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Fast, accurate, and scalable search techniques for homology searching of large genomic collections are becoming an increasingly important requirement as genomic sequence collections continue to double in size almost yearly. Almost all homology search techniques rely on extracting fixed-length overlapping sequences from queries and database sequences, and comparing these as the first step in query evaluation; this is a feature of well-known tools such as fasta, blast, and our own cafe technique. In this paper we discuss a novel, variable-length approach to extracting subsequences that is based on homology scoring matrices. Our motivation is to achieve a balance between the speed and accuracy of fixed-length choices, that is, to encapsulate the speed of longer subsequence lengths and the accuracy of shorter ones. We show that incorporating this approach into our cafe technique leads to a good compromise between accuracy and retrieval e#ciency when searching with blosum matrices sensitive to distant evolutionary relationships. We expect the same results would be achieved with other homology search techniques.
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... Some characteristics used in these papers may be borrowed to sequence alignment, but the structure of GenBank is a limitation. Chattaraj  provided another variable length interval based approach for homology search. The authors showed that one can achieve a balance between the speed and accuracy of fixed length choices. ...
Up to now, there are many homology search algorithms that have been investigated and studied. However, a good classification
method and a comprehensive comparison for these algorithms are absent. This is especially true for index based homology search
algorithms. The paper briefly introduces main index construction methods. According to index construction methods, index based
homology search algorithms are classified into three categories, i.e., length based index ones, transformation based index
ones, and their combination. Based on the classification, the characteristics of the currently popular index based homology
search algorithms are compared and analyzed. At the same time, several promising and new index techniques are also discussed.
As a whole, the paper provides a survey on index based homology search algorithms.
... Homology searches are a regular requirement of modern biological research. For example, the NCBI BLAST server is processing over 10 5 queries a day (Chattaraj and William, 2004). BLAST (Altschul et al., 1990, 1997) is the most widely used homology search software today. ...
New ideas, spaced seeds and gapped alignment before 6-frame translation are implemented for translated homology search in tPatternHunter. The new software compares favorably with tBLASTx.
Availability: The software is free to academics at http://www.bioinformaticssolutions.com/downloads/ph-academic/
Indexing and retrieval techniques for homology searching of genomic databases are increasingly important as the search tools are facing great challenges of rapid growth in sequence collection size. Consequently, the indexing and retrieval of possibly gigabytes sequences become expensive. In this paper, we present two new approaches for indexing genomic databases that can enhance the speed of indexing and retrieval. We show experimentally that the proposed methods can be more computationally efficient than the existing ones.
Scoring matrices for nucleic acid sequence comparison that are based on models appropriate to the analysis of molecular sequencing errors or biological mutation processes are presented. In mammalian genomes, transition mutations occur significantly more frequently than transversions, and the optimal scoring of sequence alignments based on this substitution model differs from that derived assuming a uniform mutation model. The information from sequence alignments potentially available using an optimal scoring system is compared with that obtained using the BLASTN default scoring. A modified BLAST database search tool allows these, or other explicitly specified scoring matrices, to be utilized in computationally efficient queries of nucleic acid databases with nucleic acid query sequences. Results of searches performed using BLASTN's default score matrix are compared with those using scores based on a mutational model in which transitions are more prevalent than transversions.
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 permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is described for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position Specific Iterated BLAST (PSLBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities.
Recall and precision are often used to evaluate the effectiveness of information retrieval systems. They are easy to define if there is a single query and if the retrieval result generated for the query is a linear ordering. However, when the retrieval results are weakly ordered, in the sense that several documents have an identical retrieval status value with respect to a query, some probabilistic notion of precision has to be introduced. Relevance probability, expected precision, and so forth, are some alternatives mentioned in the literature for this purpose. Furthermore, when many queries are to be evaluated and the retrieval results averaged over these queries, some method of interpolation of precision values at certain preselected recall levels is needed. The currently popular approaches for handling both a weak ordering and interpolation are found to be inconsistent, and the results obtained are not easy to interpret. Moreover, in cases where some alternatives are available, no comparative analysis that would facilitate the selection of a particular strategy has been provided. In this paper, we systematically investigate the various problems and issues associated with the use of recall and precision as measures of retrieval system performance. Our motivation is to provide a comparative analysis of methods available for defining precision in a probabilistic sense and to promote a better understanding of the various issues involved in retrieval performance evaluation.
Protein sequence alignments have become an important tool for molecular biologists. Local alignments are frequently constructed with the aid of a "substitution score matrix" that specifies a score for aligning each pair of amino acid residues. Over the years, many different substitution matrices have been proposed, based on a wide variety of rationales. Statistical results, however, demonstrate that any such matrix is implicitly a "log-odds" matrix, with a specific target distribution for aligned pairs of amino acid residues. In the light of information theory, it is possible to express the scores of a substitution matrix in bits and to see that different matrices are better adapted to different purposes. The most widely used matrix for protein sequence comparison has been the PAM-250 matrix. It is argued that for database searches the PAM-120 matrix generally is more appropriate, while for comparing two specific proteins with suspected homology the PAM-200 matrix is indicated. Examples discussed include the lipocalins, human alpha 1 B-glycoprotein, the cystic fibrosis transmembrane conductance regulator and the globins.
A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
An algorithm was developed which facilitates the search for similarities between newly determined amino acid sequences and sequences already available in databases. Because of the algorithm's efficiency on many microcomputers, sensitive protein database searches may now become a routine procedure for molecular biologists. The method efficiently identifies regions of similar sequence and then scores the aligned identical and differing residues in those regions by means of an amino acid replacability matrix. This matrix increases sensitivity by giving high scores to those amino acid replacements which occur frequently in evolution. The algorithm has been implemented in a computer program designed to search protein databases very rapidly. For example, comparison of a 200-amino-acid sequence to the 500,000 residues in the National Biomedical Research Foundation library would take less than 2 minutes on a minicomputer, and less than 10 minutes on a microcomputer (IBM PC).
When comparing two biological sequences, it is often desirable for a gap to be assigned a cost not directly proportional to
its length. If affine gap costs are employed, in other words if opening a gap costsv and each null in the gap costsu, the algorithm of Gotoh (1982,J. molec. Biol.
162, 705) finds the minimum cost of aligning two sequences in orderMN steps. Gotoh's algorithm attempts to find only one from among possibly many optimal (minimum-cost) alignments, but does not
always succeed. This paper provides an example for which this part of Gotoh's algorithm fails and describes an algorithm that
finds all and only the optimal alignments. This modification of Gotoh's algorithm still requires orderMN steps. A more precise form of path graph than previously used is needed to represent accurately all optimal alignments for
affine gap costs.
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 substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering
the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program
that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining
statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using
this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration
as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST
is used to uncover several new and interesting members of the BRCT superfamily.
The Protein Information Resource (PIR) produces the largest, most comprehensive, annotated protein sequence database in the
public domain, the PIR-International Protein Sequence Database, in collaboration with the Munich Information Center for Protein
Sequences (MIPS) and the Japan International Protein Sequence Database (JIPID). The expanded PIR WWW site allows sequence
similarity and text searching of the Protein Sequence Database and auxiliary databases. Several new web-based search engines
combine searches of sequence similarity and database annotation to facilitate the analysis and functional identification of
proteins. New capabilities for searching the PIR sequence databases include annotation-sorted search, domain search, combined
global and domain search, and interactive text searches. The PIR-International databases and search tools are accessible on
the PIR WWW site at http://pir.georgetown.edu and at the MIPS WWW site at http://www.mips.biochem.mpg.de . The PIR-International
Protein Sequence Database and other files are also available by FTP.
Given a transmembrane protein, we wish to find related ones by a database search. Due to the strongly hydrophobic amino acid composition of transmembrane domains, suboptimal results are obtained when general-purpose scoring matrices such as BLOSUM are used. Recently, a transmembrane-specific score matrix called PHAT was shown to perform much better than BLOSUM. In this article, we derive a transmembrane score matrix family, called SLIM, which has several distinguishing features. In contrast to currently used matrices, SLIM is non-symmetric. The asymmetry arises because different background compositions are assumed for the transmembrane query and the unknown database sequences. We describe the mathematical model behind SLIM in detail and show that SLIM outperforms PHAT both on simulated data and in a realistic setting. Since non-symmetric score matrices are a new concept in database search methods, we discuss some important theoretical and practical issues.
The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases).
We have developed three computer programs for comparisons of protein and DNA sequences. They can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence similarity. The FASTA program is a more sensitive derivative of the FASTP program, which can be used to search protein or DNA sequence data bases and can compare a protein sequence to a DNA sequence data base by translating the DNA data base as it is searched. FASTA includes an additional step in the calculation of the initial pairwise similarity score that allows multiple regions of similarity to be joined to increase the score of related sequences. The RDF2 program can be used to evaluate the significance of similarity scores using a shuffling method that preserves local sequence composition. The LFASTA program can display all the regions of local similarity between two sequences with scores greater than a threshold, using the same scoring parameters and a similar alignment algorithm; these local similarities can be displayed as a "graphic matrix" plot or as individual alignments. In addition, these programs have been generalized to allow comparison of DNA or protein sequences based on a variety of alternative scoring matrices.
The normalized recall is one of the most popular evaluation measures for information retrieval systems. In this paper an overview of its development is given. It is then shown that the normalized recall is closely related to other measures such as the CRE-measure and the expected search length. Some implications are analysed.
Database searching algorithms for proteins use scoring matrices based on average protein properties, and thus are dominated by globular proteins. However, since transmembrane regions of a protein are in a distinctly different environment than globular proteins, one would expect generalized substitution matrices to be inappropriate for transmembrane regions.
We present the PHAT (predicted hydrophobic and transmembrane) matrix, which significantly outperforms generalized matrices and a previously published transmembrane matrix in searches with transmembrane queries. We conclude that a better matrix can be constructed by using background frequencies characteristic of the twilight zone, where low-scoring true positives have scores indistinguishable from high-scoring false positives, rather than the amino acid frequencies of the database. The PHAT matrix may help improve the accuracy of sequence alignments and evolutionary trees of membrane proteins.
Methods for alignment of protein sequences typically measure similarity by using a substitution matrix with scores for all possible exchanges of one amino acid with another. The most widely used matrices are based on the Dayhoff model of evolutionary rates. Using a different approach, we have derived substitution matrices from about 2000 blocks of aligned sequence segments characterizing more than 500 groups of related proteins. This led to marked improvements in alignments and in searches using queries from each of the groups.
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With the development of large data banks of protein and nucleic acid sequences, the need for efficient methods of searching such banks for sequences similar to a given sequence has become evident. We present an algorithm for the global comparison of sequences based on matching k-tuples of sequence elements for a fixed k. The method results in substantial reduction in the time required to search a data bank when compared with prior techniques of similarity analysis, with minimal loss in sensitivity. The algorithm has also been adapted, in a separate implementation, to produce rigorous sequence alignments. Currently, using the DEC KL-10 system, we can compare all sequences in the entire Protein Data Bank of the National Biomedical Research Foundation with a 350-residue query sequence in less than 3 min and carry out a similar analysis with a 500-base query sequence against all eukaryotic sequences in the Los Alamos Nucleic Acid Data Base in less than 2 min.
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Several choices of amino acid substitution matrices are currently available for searching and alignment applications. These choices were evaluated using the BLAST searching program, which is extremely sensitive to differences among matrices, and the Prosite catalog, which lists members of hundreds of protein families. Matrices derived directly from either sequence-based or structure-based alignments of distantly related proteins performed much better overall than extrapolated matrices based on the Dayhoff evolutionary model. Similar results were obtained with the FASTA searching program. Improved performance appears to be general rather than family-specific, reflecting improved accuracy in scoring alignments. An implementation of a multiple matrix strategy was also tested. While no combination of three matrices performed as well as the single best matrix, BLOSUM 62, good results were obtained using a combination of sequence-based and structure-based matrices. This hybrid set of matrices is likely to be useful in certain situations. Our results illustrate the importance of matrix selection and the value of a comprehensive approach to evaluation of protein comparison tools.
Genomic sequence databases are widely used by molecular biologists
for homology searching. Amino acid and nucleotide databases are
increasing in size exponentially, and mean sequence lengths are also
increasing. In searching such databases, it is desirable to use
heuristics to perform computationally intensive local alignments on
selected sequences and to reduce the costs of the alignments that are
attempted. We present an index-based approach for both selecting
sequences that display broad similarity to a query and for fast local
alignment. We show experimentally that the indexed approach results in
significant savings in computationally intensive local alignments and
that index-based searching is as accurate as existing exhaustive search
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