Titlebook: Algorithms in Bioinformatics; 11th International W Teresa M. Przytycka,Marie-France Sagot Conference proceedings 2011 Springer-Verlag GmbH

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https://doi.org/10.1007/978-3-658-03646-1e them. The maximum likelihood estimation of frequencies of the sequences based on observed reads can be efficiently performed using expectation-maximization (EM) method assuming that we know sequences present in the sample. Frequently, such knowledge is incomplete, e.g., in RNA-seq not all isoforms

漂亮才会豪华

thalamus

Kölner Beiträge zur Didaktik der Mathematikline of research which attempts to adjust to each given set of input sequences a distance function which maximizes the expected accuracy of the reconstructed tree. We demonstrate both analytically and experimentally that by deliberately assuming an oversimplified evolutionary model, it is possible to increase the accuracy of reconstruction.

朝圣者

难理解

sperse

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/153262.jpg

Instrumental

Stochastic Errors vs. Modeling Errors in Distance Based Phylogenetic Reconstructions,line of research which attempts to adjust to each given set of input sequences a distance function which maximizes the expected accuracy of the reconstructed tree. We demonstrate both analytically and experimentally that by deliberately assuming an oversimplified evolutionary model, it is possible to increase the accuracy of reconstruction.

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Using Dominances for Solving the Protein Family Identification Problem,minance and propose a novel combined approach based on Distance Alignment Search Tool (DAST), which contains an exact algorithm with bounds. Our experiments show that this method successfully finds the most similar proteins in a set without solving all instances.

泥土谦卑

Conference proceedings 2011many, in September 2011. The 30 papers presented were carefully reviewed and selected from 77 submissions. They cover aspects of algorithms in bioinformatics, computational biology and systems biology.

含铁

A Mathematical Programming Approach to Marker-Assisted Gene Pyramiding,e present a mixed integer programming formulation that exploits the intrinsic combinatorial structure of the problem. We are able to solve a real-world instance to provable optimality in less than 2 seconds, which was not possible with earlier methods.