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Topic: Smith Waterman algorithm

	Smith Waterman algorithm - Wikipedia, the free encyclopedia
		The Smith-Waterman algorithm is a well-known algorithm for performing local sequence alignment; that is, for determining similar regions between two nucleotide or protein sequences.
		As such, it has the desirable property that it is guaranteed to find the optimal local alignment with respect to the scoring system being used (which includes the substitution matrix and the gap-scoring scheme).
		The main difference to the Needleman-Wunsch algorithm is that negative scoring matrix cells are set to zero, which renders the (thus positively scoring) local alignments visible.
	en.wikipedia.org /wiki/Smith-Waterman_algorithm (576 words)

	Needleman-Wunsch algorithm - Wikipedia, the free encyclopedia
		It is commonly used in bioinformatics to align protein or nucleotide sequences.
		The algorithm was proposed in 1970 by Saul Needleman and Christian Wunsch in their paper A general method applicable to the search for similarities in the amino acid sequence of two proteins, J Mol Biol.
		The Needleman-Wunsch algorithm is an example of dynamic programming, and is guaranteed to find the alignment with the maximum score.
	en.wikipedia.org /wiki/Needleman-Wunsch_algorithm (502 words)

	List of algorithms - Wikipedia, the free encyclopedia
		See also the list of data structures, list of algorithm general topics and list of terms relating to algorithms and data structures.
		Buddy memory allocation: Algorithm to allocate memory such that fragmentation is less.
		Alpha max plus beta min algorithm: an approximation of the square-root of the sum of two squares.
	en.wikipedia.org /wiki/List_of_algorithms (1697 words)

	NECSI Community
		Temple Smith is Professor of Biomedical Engineering, Research Professor of Pharmacology, and Director of the Biomolecular Engineering Research Center at Boston University.
		The Smith-Waterman algorithm for DNA or protein sequence matching, is used widely to find sequence matches to trace evolutionary development and functional relationships between biomolecules.
		Smith are used to identify structure, function, and regulation in biomolecules.
	necsi.org /faculty/tsmith.html (212 words)

	[No title] (Site not responding. Last check: 2007-10-30)
		This is usually the most sensitive algorithm as sequences are often only partially alignable.
		Global alignment algorithms report the largest overlapping sequence regions shared by two sequences.
		In unrelated sequences, the algorithm will align the best scoring overlapping end segments (which are normally quite short).
	eta.embl-heidelberg.de:8000 /misc/algorithm.html (594 words)

	M. Waterman, USC MCB (Site not responding. Last check: 2007-10-30)
		Genomics (1992) Churchill, G. and Waterman, M.S. The accuracy of DNA sequences: estimating sequence quality.
		Genomics (1988) Lauder, E.S. and Waterman, M.S. Genomic mapping by fingerprinting random clones: a mathematical analysis.
		J. Molecular Biology (1981) Smith, T.F. and Waterman, M.S. The identification of common molecular subsequences.
	www.usc.edu /dept/LAS/biosci/faculty/waterman.html (292 words)

	JAligner: Java implementation of the Smith-Waterman algorithm for biological sequence alignment
		is an open source Java implementation of the Smith-Waterman algorithm with Gotoh's improvement for biological local pairwise sequence alignment using the affine gap penalty model.
		Smith, T.F. and Waterman, M.S. Identification of common molecular subsequences.
		Gotoh, O. An improved algorithm for matching biological sequences.
	jaligner.sourceforge.net (778 words)

	Computers and the Human Genome Project: Smith-Waterman Algorithm
		The Smith-Waterman algorithm is a database search algorithm developed by T.F. Smith and M.S. Waterman, and based on an earlier model appropriately named Needleman and Wunsch after its original creators.
		The S-W Algorithm implements a technique called dynamic programming, which takes alignments of any length, at any location, in any sequence, and determines whether an optimal alignment can be found.
		It is superior to the BLAST and FASTA algorithms because it searches a larger field of possibilities, making it a more sensitive technique; however, individual pair-wise comparisons between letter slows the process down significantly.
	cse.stanford.edu /class/sophomore-college/projects-00/computers-and-the-hgp/smith_waterman.html (668 words)

	Microparallelism and High-Performance Protein Matching
		The Smith-Waterman algorithm is a computationally-intensive string-matching operation that is fundamental to the analysis of proteins and genes.
		Since a long gap can be introduced by a single mutation event, the algorithm assigns a penalty of the form U+kV for a gap of length k, where U is typically larger than V. This level of generality has been found to be sufficient to provide accurate answers.
		The performance advantages of the floating-point formulation of the algorithm are that the pipeline-stopping conditional branches are eliminated, that the integer instruction unit can be devoted to doing loads and stores while the floating-point unit does the multiply and adds, and that fused multiply-add instructions can implement a MAX and ADD in a single instruction.
	www-cse.ucsd.edu /users/carter/Micro/sc95.html (4057 words)

	Bringing Reconfigurable Computing to Real-World Applications
		Deciding how to partition the software and hardware implementation of an algorithm is a complex process, guided by the unique code profile and its memory and bandwidth requirements.
		One query character is preloaded into each processing element, which then applies the algorithm's equations to calculate the score for that square.
		By designing our Smith-Waterman implementation with 24-bit integers (sufficient to store the maximum possible score of the algorithm) we were able to use 16 more processing elements than would have been possible with 32 bits, and run approximately 20 MHz faster.
	www.fpgajournal.com /articles_2006/20060207_cray.htm (1642 words)

	FASTA a fast approximation to Smith-Waterman
		These regions are a diagonal or a few closely spaced diagonals in the table which have a high number of identical word matches between the sequences.
		The FASTA algorithm is a heuristic approximation to the Smith-Waterman algorithm.
		The first step in the FASTA algorithm is to divide the query sequence into its constituent overlapping words of length two for proteins or six for nucleic acids.
	www.bioinfo.se /kurser/swell/fasta.html (1035 words)

	Farhan Ahmed ’05 Conducts Honors Thesis that Could Help DNA Research
		Other algorithms most commonly used in genomics, the study of the genetic makeup of living things, are not as precise as the Smith-Waterman.
		And the memory requirement of the algorithm is higher than the current technology supports on a regular 32-bit processor machine.
		The complexity of DNA and protein makes running exhaustive algorithms impractical, and those used don’t explore all possible combinations of genetic makeup because of the sheer size of the task, so the results of these algorithms are probable, not exact.
	www.lafayette.edu /news.php/view/6749 (915 words)

	Biomedical Initiative - (Site not responding. Last check: 2007-10-30)
		The Smith-Waterman algorithm places no restriction on the alignment it reports other than that it have a positive score in terms of the similarity table used to score the alignment (17).
		The BLAST algorithm (20) uses a word based heuristic similar to that of FASTA to approximate a simplification of the Smith-Waterman algorithm known as the maximal segment pairs algorithm.
		However, the longest uninterrupted section of an alignment produced by the Smith-Waterman or the FASTA algorithms cannot be longer than the maximum segment pair alignment between the same pair of sequences (although it may be shorter).
	www.psc.edu /biomed/training/tutorials/sequence/db (10431 words)

	Dictionary of Algorithms and Data Structures
		This is a dictionary of algorithms, algorithmic techniques, data structures, archetypical problems, and related definitions.
		We do not include algorithms particular to business data processing, communications, operating systems or distributed algorithms, programming languages, AI, graphics, or numerical analysis: it is tough enough covering "general" algorithms and data structures.
		Data Structures and Algorithms is a wonderful site with illustrations, explanations, analysis, and code taking the student from arrays and lists through trees, graphs, and intractable problems.
	www.nist.gov /dads (680 words)

	[No title]
		Waterman is best known as the developer, with Temple F. Smith, of the Smith-Waterman algorithm for determining the degree of similarity (homology) of amino acid sequences from DNA, RNA, or proteins.
		Waterman is a founding editor of the Journal of Computational Biology and serves on the editorial boards of six other journals.
		In the study of RNA secondary structure, he developed algorithms based on general energy functions for multiple loops and for simultaneous folding and alignment, and performed the earliest studies of parametric folding and automated phylogenetic filtering.
	www.iscb.org /ssaa.shtml (1182 words)

	BioPlanet Bioinformatics - Powered by XMB
		However, if the majority of the elements are positive, the algorithm will return the global alignment of the sequences - this is because the sequences are so similar that the best alignment is reached by starting at the beginning and going to the end.
		However, imagine the case were you have 2 sequences that have "random" bases at the beginning and end of both sequences and somewhere in the middle there is a string of matches.
		If you did not include the zero, the algorithm would look for the best match from beginning to end.
	www.bioplanet.com /planetforums/viewthread.php?tid=531 (598 words)

	Implementing the Smith-Waterman Algorithm on a Reconfigurable Computer (Site not responding. Last check: 2007-10-30)
		The Smith-Waterman algorithm is a dynamic-programming algorithm that finds the optimal alignment between two biological sequences.
		However, hardware implementations of the algorithm that exploit opportunities for parallelism in the dynamic-programming procedure can be used to accelerate its execution.
		The Handel-C language was used to implement a parallelised version of the algorithm, which manages partitioning of the query and database sequences.
	www.iscb.org /ismb2003/posters/GIOGY001ATstudents.unisa.edu.au_228.html (277 words)

	A New Approach to Sequence Comparison: Normalized Sequence Alignment (Site not responding. Last check: 2007-10-30)
		The Smith-Waterman algorithm for local sequence alignment is one of the most important techniques in computational molecular biology.
		The Smith-Waterman algorithm finds the local alignment with maximal score but it is unable to find local alignment with maximum degree of similarity (e.g., maximal percent of matches).
		In this paper we propose a new sequence comparison algorithm (normalized local alignment) that reports the regions with maximum degree of similarity.
	www.cs.ucsb.edu /~omer/personal/abstracts/lna01.html (235 words)

	man page(1) manual page
		pv34compfa and pv34compsw compare all of the sequences in one DNA or protein sequence library (the query library) with to all of the entries in a reference sequence library using the FASTA (pv34compfa) or Smith-Waterman (pv34compsw) algorithms.
		Alternative, the -o option causes optimized scores to be calculated for every sequence greater than a threshold and the output to be sorted by the optimized scores.
		The gap penalties and scoring matrices can be modified with the -f, -k, and -s options.
	bioweb.pasteur.fr /docs/man/man/pvcomp.1.html (852 words)

	Bio::Tools::pSW - pairwise Smith Waterman object
		The alignment algorithm is implemented in C and added in using an XS extension.
		The algorithm is actually implemented in C, which means it is faster than a pure perl implementation (I have never done one, so I have no idea how faster) and will use considerably less memory, as it efficiently assigns memory for the calculation.
		The algorithm was written using Dynamite, and so contains an automatic switch to the linear space divide-and-conquer method.
	cpan.uwinnipeg.ca /htdocs/bioperl/Bio/Tools/pSW.html (968 words)

	2001/2002 Marine Biological Laboratory HMC CS Clinic Project
		The basis for the pairwise alignments is an additive scoring scheme that evaluates matched versus mismatched nucleotides or amino acids.
		Hence faster heuristic algorithms such as those in the programs FASTA and BLAST are often used.
		Success in developing a multilevel parallel implementation of the Smith-Waterman algorithm would have a broad impact on molecular biology and biochemistry and generate tremendous interest in the biological and biochemical research communities.
	www.cs.hmc.edu /clinic/projects/2001/mbl/description.html (674 words)

	EBI Tools: Homology & Similarity, DNA and Protein Searches. Completed Genomes and Proteomes
		This services is currently running on a compaq cluster and will be on a 21 CPU Linux cluster in the near future.
		It implements various flavours of dynamic programming algorithm (4) such as the Smith-Waterman local alignment method.
		MPsrch is a biological protein sequence comparison tool that implements the true Smith and Waterman algorithm.
	www.ebi.ac.uk /searches/blitz.html (174 words)

	Computing Science Bibliographic Database (Site not responding. Last check: 2007-10-30)
		Abstract: We investigate the use of variants of the Smith-Waterman algorithm to locate similarities in texts and in program source code, with a view to its application in the detection of plagiarism and collusion.
		The Smith-Waterman algorithm is a classical tool in the identification and quantification of local similarities in biological sequences, but we demonstrate that somewhat different issues arise in this different context, and that these factors can be exploited to yield significant speed-up in practice.
		We include empirical evidence to indicate the utility of the approach and to illustrate the efficiency gains.
	www.dcs.gla.ac.uk /contacts/paperdetails.cfm?id=7444 (110 words)

	Using the OSC portal to perform Smith-Waterman searches using TimeLogic DeCypher systems (Site not responding. Last check: 2007-10-30)
		While taking longer to execute, the algorithm provides greater accuracy in results against the target database.
		It also assumes that the file of sequences to be searched using the Smith-Waterman algorithm is in FASTA format, has a suffix.fsa and is located on the system running the web-browser.
		A further assumption is that the name of the database is known or present on the OSC TimeLogic systems.
	www.osc.edu /research/bioinformatics/portal/smithw.shtml (736 words)

	EMBOSS: water
		The Smith-Waterman algorithm is a member of the class of algorithms that can calculate the best score and local alignment in the order of mn steps, (where 'n' and 'm' are the lengths of the two sequences).
		These dynamic programming algorithms were first developed for protein sequence comparison by Smith and Waterman, though similar methods were independently devised during the late 1960's and early 1970's for use in the fields of speech processing and computer science.
		The algorithm starts the alignment at the highest path matrix score and works backwards until a cell contains zero.
	bioweb.pasteur.fr /docs/EMBOSS/water.html (2118 words)

	PRESS RELEASE Cray Introduces a More Powerful Smith-Waterman Solution Based on Cray's XD1 System (Site not responding. Last check: 2007-10-30)
		Life sciences researchers can now use the Cray XD1 system equipped with Smith-Waterman cores to significantly reduce the time required for genomic data analysis, a critical step in many life science and biotechnology research areas.
		The changes made to invoke the FPGAs are being released back into the open-source community, so researchers can always run the latest version of this popular open-source tool.
		Researchers can dramatically accelerate the Smith-Waterman algorithm and get accurate results up to 28 times faster than with off-the-shelf processing.
	www.marketwire.com /mw/release_html_b1?release_id=100311 (669 words)

	USC College : Michael Waterman
		Professor Waterman researches molecular sequence data using computational approaches.
		Professor Waterman is the co-developer of the Smith-Waterman algorithm for sequence comparison and of the Lander-Waterman formulas for physical mapping and sequencing.
		Reinert, G., Scabath, S., and M.S. Waterman, Probabilistic and statistical properties of words} {sl J. Comp.
	www.usc.edu /assets/college/faculty/old_profiles/36.html (187 words)

	Smith-Waterman algorithm
		Temple F. Smith and Michael S. Waterman, Identification of Common Molecular Subsequences, J. Mol.
		Go to the Dictionary of Algorithms and Data Structures home page.
		Paul E. Black, "Smith-Waterman algorithm", in Dictionary of Algorithms and Data Structures [online], Paul E. Black, ed., U.S. National Institute of Standards and Technology.
	www.nist.gov /dads/HTML/smithWaterman.html (102 words)

	Local Optima Sequence Alignment
		This is achieved almost entirely through a different choice of the scoring matrix and thus is a fine example how important the scoring matrix is in the process of sequence alignments.
		Like all fast gapping algorithms, the alignment displayed is a member of the family of best alignments.
		The scoring matrix used by Smith and Waterman, when local alignments were first described, used -0.333 for the mismatch penalty.
	www.sanbi.ac.za /~winhide/teach-19april/sw.html (2656 words)

	HSLS: MPsrch --True Smith and Waterman algorithm search tool (Site not responding. Last check: 2007-10-30)
		MPsrch is a biological sequence comparison tool that implements the true Smith and Waterman algorithm.
		MPsrch utilizes an exhaustive algorithm, which is recognized as the most sensitive sequence comparison method available, whereas Blast and Fasta utilize a heuristic one.
		As a consequence, MPsrch is capable of identifying hits in cases where Blast and Fasta fail and also reports fewer false-positive hits.
	www.hsls.pitt.edu /guides/genetics/tools/protein/similaritysearching/URL1043954844/info?print_format=true (185 words)

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