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  • 1
    Language: English
    In: BMC Bioinformatics, August 2, 2011, Vol.12, p.316
    Description: Background The analysis of genome synteny is a common practice in comparative genomics. With the advent of DNA sequencing technologies, individual biologists can rapidly produce their genomic sequences of interest. Although web-based synteny visualization tools are convenient for biologists to use, none of the existing ones allow biologists to upload their own data for analysis. Results We have developed the web-based Genome Synteny Viewer (GSV) that allows users to upload two data files for synteny visualization, the mandatory synteny file for specifying genomic positions of conserved regions and the optional genome annotation file. GSV presents two selected genomes in a single integrated view while still retaining the browsing flexibility necessary for exploring individual genomes. Users can browse and filter for genomic regions of interest, change the color or shape of each annotation track as well as re-order, hide or show the tracks dynamically. Additional features include downloadable images, immediate email notification and tracking of usage history. The entire GSV package is also light-weighted which enables easy local installation. Conclusions GSV provides a unique option for biologists to analyze genome synteny by uploading their own data set to a web-based comparative genome browser. A web server hosting GSV is provided at http://cas-bioinfo.cas.unt.edu/gsv, and the software is also freely available for local installations.
    Keywords: Applications Software -- Usage ; Computational Biology -- Usage ; Gene Expression -- Research ; Dna Sequencing -- Usage
    ISSN: 1471-2105
    Source: Cengage Learning, Inc.
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  • 2
    Language: English
    In: BMC Bioinformatics, August 2, 2011, Vol.12, p.316
    Description: Background The analysis of genome synteny is a common practice in comparative genomics. With the advent of DNA sequencing technologies, individual biologists can rapidly produce their genomic sequences of interest. Although web-based synteny visualization tools are convenient for biologists to use, none of the existing ones allow biologists to upload their own data for analysis. Results We have developed the web-based Genome Synteny Viewer (GSV) that allows users to upload two data files for synteny visualization, the mandatory synteny file for specifying genomic positions of conserved regions and the optional genome annotation file. GSV presents two selected genomes in a single integrated view while still retaining the browsing flexibility necessary for exploring individual genomes. Users can browse and filter for genomic regions of interest, change the color or shape of each annotation track as well as re-order, hide or show the tracks dynamically. Additional features include downloadable images, immediate email notification and tracking of usage history. The entire GSV package is also light-weighted which enables easy local installation. Conclusions GSV provides a unique option for biologists to analyze genome synteny by uploading their own data set to a web-based comparative genome browser. A web server hosting GSV is provided at http://cas-bioinfo.cas.unt.edu/gsv, and the software is also freely available for local installations.
    Keywords: Applications Software -- Usage ; Computational Biology -- Usage ; Gene Expression -- Research ; Dna Sequencing -- Usage
    ISSN: 1471-2105
    Source: Cengage Learning, Inc.
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Language: English
    In: BMC Bioinformatics, 01 August 2011, Vol.12(1), p.316
    Description: Abstract Background The analysis of genome synteny is a common practice in comparative genomics. With the advent of DNA sequencing technologies, individual biologists can rapidly produce their genomic sequences of interest. Although web-based synteny visualization tools are convenient for biologists to use, none of the existing ones allow biologists to upload their own data for analysis. Results We have developed the web-based Genome Synteny Viewer (GSV) that allows users to upload two data files for synteny visualization, the mandatory synteny file for specifying genomic positions of conserved regions and the optional genome annotation file. GSV presents two selected genomes in a single integrated view while still retaining the browsing flexibility necessary for exploring individual genomes. Users can browse and filter for genomic regions of interest, change the color or shape of each annotation track as well as re-order, hide or show the tracks dynamically. Additional features include downloadable images, immediate email notification and tracking of usage history. The entire GSV package is also light-weighted which enables easy local installation. Conclusions GSV provides a unique option for biologists to analyze genome synteny by uploading their own data set to a web-based comparative genome browser. A web server hosting GSV is provided at http://cas-bioinfo.cas.unt.edu/gsv, and the software is also freely available for local installations.
    Keywords: Biology
    ISSN: 1471-2105
    E-ISSN: 1471-2105
    Source: Directory of Open Access Journals (DOAJ)
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  • 4
    Language: English
    In: BMC Bioinformatics, 01 May 2017, Vol.18(1), pp.1-10
    Description: Abstract Background Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers, because existing taxonomic classification tools for 16S rRNA gene sequences either do not provide species-level classification, or their classification results are unreliable. The unreliable results are due to the limitations in the existing methods which either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, or use nucleotide k-mer frequency as the proxy for sequence similarity measurement. Results We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our method does not need any training datasets specific for different taxonomic groups. Instead only a reference database is required for aligning to the query sequences, making our method easily applicable for different regions of the 16S rRNA gene or other phylogenetic marker genes. Conclusions Reliable species-level classification for 16S rRNA or other phylogenetic marker genes is critical for microbiome research. Our software shows significantly higher classification accuracy than the existing tools and we provide probabilistic-based confidence scores to evaluate the reliability of our taxonomic classification assignments based on multiple database matches to query sequences. Despite its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .
    Keywords: 16s Rrna Gene ; Taxonomic Classification ; Biology
    E-ISSN: 1471-2105
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  • 5
    Language: English
    In: BMC bioinformatics, 02 August 2011, Vol.12, pp.316
    Description: The analysis of genome synteny is a common practice in comparative genomics. With the advent of DNA sequencing technologies, individual biologists can rapidly produce their genomic sequences of interest. Although web-based synteny visualization tools are convenient for biologists to use, none of the existing ones allow biologists to upload their own data for analysis. We have developed the web-based Genome Synteny Viewer (GSV) that allows users to upload two data files for synteny visualization, the mandatory synteny file for specifying genomic positions of conserved regions and the optional genome annotation file. GSV presents two selected genomes in a single integrated view while still retaining the browsing flexibility necessary for exploring individual genomes. Users can browse and filter for genomic regions of interest, change the color or shape of each annotation track as well as re-order, hide or show the tracks dynamically. Additional features include downloadable images, immediate email notification and tracking of usage history. The entire GSV package is also light-weighted which enables easy local installation. GSV provides a unique option for biologists to analyze genome synteny by uploading their own data set to a web-based comparative genome browser. A web server hosting GSV is provided at http://cas-bioinfo.cas.unt.edu/gsv, and the software is also freely available for local installations.
    Keywords: Internet ; Software ; Synteny ; Genomics -- Methods ; Sequence Analysis, DNA -- Methods
    E-ISSN: 1471-2105
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  • 6
    Language: English
    In: BMC bioinformatics, 02 August 2012, Vol.13, pp.190
    Description: Web-based synteny visualization tools are important for sharing data and revealing patterns of complicated genome conservation and rearrangements. Such tools should allow biologists to upload genomic data for their own analysis. This requirement is critical because individual biologists are generating large amounts of genomic sequences that quickly overwhelm any centralized web resources to collect and display all those data. Recently, we published a web-based synteny viewer, GSV, which was designed to satisfy the above requirement. However, GSV can only compare two genomes at a given time. Extending the functionality of GSV to visualize multiple genomes is important to meet the increasing demand of the research community. We have developed a multi-Genome Synteny Viewer (mGSV). Similar to GSV, mGSV is a web-based tool that allows users to upload their own genomic data files for visualization. Multiple genomes can be presented in a single integrated view with an enhanced user interface. Users can navigate through all the selected genomes in either pairwise or multiple viewing mode to examine conserved genomic regions as well as the accompanying genome annotations. Besides serving users who manually interact with the web server, mGSV also provides Web Services for machine-to-machine communication to accept data sent by other remote resources. The entire mGSV package can also be downloaded for easy local installation. mGSV significantly enhances the original functionalities of GSV. A web server hosting mGSV is provided at http://cas-bioinfo.cas.unt.edu/mgsv.
    Keywords: Internet ; Software ; Synteny ; Genomics -- Methods
    E-ISSN: 1471-2105
    Source: MEDLINE/PubMed (U.S. National Library of Medicine)
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  • 7
    Language: English
    In: BMC Bioinformatics, 01 August 2012, Vol.13(1), p.190
    Description: Abstract Background Web-based synteny visualization tools are important for sharing data and revealing patterns of complicated genome conservation and rearrangements. Such tools should allow biologists to upload genomic data for their own analysis. This requirement is critical because individual biologists are generating large amounts of genomic sequences that quickly overwhelm any centralized web resources to collect and display all those data. Recently, we published a web-based synteny viewer, GSV, which was designed to satisfy the above requirement. However, GSV can only compare two genomes at a given time. Extending the functionality of GSV to visualize multiple genomes is important to meet the increasing demand of the research community. Results We have developed a multi-Genome Synteny Viewer (mGSV). Similar to GSV, mGSV is a web-based tool that allows users to upload their own genomic data files for visualization. Multiple genomes can be presented in a single integrated view with an enhanced user interface. Users can navigate through all the selected genomes in either pairwise or multiple viewing mode to examine conserved genomic regions as well as the accompanying genome annotations. Besides serving users who manually interact with the web server, mGSV also provides Web Services for machine-to-machine communication to accept data sent by other remote resources. The entire mGSV package can also be downloaded for easy local installation. Conclusions mGSV significantly enhances the original functionalities of GSV. A web server hosting mGSV is provided at http://cas-bioinfo.cas.unt.edu/mgsv.
    Keywords: Biology
    ISSN: 1471-2105
    E-ISSN: 1471-2105
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  • 8
    Language: English
    In: BMC Bioinformatics, London: BioMed Central
    Description: This article discusses a web-based multi-genome synteny viewer for customized data.
    Keywords: Genomes ; Centralized Web Resources ; Multi-Genome Synteny Viewer ; Mgsv
    Source: University of North Texas
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  • 9
    Language: English
    In: BMC Bioinformatics, May 9, 2007, Vol.8(151), p.151
    Description: Background Whole genome shotgun sequencing produces increasingly higher coverage of a genome with random sequence reads. Progressive whole genome assembly and eventual finishing sequencing is a process that typically takes several years for large eukaryotic genomes. In the interim, all sequence reads of public sequencing projects are made available in repositories such as the NCBI Trace Archive. For a particular locus, sequencing coverage may be high enough early on to produce a reliable local genome assembly. We have developed software, Tracembler, that facilitates in silico chromosome walking by recursively assembling reads of a selected species from the NCBI Trace Archive starting with reads that significantly match sequence seeds supplied by the user. Results Tracembler takes one or multiple DNA or protein sequence(s) as input to the NCBI Trace Archive BLAST engine to identify matching sequence reads from a species of interest. The BLAST searches are carried out recursively such that BLAST matching sequences identified in previous rounds of searches are used as new queries in subsequent rounds of BLAST searches. The recursive BLAST search stops when either no more new matching sequences are found, a given maximal number of queries is exhausted, or a specified maximum number of rounds of recursion is reached. All the BLAST matching sequences are then assembled into contigs based on significant sequence overlaps using the CAP3 program. We demonstrate the validity of the concept and software implementation with an example of successfully recovering a full-length Chrm2 gene as well as its upstream and downstream genomic regions from Rattus norvegicus reads. In a second example, a query with two adjacent Medicago truncatula genes as seeds resulted in a contig that likely identifies the microsyntenic homologous soybean locus. Conclusion Tracembler streamlines the process of recursive database searches, sequence assembly, and gene identification in resulting contigs in attempts to identify homologous loci of genes of interest in species with emerging whole genome shotgun reads. A web server hosting Tracembler is provided at http://www.plantgdb.org/tool/tracembler/, and the software is also freely available from the authors for local installations.
    Keywords: Genomics -- Research ; Nucleotide Sequencing -- Research
    ISSN: 1471-2105
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  • 10
    Language: English
    In: BMC Bioinformatics, 01 March 2012, Vol.13(Suppl 2), p.S9
    Description: Abstract Background Modern pyrosequencing techniques make it possible to study complex bacterial populations, such as 16S rRNA, directly from environmental or clinical samples without the need for laboratory purification. Alignment of sequences across the resultant large data sets (100,000+ sequences) is of particular interest for the purpose of identifying potential gene clusters and families, but such analysis represents a daunting computational task. The aim of this work is the development of an efficient pipeline for the clustering of large sequence read sets. Methods Pairwise alignment techniques are used here to calculate genetic distances between sequence pairs. These methods are pleasingly parallel and have been shown to more accurately reflect accurate genetic distances in highly variable regions of rRNA genes than do traditional multiple sequence alignment (MSA) approaches. By utilizing Needleman-Wunsch (NW) pairwise alignment in conjunction with novel implementations of interpolative multidimensional scaling (MDS), we have developed an effective method for visualizing massive biosequence data sets and quickly identifying potential gene clusters. Results This study demonstrates the use of interpolative MDS to obtain clustering results that are qualitatively similar to those obtained through full MDS, but with substantial cost savings. In particular, the wall clock time required to cluster a set of 100,000 sequences has been reduced from seven hours to less than one hour through the use of interpolative MDS. Conclusions Although work remains to be done in selecting the optimal training set size for interpolative MDS, substantial computational cost savings will allow us to cluster much larger sequence sets in the future.
    Keywords: Biology
    ISSN: 1471-2105
    E-ISSN: 1471-2105
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