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Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

by Stephen F Altschul , Thomas L Madden , Alejandro A Schäffer , Jinghui Zhang , Zheng Zhang , Webb Miller , David J Lipman - Nucleic Acids Res. , 1997
"... ABSTRACT The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantia ..."
Abstract - Cited by 8572 (88 self) - Add to MetaCart
ABSTRACT The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased

Depth first search and linear graph algorithms

by Robert Tarjan - SIAM JOURNAL ON COMPUTING , 1972
"... The value of depth-first search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
Abstract - Cited by 1406 (19 self) - Add to MetaCart
The value of depth-first search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components

A Fast Quantum Mechanical Algorithm for Database Search

by Lov K. Grover - ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING , 1996
"... Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic) will need to look at a minimum of names. Quantum mechanical systems can be in a supe ..."
Abstract - Cited by 1135 (10 self) - Add to MetaCart
Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic) will need to look at a minimum of names. Quantum mechanical systems can be in a

TABU SEARCH

by Fred Glover, Rafael Marti
"... Tabu Search is a metaheuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore the hallm ..."
Abstract - Cited by 822 (48 self) - Add to MetaCart
algorithms based on the tabu search. The experimentation shows that the procedures provide high quality solutions to the training problem, and in addition consume a reasonable computational effort.

An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions

by Sunil Arya, David M. Mount, Nathan S. Netanyahu, Ruth Silverman, Angela Y. Wu - ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS , 1994
"... Consider a set S of n data points in real d-dimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any po ..."
Abstract - Cited by 984 (32 self) - Add to MetaCart
Consider a set S of n data points in real d-dimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any

Adaptive floating search methods in feature selection

by P. Somol , P. Pudil , J. Novovicova , P. Paclik - PATTERN RECOGNITION LETTERS , 1999
"... A new suboptimal search strategy for feature selection is presented. It represents a more sophisticated version of "classical" floating search algorithms (Pudil et al., 1994), attempts to remove some of their potential deficiencies and facilitates finding a solution even closer to the opti ..."
Abstract - Cited by 548 (21 self) - Add to MetaCart
A new suboptimal search strategy for feature selection is presented. It represents a more sophisticated version of "classical" floating search algorithms (Pudil et al., 1994), attempts to remove some of their potential deficiencies and facilitates finding a solution even closer

Pushing the Envelope: Planning, Propositional Logic, and Stochastic Search

by Henry Kautz, Bart Selman , 1996
"... Planning is a notoriously hard combinatorial search problem. In many interesting domains, current planning algorithms fail to scale up gracefully. By combining a general, stochastic search algorithm and appropriate problem encodings based on propositional logic, we are able to solve hard planning pr ..."
Abstract - Cited by 579 (33 self) - Add to MetaCart
Planning is a notoriously hard combinatorial search problem. In many interesting domains, current planning algorithms fail to scale up gracefully. By combining a general, stochastic search algorithm and appropriate problem encodings based on propositional logic, we are able to solve hard planning

An Efficient Boosting Algorithm for Combining Preferences

by Raj Dharmarajan Iyer , Jr. , 1999
"... The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new boosting ..."
Abstract - Cited by 727 (18 self) - Add to MetaCart
The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new

A learning algorithm for Boltzmann machines

by H. Ackley, E. Hinton, J. Sejnowski - Cognitive Science , 1985
"... The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a probl ..."
Abstract - Cited by 584 (13 self) - Add to MetaCart
problem in o very short time. One kind of computation for which massively porollel networks appear to be well suited is large constraint satisfaction searches, but to use the connections efficiently two conditions must be met: First, a search technique that is suitable for parallel networks must be found

Search and replication in unstructured peer-to-peer networks

by Qin Lv, Pei Cao, Edith Cohen, Kai Li, Scott Shenker , 2002
"... Abstract Decentralized and unstructured peer-to-peer networks such as Gnutella are attractive for certain applicationsbecause they require no centralized directories and no precise control over network topologies and data placement. However, the flooding-based query algorithm used in Gnutella does n ..."
Abstract - Cited by 692 (6 self) - Add to MetaCart
Abstract Decentralized and unstructured peer-to-peer networks such as Gnutella are attractive for certain applicationsbecause they require no centralized directories and no precise control over network topologies and data placement. However, the flooding-based query algorithm used in Gnutella does
Results 1 - 10 of 47,122