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By Adrian-Horia Dediu, Carlos Martín-Vide, Bianca Truthe (eds.)

This booklet constitutes the refereed complaints of the 1st foreign convention, AlCoB 2014, held in July 2014 in Tarragona, Spain.

The 20 revised complete papers have been rigorously reviewed and chosen from 39 submissions. The scope of AlCoB contains themes of both theoretical or utilized curiosity, particularly: detailed series research, approximate series research, pairwise series alignment, a number of series alignment, series meeting, genome rearrangement, regulatory motif discovering, phylogeny reconstruction, phylogeny comparability, constitution prediction, proteomics: molecular pathways, interplay networks, transcriptomics: splicing variations, isoform inference and quantification, differential research, next-generation sequencing: inhabitants genomics, metagenomics, metatranscriptomics, microbiome research, platforms biology.

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Additional resources for Algorithms for Computational Biology: First International Conference, AlCoB 2014, Tarragona, Spain, July 1-3, 2014, Proceedigns

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N} the set of genes and by T the finite set of time steps. The set T contains all but the last time step of T . Then xt+1,i = ai,j xt,j , ∀ i ∈ G, t ∈ T , (1) j∈G where xt = (xt,1 , xt,2 , . . , xt,n ) ∈ Rn is a vector with the expression level of the genes in G at time step t. Here, A = (ai,j ) ∈ Rn×n is a matrix, where the influence coefficient ai,j represents the ability of gene j to regulate gene i. To solve such models, linear regression has frequently been used, see for example Zhang et al.

AlCoB 2014, LNBI 8542, pp. 25–34, 2014. c Springer International Publishing Switzerland 2014 26 E. Althaus, A. K. Hildebrandt mark them as completed, and link them to a common parent. Iterating until only a single cluster remains leads to the complete clustering tree. Please note that in some applications, computing the whole tree is not required. Instead, the user specifies an application-specific threshold on the inter-cluster distances or similarities. The computation is then terminated if no pair of clusters can be found with a similarity higher or a dissimilarity lower than the given threshold.

If two queues that are closed are merged, the resulting queue is marked closed too. Notice that if one of the two queues is closed, we know that only the distances stored in the closed queue are relevant when merging the queue to the other. We can use this information to compute only the relevant distances in the merged queue, but we have not implemented this idea, as we observed that this does not happen too often. Parallelization is done trivially. In the first phase, all priority-queues can be filled in parallel and the workload is nontrivial and approximately the same for each queue.

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