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Abstract SpaceEfficient Parallel Algorithms for the Constrained Multiple Sequence Alignment Problem
"... Given sequences S1,S2,...Sn, and a pattern string P the constrained multiple sequence alignment problem (CMSA) is to align similar subsequences of these sequences with the constraint that the alignment “contains” P. The CMSA problem can be considered as an optimal path search problem in the dynamic ..."
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Given sequences S1,S2,...Sn, and a pattern string P the constrained multiple sequence alignment problem (CMSA) is to align similar subsequences of these sequences with the constraint that the alignment “contains” P. The CMSA problem can be considered as an optimal path search problem in the dynamic
Parallel Threesequence Alignment with Spaceefficient
"... The sequence alignment is a fundamental problem in computational biology. Many sequence alignment methods have been proposed, such as pairwise sequence alignment, multiple sequence alignment (MSA), syntenic alignment, constraint multiple sequence alignment, and etc. Among them, pairwise sequence a ..."
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are the lengths of the sequences to be aligned. The complexities of threesequence alignment limit its applicability. Hence, to reduce the complexities becomes an important issue. In this paper, we propose a parallel algorithm to solve this problem. Our parallel algorithm requires O((mn)/p) space complexity and O
Support vector machine learning for interdependent and structured output spaces
 In ICML
, 2004
"... Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernelbased methods has focused on designing flexible and powerful input representations. This paper addresses the complementary issue of problems involving complex outputs suchas multiple depe ..."
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Cited by 447 (20 self)
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dependent output variables and structured output spaces. We propose to generalize multiclass Support Vector Machine learning in a formulation that involves features extracted jointly from inputs and outputs. The resulting optimization problem is solved efficiently by a cutting plane algorithm that exploits
A spaceefficient algorithm for the constrained pairwise sequence alignment problem, Genome Iformatics
"... The constrained pairwise sequence alignment (CP SA) problem aims to align two given sequences by aligning their similar subsequences in the same region under the guidance of a given pattern (constraint). Let the lengths of the sequences be m, and n where n ≤ m, and let r ≤ n be the length of the giv ..."
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Cited by 3 (0 self)
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. This algorithm is not only space efficient but also very fast. A generalization of the CP SA problem for multiple sequences is called the constrained multiple sequence alignment (CMSA) problem. Our CP SA algorithm also improves the space requirement of progressive CMSA algorithms that use solutions of CP SA
Fast and spaceefficient entity . . .
, 2015
"... Entity linking deals with identifying entities from a knowledge base in a given piece of text and has become a fundamental building block for web search engines, enabling numerous downstream improvements from better document ranking to enhanced search results pages. A key problem in the context of w ..."
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to entities in a knowledge base. There are three key ingredients that make the algorithm fast and spaceefficient. First, the linking process ignores any dependencies between the different entity candidates, which allows for a O(k2) implementation in the number of query terms. Second, we leverage hashing
Algorithms on Constrained Sequence Alignment
, 2004
"... One of the fundamental issues that arises in computational biology is Multiple Sequence Alignment (MSA), which needs to be addressed in many applications of Bioinformatics (e.g. study of the SARS Coronavirus and the Human Genome Project). Many algorithms have been proposed to solve the MSA problem, ..."
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One of the fundamental issues that arises in computational biology is Multiple Sequence Alignment (MSA), which needs to be addressed in many applications of Bioinformatics (e.g. study of the SARS Coronavirus and the Human Genome Project). Many algorithms have been proposed to solve the MSA problem
A * Algorithms for the Constrained Multiple Sequence Alignment Problem
"... It is well known that A ∗ algorithm reduces the search space in many applications. For shortest path computations, the algorithm uses a heuristic estimator which can better guide the search to the destination. It allocates memory dynamically to store only the necessary vertices, which are those vert ..."
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vertices in its open list and close list. Therefore, an A ∗ algorithm for the shortest paths search problem is much more space efficient than ordinary search algorithm such as the dynamic programming algorithm and the Dijkstra algorithm. The constrained multiple sequence alignment problem (CMSA) aims
Spaceefficient Local Computation Algorithms
"... Recently Rubinfeld et al. (ICS 2011, pp. 223–238) proposed a new model of sublinear algorithms called local computation algorithms. In this model, a computation problem F may have more than one legal solution and each of them consists of many bits. The local computation algorithm for F should answer ..."
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Cited by 4 (2 self)
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under certain conditions can be applied to construct local computation algorithms that run not only in polylogarithmic time but also in polylogarithmic space. Moreover, these local computation algorithms are easily parallelizable and can answer all parallel queries consistently. Our main technical tools
FastPCMSA: An Improved Parallel Algorithm for the Constrained Multiple Sequence Alignment Problem
"... The constrained multiple sequence alignment (CMSA) problem is to align given sequences S1,S2,...,Sn to maximize a similarity score with the constraint that P is “contained ” in the resulting alignment. The CMSA problem can be considered as a constrained path search problem in the dynamic programming ..."
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The constrained multiple sequence alignment (CMSA) problem is to align given sequences S1,S2,...,Sn to maximize a similarity score with the constraint that P is “contained ” in the resulting alignment. The CMSA problem can be considered as a constrained path search problem in the dynamic
Results 1  10
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