By Matthias Bernt, Kun-Mao Chao, Jyun-Wei Kao (auth.), Ben Raphael, Jijun Tang (eds.)

This publication constitutes the refereed complaints of the twelfth overseas Workshop on Algorithms in Bioinformatics, WABI 2012, held in Ljubljana, Slovenia, in September 2012. WABI 2012 is one among six workshops which, besides the ecu Symposium on Algorithms (ESA), represent the ALGO annual assembly and makes a speciality of algorithmic advances in bioinformatics, computational biology, and structures biology with a specific emphasis on discrete algorithms and machine-learning equipment that tackle vital difficulties in molecular biology. The 35 complete papers provided have been rigorously reviewed and chosen from ninety two submissions. The papers contain algorithms for various organic difficulties together with phylogeny, DNA and RNA sequencing and research, protein constitution, and others.

**Read or Download Algorithms in Bioinformatics: 12th International Workshop, WABI 2012, Ljubljana, Slovenia, September 10-12, 2012. Proceedings PDF**

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**Additional resources for Algorithms in Bioinformatics: 12th International Workshop, WABI 2012, Ljubljana, Slovenia, September 10-12, 2012. Proceedings**

**Example text**

From (3) we see that the expected value of the MPD is independent of the size of R, which is an interesting, yet not surprising, result by itself. However, as we show later on in this paper, this is not the case for the standard deviation of the MPD. The Standard Deviation of the MPD. Before describing how we can compute analytically the standard deviation of the MPD on a given tree T and for a given sample size, we introduce a few quantities that relate to groups of paths on T . Our goal is to simplify the computation of the standard deviation of the MPD by expressing the standard deviation in terms of these quantities.

3 Experimental Results We have implemented all the algorithms that we present in Section 2 and we conducted experiments in order to assess their eﬃciency. The implementation was done in C++, using template programming that allows us to use number types of diﬀerent precision. All the experiments that appear in the current version of the paper were executed using the double built-in C++ type. 67 GHz processor. The main memory of this computer is 4 Gigabytes. The trees that we used in the experiments are subtrees of varying size that we extracted from a phylogenetic tree data set that contains 4510 tips and which represents the phylogenetic relations between all mammals [1].

Otherwise, it returns true with high probability. Proof. Let T (a) and T (x) be the subtrees that contain a and x, respectively. Sequences a and b are independent and lie on the opposite sides of some edge e. If x and y join the tree at e, we have M E(xy|ab) = M E(xy|ai bj ) for any choice of i and j. If x, y, a, b are independent, all middle edge estimates are within Δ/2 of each other and correct within Δ/2. Suppose some two of these sequences are not independent (say a and x). Without loss of generality, T (x) joins T (a) at some edge in subtree of T (a) consisting of all nodes from which we reconstruct the sequence at a.