14 research outputs found

    A basic analysis toolkit for biological sequences

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    This paper presents a software library, nicknamed BATS, for some basic sequence analysis tasks. Namely, local alignments, via approximate string matching, and global alignments, via longest common subsequence and alignments with affine and concave gap cost functions. Moreover, it also supports filtering operations to select strings from a set and establish their statistical significance, via z-score computation. None of the algorithms is new, but although they are generally regarded as fundamental for sequence analysis, they have not been implemented in a single and consistent software package, as we do here. Therefore, our main contribution is to fill this gap between algorithmic theory and practice by providing an extensible and easy to use software library that includes algorithms for the mentioned string matching and alignment problems. The library consists of C/C++ library functions as well as Perl library functions. It can be interfaced with Bioperl and can also be used as a stand-alone system with a GUI. The software is available at under the GNU GPL

    Subsequences and Supersequences of Strings

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    Stringology - the study of strings - is a branch of algorithmics which been the sub-ject of mounting interest in recent years. Very recently, two books [M. Crochemore and W. Rytter, Text Algorithms, Oxford University Press, 1995] and [G. Stephen, String Searching Algorithms, World Scientific, 1994] have been published on the subject and at least two others are known to be in preparation. Problems on strings arise in information retrieval, version control, automatic spelling correction, and many other domains. However the greatest motivation for recent work in stringology has come from the field of molecular biology. String problems occur, for example, in genetic sequence construction, genetic sequence comparison, and phylogenetic tree construction. In this thesis we study a variety of string problems from a theoretical perspective. In particular, we focus on problems involving subsequences and supersequences of strings

    Speeding-up hirschberg and hunt-szymanski LCS algorithms

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    Speeding-up Hirschberg and Hunt-Szymanski LCS Algorithms

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    Two algorithms are presented that solve the problem of recovering the longest common subsequence of two strings. The first algorithm is an improvement of Hirschberg’s divide-and-conquer algorithm. The second algorithm is an improvement of Hunt-Szymanski algorithm based on an efficient computation of all dominant match points. These two algorithms use bit-vector operations and are shown to work very efficiently in practice
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