene finding algorithms, and detail a number of different methods for integrating the sensors the submodels incorporate.