Parameterized String Matching Algorithms with Application to Molecular Biology

In the molecular biology, it is said that two biological sequences tend to have similar properties if they have similar 3-D structures. Hence, it is very important to find not only similar sequences in the string sense, but also structurally similar squences from the database. Parameterized string matchin has been used to find structurally similar sequences from the database. In the parameterized string matching problem, a given pattern P is said to match with a sub-string t of the text T, if there exist a bijection from the symbols of P to the symbols of t. Salmela and Tarhio solve the parameterized string matching problem in sub-linear time by applying the concept of q-gram in the Horspool algorithm (FPBMH). In this paper, we extend the Boyer Moore type algorithms: Smith, Raita and Quick Search, to solve the same problem by using the q-gram. We compare the performance of: FPBMH, Smith, Raita, and Quick search algorithms on DNA alphabet and found that Smith algorithm perform better than FPBMH algorithm

パターン照合問題に対する高速なアルゴリズム

Tohoku University篠原歩課

Approximate string matching with reduced alphabet

Peer reviewe

An overview of selected information storage and retrieval issues in computerized document processing

The rapid development of computerized information storage and retrieval techniques has introduced the possibility of extending the word processing concept to document processing. A major advantage of computerized document processing is the relief of the tedious task of manual editing and composition usually encountered by traditional publishers through the immense speed and storage capacity of computers. Furthermore, computerized document processing provides an author with centralized control, the lack of which is a handicap of the traditional publishing operation. A survey of some computerized document processing techniques is presented with emphasis on related information storage and retrieval issues. String matching algorithms are considered central to document information storage and retrieval and are also discussed

Improved algorithms for string searching problems

We present improved practically efficient algorithms for several string searching problems, where we search for a short string called the pattern in a longer string called the text. We are mainly interested in the online problem, where the text is not preprocessed, but we also present a light indexing approach to speed up exact searching of a single pattern. The new algorithms can be applied e.g. to many problems in bioinformatics and other content scanning and filtering problems. In addition to exact string matching, we develop algorithms for several other variations of the string matching problem. We study algorithms for approximate string matching, where a limited number of errors is allowed in the occurrences of the pattern, and parameterized string matching, where a substring of the text matches the pattern if the characters of the substring can be renamed in such a way that the renamed substring matches the pattern exactly. We also consider searching multiple patterns simultaneously and searching weighted patterns, where the weight of a character at a given position reflects the probability of that character occurring at that position. Many of the new algorithms use the backward matching principle, where the characters of the text that are aligned with the pattern are read backward, i.e. from right to left. Another common characteristic of the new algorithms is the use of q-grams, i.e. q consecutive characters are handled as a single character. Many of the new algorithms are bit parallel, i.e. they pack several variables to a single computer word and update all these variables with a single instruction. We show that the q-gram backward string matching algorithms that solve the exact, approximate, or multiple string matching problems are optimal on average. We also show that the q-gram backward string matching algorithm for the parameterized string matching problem is sublinear on average for a class of moderately repetitive patterns. All the presented algorithms are also shown to be fast in practice when compared to earlier algorithms. We also propose an alphabet sampling technique to speed up exact string matching. We choose a subset of the alphabet and select the corresponding subsequence of the text. String matching is then performed on this reduced subsequence and the found matches are verified in the original text. We show how to choose the sampled alphabet optimally and show that the technique speeds up string matching especially for moderate to long patterns

Measuring the Propagation of Information in Partial Evaluation

We present the first measurement-based analysis of the information propagated by a partial evaluator. Our analysis is based on measuring implementations of string-matching algorithms, based on the observation that the sequence of character comparisons accurately reflects maintained information. Notably, we can easily prove matchers to be different and we show that they display more variety and finesse than previously believed. As a consequence, we are able to pinpoint differences and inaccuracies in many results previously considered equivalent. Our analysis includes a framework that lets us obtain string matchers - notably the family of Boyer-Moore algorithms - in a systematic formalism-independent way from a few information-propagation primitives. By leveraging the existing research in string matching, we show that the landscape of information propagation is non-trivial in the sense that small changes in information propagation may dramatically change the properties of the resulting string matchers. We thus expect that this work will prove useful as a test and feedback mechanism for information propagation in the development of advanced program transformations, such as GPC or Supercompilation

Order-Preserving Pattern Matching Indeterminate Strings

Given an indeterminate string pattern p and an indeterminate string text t, the problem of order-preserving pattern matching with character uncertainties (muOPPM) is to find all substrings of t that satisfy one of the possible orderings defined by p. When the text and pattern are determinate strings, we are in the presence of the well-studied exact order-preserving pattern matching (OPPM) problem with diverse applications on time series analysis. Despite its relevance, the exact OPPM problem suffers from two major drawbacks: 1) the inability to deal with indetermination in the text, thus preventing the analysis of noisy time series; and 2) the inability to deal with indetermination in the pattern, thus imposing the strict satisfaction of the orders among all pattern positions. In this paper, we provide the first polynomial algorithms to answer the muOPPM problem when: 1) indetermination is observed on the pattern or text; and 2) indetermination is observed on both the pattern and the text and given by uncertainties between pairs of characters. First, given two strings with the same length m and O(r) uncertain characters per string position, we show that the muOPPM problem can be solved in O(mr lg r) time when one string is indeterminate and r in N^+ and in O(m^2) time when both strings are indeterminate and r=2. Second, given an indeterminate text string of length n, we show that muOPPM can be efficiently solved in polynomial time and linear space