Computer applications in the biosciences : CABIOS最新文献_第9页

Using video-oriented instructions to speed up sequence comparison. 使用面向视频的指令来加快序列比较。

Computer applications in the biosciences : CABIOS Pub Date : 1997-04-01 DOI: 10.1093/bioinformatics/13.2.145

A Wozniak

{"title":"Using video-oriented instructions to speed up sequence comparison.","authors":"A Wozniak","doi":"10.1093/bioinformatics/13.2.145","DOIUrl":"https://doi.org/10.1093/bioinformatics/13.2.145","url":null,"abstract":"Motivation: This document presents an implementation of the well-known Smith-Waterman algorithm for comparison of proteic and nucleic sequences, using specialized video instructions. These instructions, SIMD-like in their design, make possible parallelization of the algorithm at the instruction level.Results: Benchmarks on an ULTRA SPARC running at 167 MHz show a speed-up factor of two compared to the same algorithm implemented with integer instructions on the same machine. Performance reaches over 18 million matrix cells per second on a single processor, giving to our knowledge the fastest implementation of the Smith-Waterman algorithm on a workstation. The accelerated procedure was introduced in LASSAP--a LArge Scale Sequence compArison Package software developed at INRIA--which handles parallelism at higher level. On a SUN Enterprise 6000 server with 12 processors, a speed of nearly 200 million matrix cells per second has been obtained. A sequence of length 300 amino acids is scanned against SWISSPROT R33 (1,8531,385 residues) in 29 s. This procedure is not restricted to databank scanning. It applies to all cases handled by LASSAP (intra- and inter-bank comparisons, Z-score computation, etc.","PeriodicalId":77081,"journal":{"name":"Computer applications in the biosciences : CABIOS","volume":"13 2","pages":"145-50"},"PeriodicalIF":0.0,"publicationDate":"1997-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/bioinformatics/13.2.145","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"20094540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 166

ONIX: an interactive PC program for the examination of protein 3D structure from PDB. ONIX:一个交互式PC程序，用于检查PDB中的蛋白质3D结构。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.111

A S Ivanov, A B Rumjantsev, V S Skvortşov, A I Archakov

引用次数: 2

Latent sequence periodicity of some oncogenes and DNA-binding protein genes. 某些癌基因和dna结合蛋白基因的潜在序列周期性。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.37

E V Korotkov, M A Korotkova, J S Tulko

引用次数: 28

Hexanucleotide frequency database. 六核苷酸频率数据库。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.107

W Bains

引用次数: 2

A tool for aligning very similar DNA sequences. 一种对非常相似的DNA序列进行比对的工具。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.75

K M Chao, J Zhang, J Ostell, W Miller

引用次数: 29

Post-processing of BLAST results using databases of clustered sequences. 聚类序列数据库对BLAST结果的后处理。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.81

G S Miller, R Fuchs

{"title":"Post-processing of BLAST results using databases of clustered sequences.","authors":"G S Miller, R Fuchs","doi":"10.1093/bioinformatics/13.1.81","DOIUrl":"https://doi.org/10.1093/bioinformatics/13.1.81","url":null,"abstract":"Motivation: When evaluating the results of a sequence similarity search, there are many situations where it can be useful to determine whether sequences appearing in the results share some distinguishing characteristic. Such dependencies between database entries are often not readily identifiable, but can yield important new insights into the biological function of a gene or protein.Results: We have developed a program called CBLAST that sorts the results of a BLAST sequence similarity search according to sequence membership in user-defined 'clusters' of sequences. To demonstrate the utility of this application, we have constructed two cluster databases. The first describes clusters of nucleotide sequences representing the same gene, as documented in the UNIGENE database, and the second describes clusters of protein sequences which are members of the protein families documented in the PROSITE database. Cluster databases and the CBLAST post-processor provide an efficient mechanism for identifying and exploring relationships and dependencies between new sequences and database entries.","PeriodicalId":77081,"journal":{"name":"Computer applications in the biosciences : CABIOS","volume":"13 1","pages":"81-7"},"PeriodicalIF":0.0,"publicationDate":"1997-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/bioinformatics/13.1.81","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"20040133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Secondary structure computer prediction of the poliovirus 5' non-coding region is improved by a genetic algorithm. 采用遗传算法改进了脊髓灰质炎病毒5型非编码区的二级结构计算机预测。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.1

K M Currey, B A Shapiro

{"title":"Secondary structure computer prediction of the poliovirus 5' non-coding region is improved by a genetic algorithm.","authors":"K M Currey, B A Shapiro","doi":"10.1093/bioinformatics/13.1.1","DOIUrl":"https://doi.org/10.1093/bioinformatics/13.1.1","url":null,"abstract":"Comparison of the secondary structure of the 5' non-coding region of poliovirus 3 RNA derived from the genetic algorithm with the model of Skinner et al. (J. Mol. Biol., 207, 379-392, 1989) demonstrates many of the confirmed structural elements. The genetic algorithm (Shapiro and Navetta, J. Supercomput., 8, 195-201, 1994) generates a population of all possible stems, then mixes, combines, and recombines these stems in multiple iterations on a massively parallel computer, ultimately selecting a most fit structure based on its energy. The secondary structure of the region containing the determinants of neurovirulence was better predicted using the genetic algorithm, whereas the dynamic programming algorithm (Zuker, Science, 244, 48-52, 1989) required phylogenetic comparative sequence analysis to arrive at the correct conclusion. In addition, artificial mutations were introduced throughout this region of the genome and although rearrangements in structure may occur, many structures persisted, suggesting that the given structures thus selected may have evolved to withstand isolated mutations. The genetic algorithm-derived structure for the 5' non-coding region compares favorably with the biological data and functions previously described, and contains all of the 'persistent' structures, suggesting also that the persistence factor may be an aid to validating structures.","PeriodicalId":77081,"journal":{"name":"Computer applications in the biosciences : CABIOS","volume":"13 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"1997-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/bioinformatics/13.1.1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"20040199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

ConsInspector 3.0: new library and enhanced functionality. ConsInspector 3.0:新的库和增强的功能。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.109

K Frech, P Dietze, T Werner

{"title":"ConsInspector 3.0: new library and enhanced functionality.","authors":"K Frech, P Dietze, T Werner","doi":"10.1093/bioinformatics/13.1.109","DOIUrl":"https://doi.org/10.1093/bioinformatics/13.1.109","url":null,"abstract":"Conslnspector (Freeh et al, 1993) is a program to scan nucleic acid sequences for matches to a pre-compiled library of transcription factor binding sites. The program carries out an extensive examination of binding site candidates; the real sequence is compared with randomly shuffled versions and sequence regions surrounding the conserved binding site are included in the analysis (default 40 bp upstream and 40 bp downstream of the highly conserved core sequence). This feature distinguishes the program from other methods available for the identification of transcription factor binding sites which are restricted to the binding sites: SIGNAL SCAN (Prestridge, 1991, 1996; Prestridge and Stormo, 1993), MATRIX SEARCH (Chen et al, 1995) and Matlnspector (Quandt et al, 1995a). Recently, we showed the quality scores (Q-scores) assigned by Conslnspector to correlate to some extent with biological functionality (Quandt et al, 1995b). Release 3.0 of Conslnspector, with enhanced performance and a considerably extended library of consensus profiles, is available now at ftp://ariane.gsf.de/pub/ or http://www.gsf.de/biodv/. The program Conslnd (Freeh et al, 1993) has been used to compile the library of consensus profiles. The library now encompasses 37 consensus profiles (Release 1.0: 12, Release 2.1: 17 consensus profiles) and is separated into four groups (Table I). The extended weight matrices were deduced from experimentally confirmed binding sequences selected from the TRANSFAC database (Wingender et al, 1996) or directly from the literature. Most consensus profiles of the original library have been improved by the inclusion of additional sequences. Consensus profiles have been compiled from a minimum of nine sequences (Table I). The analysis of DNA sequences for transcription factor binding sites with Conslnspector has improved since Release 1.0:","PeriodicalId":77081,"journal":{"name":"Computer applications in the biosciences : CABIOS","volume":"13 1","pages":"109-10"},"PeriodicalIF":0.0,"publicationDate":"1997-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/bioinformatics/13.1.109","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"20040632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Reduced space sequence alignment. 减少空间序列对齐。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.45

J A Grice, R Hughey, D Speck

{"title":"Reduced space sequence alignment.","authors":"J A Grice, R Hughey, D Speck","doi":"10.1093/bioinformatics/13.1.45","DOIUrl":"https://doi.org/10.1093/bioinformatics/13.1.45","url":null,"abstract":"MOTIVATION Sequence alignment is the problem of finding the optimal character-by-character correspondence between two sequences. It can be readily solved in O(n2) time and O(n2) space on a serial machine, or in O(n) time with O(n) space per O(n) processing elements on a parallel machine. Hirschberg's divide-and-conquer approach for finding the single best path reduces space use by a factor of n while inducing only a small constant slowdown to the serial version. RESULTS This paper presents a family of methods for computing sequence alignments with reduced memory that are well suited to serial or parallel implementation. Unlike the divide-and-conquer approach, they can be used in the forward-backward (Baum-Welch) training of linear hidden Markov models, and they avoid data-dependent repartitioning, making them easier to parallelize. The algorithms feature, for an arbitrary integer L, a factor proportional to L slowdown in exchange for reducing space requirement from O(n2) to O(n1 square root of n). A single best path member of this algorithm family matches the quadratic time and linear space of the divide-and-conquer algorithm. Experimentally, the O(n1.5)-space member of the family is 15-40% faster than the O(n)-space divide-and-conquer algorithm.","PeriodicalId":77081,"journal":{"name":"Computer applications in the biosciences : CABIOS","volume":"13 1","pages":"45-53"},"PeriodicalIF":0.0,"publicationDate":"1997-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/bioinformatics/13.1.45","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"20040128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 57

DROSOPOSON: a knowledge base on chromosomal localization of transposable element insertions in Drosophila. DROSOPOSON:果蝇转座因子插入染色体定位的知识库。

Computer applications in the biosciences : CABIOS Pub Date : 1997-02-01 DOI: 10.1093/bioinformatics/13.1.61

C Hoogland, C Biémont

引用次数: 5