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*** network distributed basic local alignment search toolkit (***-BLAST)

BMC BIOINFORMATICS 2005年第1期6卷 1-14页

作者： Dowd, SE Zaragoza, J Rodriguez, JR Oliver, MJ Payton, PR ARS Livestock Issues Res Unit USDA Lubbock TX USA ARS Plant Stress & Germplasm Dev Res Unit USDA Lubbock TX USA

Background: BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows. NET Distributed basic local alignment search toolkit ( W. ND-BLAST), which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality. Results: ***-BLAST is a comprehensive Windows-based software toolkit that targets researchers, including those with minimal computer skills, and provides the ability increase the performance of BLAST by distributing BLAST queries to any number of Windows based machines across local area networks (LAN). ***-BLAST provides intuitive Graphic User Interfaces (GUI) for BLAST database creation, BLAST execution, BLAST output evaluation and BLAST result exportation. This software also provides several layers of fault tolerance and fault recovery to prevent loss of data if nodes or master machines fail. This paper lays out the functionality of ***-BLAST. ***-BLAST displays close to 100% performance efficiency when distributing tasks to 12 remote computers of the same performance class. A high throughput BLAST job which took 662.68 minutes ( 11 hours) on one average machine was completed in 44.97 minutes when distributed to 17 nodes, which included lower performance class machines. Finally, there is a comprehensive high-throughput BLAST Output Viewer (BOV) and Annotation Engine components, which provides comprehensive exportation of BLAST hits to text files, annotated fasta files, tables, or association files. Conclusion: ***-BLAST provides an interactive tool that allows scientists to easily utilizing their available computing resources for high throughput and comprehensive sequence analyses. The install package for ***-BLAST is freely downloadable fr

关键词： Fault Tolerance Child Node basic local alignment search tool Master Node Fasta File

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SS-Wrapper: a package of wrapper applications for similarity searches on Linux clusters

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BMC BIOINFORMATICS 2004年第1期5卷 1-9页

作者： Wang, CL Lefkowitz, EJ Univ Alabama Birmingham Dept Microbiol Birmingham AL 35294 USA

Background: Large-scale sequence comparison is a powerful tool for biological inference in modern molecular biology. Comparing new sequences to those in annotated databases is a useful source of functional and structural information about these sequences. Using software such as the basic local alignment search tool ( BLAST) or HMMPFAM to identify statistically significant matches between newly sequenced segments of genetic material and those in databases is an important task for most molecular biologists. searching algorithms are intrinsically slow and data-intensive, especially in light of the rapid growth of biological sequence databases due to the emergence of high throughput DNA sequencing techniques. Thus, traditional bioinformatics tools are impractical on PCs and even on dedicated UNIX servers. To take advantage of larger databases and more reliable methods, high performance computation becomes necessary. Results: We describe the implementation of SS-Wrapper ( Similarity search Wrapper), a package of wrapper applications that can parallelize similarity search applications on a Linux cluster. Our wrapper utilizes a query segmentation-search (QS-search) approach to parallelize sequence database search applications. It takes into consideration load balancing between each node on the cluster to maximize resource usage. QS-search is designed to wrap many different search tools, such as BLAST and HMMPFAM using the same interface. This implementation does not alter the original program, so newly obtained programs and program updates should be accommodated easily. Benchmark experiments using QS-search to optimize BLAST and HMMPFAM showed that QS-search accelerated the performance of these programs almost linearly in proportion to the number of CPUs used. We have also implemented a wrapper that utilizes a database segmentation approach (DS-BLAST) that provides a complementary solution for BLAST searches when the database is too large to fit into the memory of a single

关键词： Query Sequence basic local alignment search tool Message Passing Interface Sequence Similarity search basic local alignment search tool search

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PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

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BMC BIOINFORMATICS 2007年第1期8卷 1-10页

作者： He, Ji Dai, Xinbin Zhao, Xuechun Samuel Roberts Noble Fdn Inc Div Plant Biol Bioinformat Lab Ardmore OK 73401 USA

Background: BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Results: Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. Conclusion: PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interfa

关键词： Query Sequence basic local alignment search tool Laboratory Information Management System basic local alignment search tool search search Session

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DraGnET: Software for storing, managing and analyzing annotated draft genome sequence data

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BMC BIOINFORMATICS 2010年第1期11卷 1-13页

作者： Duncan, Stacy Sirkanungo, Ruchita Miller, Leslie Phillips, Gregory J. Iowa State Univ Dept Vet Microbiol & Prevent Med Ames IA 50011 USA Iowa State Univ Dept Comp Sci Ames IA USA Iowa State Univ Interdept Bioinformat & Computat Biol Ames IA USA

Background: New "next generation" DNA sequencing technologies offer individual researchers the ability to rapidly generate large amounts of genome sequence data at dramatically reduced costs. As a result, a need has arisen for new software tools for storage, management and analysis of genome sequence data. Although bioinformatic tools are available for the analysis and management of genome sequences, limitations still remain. For example, restrictions on the submission of data and use of these tools may be imposed, thereby making them unsuitable for sequencing projects that need to remain in-house or proprietary during their initial stages. Furthermore, the availability and use of next generation sequencing in industrial, governmental and academic environments requires biologist to have access to computational support for the curation and analysis of the data generated;however, this type of support is not always immediately available. Results: To address these limitations, we have developed DraGnET (Draft Genome Evaluation tool). DraGnET is an open source web application which allows researchers, with no experience in programming and database management, to setup their own in-house projects for storing, retrieving, organizing and managing annotated draft and complete genome sequence data. The software provides a web interface for the use of BLAST, allowing users to perform preliminary comparative analysis among multiple genomes. We demonstrate the utility of DraGnET for performing comparative genomics on closely related bacterial strains. Furthermore, DraGnET can be further developed to incorporate additional tools for more sophisticated analyses. Conclusions: DraGnET is designed for use either by individual researchers or as a collaborative tool available through Internet (or Intranet) deployment. For genome projects that require genome sequencing data to initially remain proprietary, DraGnET provides the means for researchers to keep their data in-house for analys

关键词： basic local alignment search tool Genome Sequence Data Integrate Microbial Genome Reverse Vaccinology Strain Information

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Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment

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BMC BIOINFORMATICS 2007年第1期8卷 1-17页

作者： Jothi, Raja Przytycka, Teresa M. Aravind, L. Natl Lib Med Natl Ctr Biotechnol Informat NIH Bethesda MD 20894 USA

Background: A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution. Results: Our experimentation with E. coli and yeast proteins with 16 different carefully composed reference sets of genomes revealed that the phyletic patterns of proteins in prokaryotes alone could be adequate enough to make reasonably accurate functional linkage predictions. A slight improvement in performance is observed on adding few eukaryotes into the reference set, but a noticeable drop-off in performance is observed with increased number of eukaryotes. Inclusion of most parasitic, pathogenic or vertebrate genomes and multiple strains of the same species into the reference set do not necessarily contribute to an improved sensitivity or accuracy. Interestingly, we also found that evolutionary histories of individual pathways have a significant affect on the performance of the PPC approach with respect to a particular reference set. For example, to accurately predict functional links in carbohydrate or lipid metabolism, a reference set solely composed of prokaryotic (or bacterial) genomes performed among the best compared to one composed of genomes from all three super-kingdoms;this is in contrast to predicting functional links in translation for which a reference set composed of prokaryotic (or bacterial) genomes performed the worst. We also demonstrate that the widely used random null model to quantify the statistical significance of profile similarity is incomplete, which could result in an increased number of false-positives. Conclusion: Contrary to previous proposals, it is not merely the number of genomes but a careful selection of informative genomes in the reference set that influen

关键词： Mutual Information Similarity Score basic local alignment search tool KEGG Pathway Functional Linkage

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Protein function prediction by collective classification with explicit and implicit edges in protein-protein interaction networks

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BMC BIOINFORMATICS 2013年第12期14卷 1-13页

作者： Xiong, Wei Liu, Hui Guan, Jihong Zhou, Shuigeng Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China Fudan Univ Shanghai Key Lab Intelligent Informat Proc Shanghai 200433 Peoples R China Changzhou Univ Res Lab Informat Management Changzhou Jiangsu Peoples R China Tongji Univ Dept Comp Sci & Technol Shanghai 200092 Peoples R China

Background: Protein function prediction is an important problem in the post-genomic era. Recent advances in experimental biology have enabled the production of vast amounts of protein-protein interaction (PPI) data. Thus, using PPI data to functionally annotate proteins has been extensively studied. However, most existing network-based approaches do not work well when annotation and interaction information is inadequate in the networks. Results: In this paper, we proposed a new method that combines PPI information and protein sequence information to boost the prediction performance based on collective classification. Our method divides function prediction into two phases: First, the original PPI network is enriched by adding a number of edges that are inferred from protein sequence information. We call the added edges implicit edges, and the existing ones explicit edges correspondingly. Second, a collective classification algorithm is employed on the new network to predict protein function. Conclusions: We conducted extensive experiments on two real, publicly available PPI datasets. Compared to four existing protein function prediction approaches, our method performs better in many situations, which shows that adding implicit edges can indeed improve the prediction performance. Furthermore, the experimental results also indicate that our method is significantly better than the compared approaches in sparsely-labeled networks, and it is robust to the change of the proportion of annotated proteins.

关键词： Gene Ontology Prediction Performance basic local alignment search tool Annotate Protein Protein Versus

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Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

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BMC BIOINFORMATICS 2007年第1期8卷 1-14页

作者： Liu, Chun-Chi Lin, Chin-Chung Li, Ker-Chau Chen, Wen-Shyen E. Chen, Jiun-Ching Yang, Ming-Te Yang, Pan-Chyr Chang, Pei-Chun Chen, Jeremy J. W. Natl Chung Hsing Univ Dept Comp Sci Taichung Taiwan Natl Chung Hsing Univ Inst Biomed Sci Taichung Taiwan Acad Sinica Inst Stat Sci Taipei Taiwan Natl Chung Hsing Univ Inst Mol Biol Taichung Taiwan Natl Taiwan Univ Coll Med NTU Ctr Genom Med Taipei 10764 Taiwan Asia Univ Dept Biotechnol & Bioinformat Taichung Taiwan

Background: Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network ( ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos. Results: We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB) algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. Conclusion: The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through polymerase chain reacti

关键词： Root Mean Square Error Artificial Neural Network basic local alignment search tool Specific Oligos Hide Layer Node

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Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency

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BMC BIOINFORMATICS 2010年第1期11卷 1-10页

作者： Weng, Francis C. Su, Chien-Hao Hsu, Ming-Tsung Wang, Tse-Yi Tsai, Huai-Kuang Wang, Daryi Acad Sinica Inst Informat Sci Taipei 115 Taiwan Acad Sinica Biodivers Res Ctr Taipei 115 Taiwan Acad Sinica Res Ctr Informat Technol Innovat Taipei 115 Taiwan Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei 106 Taiwan

Background: Investigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However, at present, taxonomic binning tools for metagenomes discard 30-40% of Sanger sequencing data due to the stringency of BLAST cut offs. In an attempt to provide a comprehensive overview of metagenomic data, we re-analyzed the discarded metagenomes by using less stringent cut-offs. Additionally, we introduced a new criterion, namely, the evolutionary conservation of adjacency between neighboring genes. To evaluate the feasibility of our approach, we re-analyzed discarded contigs and singletons from several environments with different levels of complexity. We also compared the consistency between our taxonomic binning and those reported in the original studies. Results: Among the discarded data, we found that 23.7 +/- 3.9% of singletons and 14.1 +/- 1.0% of contigs were assigned to taxa. The recovery rates for singletons were higher than those for contigs. The Pearson correlation coefficient revealed a high degree of similarity (0.94 +/- 0.03 at the phylum rank and 0.80 +/- 0.11 at the family rank) between the proposed taxonomic binning approach and those reported in original studies. In addition, an evaluation using simulated data demonstrated the reliability of the proposed approach. Conclusions: Our findings suggest that taking account of conserved neighboring gene adjacency improves taxonomic assignment when analyzing metagenomes using Sanger sequencing. In other words, utilizing the conserved gene order as a criterion will reduce the amount of data discarded when analyzing metagenomes.

关键词： basic local alignment search tool Genomic Fragment Taxonomic Assignment Metagenomic Data Taxonomic Class

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Identification of taxol biosynthesis stage-enriched transcripts in Nodulisporium sylviforme, using suppression subtractive hybridization

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WORLD JOURNAL OF MICROBIOLOGY & BIOTECHNOLOGY 2008年第11期24卷 2601-2605页

作者： Chi, Yan Zhao, Dong-Li Zhou, Dong-Po Heilongjiang Univ Key Lab Microbe Harbin Peoples R China Dalian Univ Coll Biol Engn Key Lab Bioorgan Chem Dalian Peoples R China Dalian Univ Coll Med Dalian Peoples R China

The endophytic fungus Nodulisporium sylviforme produces taxol, a diterpene alkaloid compound that has unique anti-neoplastic activity. In this study, suppression subtractive hybridization was performed to identify genes in N. sylviforme that were involved in the up-regulation of taxol production. A total of 91 clones represented the differentially expressed genes were selected based on reverse blotting results. These clones were then sequenced and analyzed using BLAST-X comparisons that revealed that about 37.8% of the ESTs were homologous to 17 different proteins with known function, 20.7% were homologous to nine hypothetical proteins and the remaining 41.5% had no identifiable homology;these may be novel genes. Two enzymatic genes involved in taxol production were found. The data presented in this study provide the first primary overview of a set of genes that are differentially expressed in N. sylviforme during taxol biosynthesis and form a solid foundation for the construction of high taxol-yielding genetically engineered strains.

关键词： endophytic fungus expressed sequence tag differentially expressed genes taxol biosynthetic pathway basic local alignment search tool

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PepBank - a database of peptides based on sequence text mining and public peptide data sources

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BMC BIOINFORMATICS 2007年第1期8卷 1-10页

作者： Shtatland, Timur Guettler, Daniel Kossodo, Misha Pivovarov, Misha Weissleder, Ralph Harvard Univ Massachusetts Gen Hosp Sch Med Ctr Mol Imaging Res Charlestown MA 02129 USA No Essex Community Coll Haverhill MA 01830 USA

Background: Peptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequences or associated biological data. Rather, peptide sequences still have to be mined from abstracts and full-length articles, and/or obtained from the fragmented public sources. Description: We have constructed a new database (PepBank), which at the time of writing contains a total of 19,792 individual peptide entries. The database has a web-based user interface with a simple, Google-like search function, advanced text search, and BLAST and Smith-Waterman search capabilities. The major source of peptide sequence data comes from text mining of MEDLINE abstracts. Another component of the database is the peptide sequence data from public sources (ASPD and UniProt). An additional, smaller part of the database is manually curated from sets of full text articles and text mining results. We show the utility of the database in different examples of affinity ligand discovery. Conclusion: We have created and maintain a database of peptide sequences. The database has biological and medical applications, for example, to predict the binding partners of biologically interesting peptides, to develop peptide based therapeutic or diagnostic agents, or to predict molecular targets or binding specificities of peptides resulting from phage display selection. The database is freely available on http://***/, and the text mining source code (Peptide:: Pubmed) is freely available above as well as on CPAN (http://***/).

关键词： Peptide Sequence Text Mining basic local alignment search tool Phage Display Sequence Similarity search

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