For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
145
views
16
references
 Top references
cited by
290
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      74
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Integrated Genome Browser: free software for distribution and exploration of genome-scale datasets

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Summary: Experimental techniques that survey an entire genome demand flexible, highly interactive visualization tools that can display new data alongside foundation datasets, such as reference gene annotations. The Integrated Genome Browser (IGB) aims to meet this need. IGB is an open source, desktop graphical display tool implemented in Java that supports real-time zooming and panning through a genome; layout of genomic features and datasets in moveable, adjustable tiers; incremental or genome-scale data loading from remote web servers or local files; and dynamic manipulation of quantitative data via genome graphs.

          Availability: The application and source code are available from http://igb.bioviz.org and http://genoviz.sourceforge.net.

          Contact: aloraine@ 123456uncc.edu

          Related collections

          Most cited references16

          • Record: found
          • Abstract: found
          • Article: not found

          A high-resolution atlas of nucleosome occupancy in yeast.

          William Lee, Desiree Tillo, Nicolas Bray … (2007)
          We present the first complete high-resolution map of nucleosome occupancy across the whole Saccharomyces cerevisiae genome, identifying over 70,000 positioned nucleosomes occupying 81% of the genome. On a genome-wide scale, the persistent nucleosome-depleted region identified previously in a subset of genes demarcates the transcription start site. Both nucleosome occupancy signatures and overall occupancy correlate with transcript abundance and transcription rate. In addition, functionally related genes can be clustered on the basis of the nucleosome occupancy patterns observed at their promoters. A quantitative model of nucleosome occupancy indicates that DNA structural features may account for much of the global nucleosome occupancy.
          Article 0 comments Cited 324 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Empirical analysis of transcriptional activity in the Arabidopsis genome.

            Kayoko Yamada, Jun Jun Lim, Joseph Dale … (2003)
            Functional analysis of a genome requires accurate gene structure information and a complete gene inventory. A dual experimental strategy was used to verify and correct the initial genome sequence annotation of the reference plant Arabidopsis. Sequencing full-length cDNAs and hybridizations using RNA populations from various tissues to a set of high-density oligonucleotide arrays spanning the entire genome allowed the accurate annotation of thousands of gene structures. We identified 5817 novel transcription units, including a substantial amount of antisense gene transcription, and 40 genes within the genetically defined centromeres. This approach resulted in completion of approximately 30% of the Arabidopsis ORFeome as a resource for global functional experimentation of the plant proteome.
            Article 0 comments Cited 197 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Sampling the Arabidopsis transcriptome with massively parallel pyrosequencing.

              John Ohlrogge, Kevin Carr, Megan Weber … (2007)
              Massively parallel sequencing of DNA by pyrosequencing technology offers much higher throughput and lower cost than conventional Sanger sequencing. Although extensively used already for sequencing of genomes, relatively few applications of massively parallel pyrosequencing to transcriptome analysis have been reported. To test the ability of this technology to provide unbiased representation of transcripts, we analyzed mRNA from Arabidopsis (Arabidopsis thaliana) seedlings. Two sequencing runs yielded 541,852 expressed sequence tags (ESTs) after quality control. Mapping of the ESTs to the Arabidopsis genome and to The Arabidopsis Information Resource 7.0 cDNA models indicated: (1) massively parallel pyrosequencing detected transcription of 17,449 gene loci providing very deep coverage of the transcriptome. Performing a second sequencing run only increased the number of genes identified by 10%, but increased the overall sequence coverage by 50%. (2) Mapping of the ESTs to their predicted full-length transcripts indicated that all regions of the transcript were well represented regardless of transcript length or expression level. Furthermore, short, medium, and long transcripts were equally represented. (3) Over 16,000 of the ESTs that mapped to the genome were not represented in the existing dbEST database. In some cases, the ESTs provide the first experimental evidence for transcripts derived from predicted genes, and, for at least 60 locations in the genome, pyrosequencing identified likely protein-coding sequences that are not now annotated as genes. Together, the results indicate massively parallel pyrosequencing provides novel information helpful to improve the annotation of the Arabidopsis genome. Furthermore, the unbiased representation of transcripts will be particularly useful for gene discovery and gene expression analysis of nonmodel plants with less complete genomic information. EST sequence accession numbers in GenBank are EH 795234 through EH 995233 and EL 000001 through EL 341852.
              Article 0 comments Cited 119 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Journal ID (hwp): bioinfo
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1460-2059
                Publication date (Print): 15 October 2009
                Publication date (Electronic): 4 August 2009
                Publication date PMC-release: 4 August 2009
                Volume: 25
                Issue: 20
                Pages: 2730-2731
                Affiliations
                1 Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, 600 Laureate Way, Kannapolis, NC 28081 and 2 Genomancer Consulting, Healdsburg, CA 95448, USA
                Author notes
                * To whom correspondence should be addressed.

                Associate Editor: Alex Bateman

                Article
                Publisher ID: btp472
                DOI: 10.1093/bioinformatics/btp472
                PMC ID: 2759552
                PubMed ID: 19654113
                SO-VID: 0f3da060-d832-4e24-9065-d6e6293fccd8
                Copyright © © 2009 The Author(s)
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 5 June 2009
                Date revision received : 21 July 2009
                Date accepted : 30 July 2009
                Categories
                Subject: Applications Note
                Subject: Genome Analysis

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

                Comments

                Comment on this article

                scite_

                Similar content74

                See all similar

                Cited by268

                See all cited by

                Most referenced authors245

                See all reference authors