Titlebook: Health Web Science; Social Media Data fo Kerstin Denecke Book 2015 Springer International Publishing Switzerland 2015 Data Integration.Heal

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Mucosa

Kerstin Deneckeo far, this model only supported comparisons between genomes with the same gene content. We seek to generalize it, allowing for genomes with different gene content. In this paper, we approach such generalization from two different angles, both using the same representation of genomes, and leading to

Tailor

Kerstin Deneckehm was introduced to partition dual graphs into maximal topological components called blocks and determine whether each block contains a pseudoknot or not. This characterization allowed us to efficiently isolate smaller RNA fragments and classify them as pseudoknotted or pseudoknot-free regions, whi

forecast

Kerstin Deneckefe might be achievable. Yet, the most accurate methods for estimating phylogenies are heuristics for NP-hard optimization problems, many of which are too computationally intensive to use on large datasets. Divide-and-conquer approaches have been proposed to address scalability to large datasets that

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es, or allelic variations amongst highly conserved housekeeping genes used for strain typing, etc. The typical application of such a database includes the alignment of contigs to pHMM hoping that the sequence of gene of interest is located within the single contig. Such a condition is often violated

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resuscitation

大喘气

Kerstin Denecke in June 2018.. The 11 full papers presented together with 1 invited paper were carefully reviewed and selected from 20 submissions. They are organized in the following topical sections: Phylogenetics, Sequence Rearrangement and Analysis, Systems Biology and Other Biological Processes. 

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和平主义者

odel seeks to explain incongruence between gene trees and species trees by postulating gene duplication, gene loss, and deep coalescence events. While efficient algorithms exist for inferring optimal DLC reconciliations, they assume that only one individual is sampled per species. In recent work, we