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Titlebook: Bioinformatics Research and Applications; Fourth International Ion M?ndoiu,Raj Sunderraman,Alexander Zelikovsky Conference proceedings 2008

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樓主: choleric
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發(fā)表于 2025-3-23 13:40:48 | 只看該作者
PFP: A Computational Framework for Phylogenetic Footprinting in Prokaryotic Genomes,ed motifs in the upstream sequences of orthologous genes in eukaryotic genomes. However, this popular strategy may not be directly applicable to prokaryotic genomes, where typically about half of the genes in a genome form multiple-gene transcription units or operons. The promoter sequences for thes
12#
發(fā)表于 2025-3-23 17:26:45 | 只看該作者
Accelerating the Neighbor-Joining Algorithm Using the Adaptive Bucket Data Structure,ly at each iteration. Accelerating the neighbor-joining method requires performing a smarter search for an optimal pair of neighbors, avoiding re-evaluation of all possible pairs of points at each iteration..We developed an acceleration technique for the neighbor-joining method that significantly de
13#
發(fā)表于 2025-3-23 19:57:48 | 只看該作者
14#
發(fā)表于 2025-3-23 23:02:58 | 只看該作者
Physicochemical Correlation between Amino Acid Sites in Short Sequences under Selective Pressure,stitutions which tend to destabilize a particular structure may be compensated by other substitutions which confer stability to that structure. Patterns of coordinated substitutions were studied in two sets of selected peptides. The first is a set of 181 amino acid sequences that were selected . to
15#
發(fā)表于 2025-3-24 06:15:00 | 只看該作者
16#
發(fā)表于 2025-3-24 07:03:10 | 只看該作者
A Dynamic Programming Algorithm for De Novo Peptide Sequencing with Variable Scoring,he output. Candidate peptides can be determined by finding forbidden-pairs paths in a spectrum graph constructed from the mass spectrometer data, assigning scores to vertices and/or edges in order to favor higher-scoring peptides. Chen et al.?gave an algorithm to find the highest-scoring forbidden-p
17#
發(fā)表于 2025-3-24 12:59:58 | 只看該作者
18#
發(fā)表于 2025-3-24 16:06:03 | 只看該作者
Incorporating Literature Knowledge in Bayesian Network for Inferring Gene Networks with Gene Expresed for this problem. The incorporation of various genomic and proteomic data has been shown to enhance the learning ability in the Bayesian Network (BN) approach. However, the knowledge embedded in the large body of published literature has not been utilized in a systematic way. In this work, prior
19#
發(fā)表于 2025-3-24 21:56:27 | 只看該作者
20#
發(fā)表于 2025-3-24 23:18:32 | 只看該作者
0302-9743 , held in Atlanta, GA, USA in May 2008. The 35 revised full papers presented together with 6 workshop papers and 6 invited papers were carefully reviewed and selected from a total of 94 submissions. The papers cover a wide range of topics, including clustering and classification, gene expression ana
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