<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002... more
<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002 Kaminker et al., licensee BioMed Central Ltd Sites for ; ; . Genomic sequence flanking the insertion site of each element was extracted from our dataset. Those elements for which duplicated target sequences could not be identified were discarded. The remaining sequences from each family were centered on the repeat (vertical gray line) and the average denaturation temperature across all sequences was determined using a 3-bp window size. In each panel, the light horizontal gray line represents the average denaturation temperature of random genomic sequence and the horizontal black line represents the average denaturation temperature of the experimental set of sequences. The -axis represents the distance (in bp) from the insertion site and the -axis represents the temperature (°C). The sequences flanking the (a) and (b) elements have opposite characteristics; the sequences have a higher than average denaturation temperature whereas the sequences have a lower than average denaturation temperature. The average denaturation temperature of the sequence flanking the elements does not differ from that of the random sequence.
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Research Interests: Computer Science, Design, Biomedicine, Knowledge Management, Data Analysis, and 15 moreEvaluation, Experience Design, Biomedical Ontology, Biological Sciences, Biomedical Research, Data Science, Best practice, Hypothesis, Dissemination, Basic Formal Ontology, Hypothesis Generation, Design Evaluation, Human Disease, Experimental Data, and Internet
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Research Interests: Computer Science, Ontology, Biomedicine, Biology, Medicine, and 15 moreMultidisciplinary, Nature, Annotation, Data Integration, Interoperability, Humans, Models, Classification, Gene ontology, Ontology Design, Information Storage and Retrieval, Data Integrity, Nervous System, IDEF, and Controlled Vocabulary
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The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the... more
The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.
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Semantic phenotyping has been shown to be an effective means to aid variant prioritization and characterization by comparison to both known Mendelian diseases and across species with animal models (Robinson et al 2013). This process,... more
Semantic phenotyping has been shown to be an effective means to aid variant prioritization and characterization by comparison to both known Mendelian diseases and across species with animal models (Robinson et al 2013). This process, whereby symptoms and characteristic phenotypic findings are curated with species-specific ontology terms, has generated a baseline set of disease phenotype descriptions for more than 7,000 Mendelian diseases (Kohler et al 2014a) as well as many thousands of descriptions of additional animal models. By leveraging the knowledge encoded in the ontology graph and methods drawn from information theory, similarities can be computed between any two sets of phenotype descriptions (Washington et al 2009). This very powerful technique has the potential to be used for disease diagnosis, particularly for novel and rare diseases when the underlying genetic cause is unknown. The robustness of semantic similarity methods is heavily dependent on the quality of both the...
<b>Copyright information:</b>Taken from "Systematic determination of patterns of gene expression during embryogenesis"Genome Biology 2002;3(12):research0088.1-88.14.Published online 23 Dec... more
<b>Copyright information:</b>Taken from "Systematic determination of patterns of gene expression during embryogenesis"Genome Biology 2002;3(12):research0088.1-88.14.Published online 23 Dec 2002PMCID:PMC151190.Copyright © 2002 Tomancak et al., licensee BioMed Central Ltd Series of five embryos stained with a probe () highlighting the fat-body primordium and revealing dynamic aspects of segmental fat-body specification. Ventral view with anterior to the left. Series of five embryos stained with a probe () visualizing the lamellocyte precursors. The staining reveals the spreading pattern of lamellocytes across the embryo and the 'hitchhiking' of migrating cells on the retracting germ band.
<b>Copyright information:</b>Taken from "Systematic determination of patterns of gene expression during embryogenesis"Genome Biology 2002;3(12):research0088.1-88.14.Published online 23 Dec... more
<b>Copyright information:</b>Taken from "Systematic determination of patterns of gene expression during embryogenesis"Genome Biology 2002;3(12):research0088.1-88.14.Published online 23 Dec 2002PMCID:PMC151190.Copyright © 2002 Tomancak et al., licensee BioMed Central Ltd Fourteen examples of correlations between microarray and image data for genes with known expression patterns. Microarray expression profiles are shown on the left. Red is absent, green is present, and vertical lines on bars represent error bars of triplicate measurements. On the right are six representative images, one for each stage range specified in Figure , ordered according to developmental time to allow visual correlation with the corresponding array profile. Anterior to the left. The most straightforward comparisons occur when gene expression comes on (e,n) or is turned off abruptly (a,b), corresponding to the absence or presence of staining respectively. In many cases, the absent/present call misses the expression of genes confined to a small subset of tissues (c,m). (l) Gene-expression levels increase, followed by an increase in staining intensity that occupies approximately the same proportion of the embryo. (f) The increase in microarray intensity reflects an increase in the number of cells in the embryo showing gene expression across time. (c) Fading expression is indicative of the restriction of gene expression to a smaller subset of cells as development proceeds. Frequently, a microarray profile will show both types of fluctuations, and in that case the visual correlation is rather subjective (g,h), unless accompanied by a clear-cut qualitative change (d,e,i). (k) Genes transcribed both maternally and zygotically have no 'off' period during our developmental time course. (j) The decrease in abundance of maternal transcript often overlaps with emergence of zygotic transcript, leading to the flattening of the early portion of the microarray profile.
<b>Copyright information:</b>Taken from "Annotation of the euchromatic genome: a systematic review"Genome Biology 2002;3(12):research0083.1-83.22.Published online 31 Dec 2002PMCID:PMC151185.Copyright © 2002 Misra et... more
<b>Copyright information:</b>Taken from "Annotation of the euchromatic genome: a systematic review"Genome Biology 2002;3(12):research0083.1-83.22.Published online 31 Dec 2002PMCID:PMC151185.Copyright © 2002 Misra et al., licensee BioMed Central Ltd Data directly used to annotate the dicistronic gene model are shown in the black panel and the gene models generated from these data are shown in the cyan panel. Coding sequences are delineated by green vertical lines (starts of translation) and red vertical lines (stops of translation). Dicistronic genes (dark blue) were predicted when assembled cDNA sequencing reads or complete cDNA sequence (light and dark green) span two complete open reading frames (ORF1 and ORF2, shaded in cyan panel) that are separated by in-frame stop codons. There must be additional evidence supporting the existence of both predicted peptides. In the case of on chromosome arm 3R, each of the two ORFs shares homology with proteins from other eukaryotes (orange) or (red).
<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002... more
<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002 Kaminker et al., licensee BioMed Central Ltd Plotted are average pairwise distances (per bp) for individual transposable element families by functional class. Mann-Whitney tests reveal that intra-family average pairwise distances differ significantly between LTR families and LINE-like families (&lt; 0.005), and between LTR families and TIR families (&lt; 0.0005), but not between LINE-like and TIR families (&lt; 0.311).
<b>Copyright information:</b>Taken from "Systematic determination of patterns of gene expression during embryogenesis"Genome Biology 2002;3(12):research0088.1-88.14.Published online 23 Dec... more
<b>Copyright information:</b>Taken from "Systematic determination of patterns of gene expression during embryogenesis"Genome Biology 2002;3(12):research0088.1-88.14.Published online 23 Dec 2002PMCID:PMC151190.Copyright © 2002 Tomancak et al., licensee BioMed Central Ltd The first four of the 14 genes returned by a query for genes expressed in the 'embryonic optic lobe' are shown. The 'Gene' column gives the gene name, gene identifier, EST identifier, cytological position and GO function assignments, where available. The gene name serves as a link to access the complete expression report page for that gene. Array profiles and images can be enlarged in a separate window by clicking on the thumbnail image. In the column labeled 'Body Part' is a list of all annotation terms that have been assigned to that gene, with the query subject (in this case, embryonic optic lobe) highlighted by bold italics. Each annotation term is hyperlinked to the ImaGO Gene Ontology browser.
<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002... more
<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002 Kaminker et al., licensee BioMed Central Ltd Plotted are the lengths (in bp) of individual elements by functional class: LTR (gray), LINE-like (white), and TIR (black). Pairwise tests among all three classes (LTR versusLINE-like, LTRversusTIR, and LINE-like versus TIR) reveal that the distribution of individual element lengths differ significantly between functional classes (Mann-Whitney test, &lt; 1 × 10).
<b>Copyright information:</b>Taken from "Annotation of the euchromatic genome: a systematic review"Genome Biology 2002;3(12):research0083.1-83.22.Published online 31 Dec 2002PMCID:PMC151185.Copyright © 2002 Misra et... more
<b>Copyright information:</b>Taken from "Annotation of the euchromatic genome: a systematic review"Genome Biology 2002;3(12):research0083.1-83.22.Published online 31 Dec 2002PMCID:PMC151185.Copyright © 2002 Misra et al., licensee BioMed Central Ltd Only evidence (black panel) directly used to annotate the gene models (cyan panel) is shown. Occasionally, annotation of a particular region required complex rearrangement of the exons comprising the Release 2 gene models. In this case, the second exon of the Release 2 annotation (light blue) was split off as a new gene (, dark blue) on the strength of DGC cDNA data (dark green) and BLASTX evidence (red). The remaining exon of , along with six other Release 2 annotations (, , , , , and ; light blue), were merged together into the large gene (dark blue), strongly supported by sequence of a full-length cDNA, GenBank:AF254867.
<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002... more
<b>Copyright information:</b>Taken from "The transposable elements of the euchromatin: a genomics perspective"Genome Biology 2002;3(12):research0084.1-84.2.Published online 23 Dec 2002PMCID:PMC151186.Copyright © 2002 Kaminker et al., licensee BioMed Central Ltd Multiple alignments generated from each respective family were used to approximate genomic variation. Each position along the length of the multiple alignment (-axis) was measured for the presence of a nucleotide. The percentage of elements within an alignment that contained the nucleotide was determined and is indicated along the -axis. A schematic drawing representing a , , or element is shown directly below each panel; coding regions are indicated by light-gray boxes and repeats (and ) are represented by black boxes.
<b>Copyright information:</b>Taken from "Annotation of the euchromatic genome: a systematic review"Genome Biology 2002;3(12):research0083.1-83.22.Published online 31 Dec 2002PMCID:PMC151185.Copyright © 2002 Misra et... more
<b>Copyright information:</b>Taken from "Annotation of the euchromatic genome: a systematic review"Genome Biology 2002;3(12):research0083.1-83.22.Published online 31 Dec 2002PMCID:PMC151185.Copyright © 2002 Misra et al., licensee BioMed Central Ltd Only evidence (black panel) directly used to annotate the gene models (cyan panel) is shown. Coding sequences are delineated by green vertical lines (starts of translation) and red vertical lines (stops of translation). The Release 3 annotations and α-(dark blue) on chromosome arm 3L overlap at their most distal 5' end, sharing a portion of their untranslated regions. These gene models are supported by many ESTs and cDNA sequencing reads (light green), a complete cDNA clone (dark green), and several GenBank records (dark green). In spite of the shared initiation point for these transcripts, none of the remaining exons or coding sequences coincides. Note the small exon (arrow) predicted by Genie and GENSCAN. This exon is not included in the α-annotation, for lack of other supporting evidence, but alternative cDNA clones including this exon will be screened for directly in cDNA libraries [].
Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research
Phenotype ontologies are typically constructed to serve the needs of a particular community, such as annotation of genotype-phenotype associations in mouse or human. Here we demonstrate how these ontologies can be improved through... more
Phenotype ontologies are typically constructed to serve the needs of a particular community, such as annotation of genotype-phenotype associations in mouse or human. Here we demonstrate how these ontologies can be improved through assignment of logical definitions using a core ontology of phenotypic qualities and multiple additional ontologies from the Open Biological Ontologies library. We also show how these logical definitions can be used for data integration when combined with a unified multi-species anatomy ontology. Background The completion of the Human Genome Project [1,2] has resulted in an increase in high-throughput systematic projects aimed at elucidating the molecular basis of human disease. Accurate, precise, and comparable phenotypic information is critical for gaining an in-depth understanding of the relationship between diseases and genes, as well as shedding light upon the influence of different environments on individual genotypes. Natural language free-text descr...
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In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been... more
In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to...
Research Interests: Computer Science, Algorithms, Developmental Biology, Genomics, Computational Biology, and 15 moreBiology, Life Sciences, Medicine, Databases, Biological Sciences, Environmental Sciences, Humans, Animals, Genetic Association Studies, Genotype, Genetic variation, Medicine and Health Sciences, Internet, Exome, and Genetic
Research Interests: Computer Science, Ontology, Documentation, Genomics, Biology, and 15 moreLife Sciences, Medicine, Annotation, Biological Sciences, Environmental Sciences, Humans, Mice, Animals, Nucleic Acids, Phenotype, Medicine and Health Sciences, Controlled Vocabulary, Unified Medical Language System, Internet, and Decipher
A PCR-based sequence-tagged site (STS) content mapping strategy has been used to generate a physical map with 90% coverage of the 120-Mb euchromatic portion of the Drosophila genome. To facilitate map completion, the bulk of the STS... more
A PCR-based sequence-tagged site (STS) content mapping strategy has been used to generate a physical map with 90% coverage of the 120-Mb euchromatic portion of the Drosophila genome. To facilitate map completion, the bulk of the STS markers was chosen in a nonrandom fashion. To ensure that all contigs were localized in relation to each other and the genome, these contig-building procedures were performed in conjunction with a large-scale in situ hybridization analysis of randomly selected clones from a Drosophila genomic library that had been generated in a P1 cloning vector. To date, the map consists of 649 contigs with an STS localized on average every 50 kb. This is the first whole genome that has been mapped based on a library constructed with large inserts in a vector that is maintained in Escherichia coli as a single-copy plasmid.
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The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes... more
The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second ‘Quest for Orthologs’ meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications. Contact: dessimoz@ebi.ac.uk
Research Interests: Bioinformatics, Computer Science, Genomics, Molecular Evolution, Standards, and 15 moreBiology, Life Sciences, Medicine, Annotation, Biological Sciences, Identification, Humans, Mathematical Sciences, Animals, Health Science, Genes, Prioritization, Medicine and Health Sciences, Genomes, and Letter to the editor
The influence of disease categories on gene candidate predictions from model organism phenotypes
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API for linked biological knowledge
Improvements to sim endpoints to prevent ddos queries, see: https://github.com/biolink/biolink-api/pull/381
<strong>2.1.0 Official Release</strong> Some of the new features include:<br> - Added ability to annotate a variant from VCF evidence tracks [1892](https://github.com/GMOD/Apollo/pull/1892)<br> - Allow forced... more
<strong>2.1.0 Official Release</strong> Some of the new features include:<br> - Added ability to annotate a variant from VCF evidence tracks [1892](https://github.com/GMOD/Apollo/pull/1892)<br> - Allow forced assignment of transcript to a gene [#1851](https://github.com/GMOD/Apollo/pull/1851)<br> - Added proper Instructor and Organism Admin permission level [#1178](https://github.com/GMOD/Apollo/issues/1178)<br> - Indicate start / stop codons with color [#1852](https://github.com/GMOD/Apollo/pull/1852)<br> - Set the default biotype on track [#1861](https://github.com/GMOD/Apollo/issues/1861) Some important bug fixes:<br> - Prevents setting bad translation starts and ends [#1838](https://github.com/GMOD/Apollo/issues/1838)<br> - Fixed descriptor leak when loading bulk loading GFF3 [#1187](https://github.com/GMOD/Apollo/pull/1887)<br> - Fixed adding ability to create sequence alterations of uneven length [#1883](https://github.com/GMOD/Apollo/issues/1883)<br> - Fixed problem where canonical splice-sites were not recognized if sequence was being shown in lower-case [#1879](https://github.com/GMOD/Apollo/issues/1879)<br> - In some cases when the name store is not properly configured, the location is not remembered [#1895](https://github.com/GMOD/Apollo/issues/1895) <br> *Note* You will need to [install node 6 or better](https://nodejs.org/en/download/package-manager/). <br> *Note* If updating your jbrowse settings from previous versions in `apollo-config.groovy` you will need to set the JBrowse to use the [currently tagged version or better](https://github.com/GMOD/Apollo/blob/master/sample-postgres-apollo-config.groovy#L113). If this is commented out, however, [the default will work](https://github.com/GMOD/Apollo/blob/master/grails-app/conf/Config.groovy#L388-L433). <br> *Note* Some issues with new tomcat and addStore / addTracks RFC 7230 and RFC 3986. See http://genomearchitect.readthedocs.io/en/latest/Setup.html?highlight=RFC#json-in-the-url-with-newer-versions-of-tomcat The complete change log can be fo [...]
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Fixes to allow biolink to correctly construct self-URLs when being served from behind an SSL-terminating proxy, see https://github.com/biolink/biolink-api/pull/377
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This release updates ontobio to include https://github.com/biolink/ontobio/pull/346 and other recent commits.
Nathan Dunn; Mónica C Muñoz-Torres; Deepak Unni; Colin Diesh; Eric Rasche; Eric Yao; Ian Holmes; Christine G Elsik; Suzanna E Lewis (ND, MMT, SEL) Berkeley Bioinformatics Open-source Projects, Lawrence Berkeley National Laboratory,... more
Nathan Dunn; Mónica C Muñoz-Torres; Deepak Unni; Colin Diesh; Eric Rasche; Eric Yao; Ian Holmes; Christine G Elsik; Suzanna E Lewis (ND, MMT, SEL) Berkeley Bioinformatics Open-source Projects, Lawrence Berkeley National Laboratory, Berkeley, CA; (CD, CE) University of Missouri, Columbia, MO; (EY,IH) Department of Bioengineering, University of California at Berkeley, Berkeley, CA; (ER) Center for Phage Technology, Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX
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<b>Copyright information:</b>Taken from "Reactome: a knowledge base of biologic pathways and processes"http://genomebiology.com/2007/8/3/R39Genome Biology 2007;8(3):R39-R39.Published online 16 Mar... more
<b>Copyright information:</b>Taken from "Reactome: a knowledge base of biologic pathways and processes"http://genomebiology.com/2007/8/3/R39Genome Biology 2007;8(3):R39-R39.Published online 16 Mar 2007PMCID:PMC1868929. The bold arrow in the reaction map at top points to the tricarboxylic acid (TCA) cycle.
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<b>Copyright information:</b>Taken from "Reactome: a knowledge base of biologic pathways and processes"http://genomebiology.com/2007/8/3/R39Genome Biology 2007;8(3):R39-R39.Published online 16 Mar 2007PMCID:PMC1868929.
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<b>Copyright information:</b>Taken from "Reactome: a knowledge base of biologic pathways and processes"http://genomebiology.com/2007/8/3/R39Genome Biology 2007;8(3):R39-R39.Published online 16 Mar... more
<b>Copyright information:</b>Taken from "Reactome: a knowledge base of biologic pathways and processes"http://genomebiology.com/2007/8/3/R39Genome Biology 2007;8(3):R39-R39.Published online 16 Mar 2007PMCID:PMC1868929. Warmer colors indicate reactions found in distantly related species; cooler colors indicate reactions inferred only in closely related species.
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Genome annotation is the process of identifying the location and function of a genome’s encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate... more
Genome annotation is the process of identifying the location and function of a genome’s encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate multiple sources of information such as transcriptome alignments, predictive models based on sequence profiles, and comparisons to features found in related organisms. Because rapidly decreasing costs are enabling an ever-growing number of scientists to incorporate sequencing as a routine laboratory technique, there is widespread demand for tools that can assist in the deliberative analytical review of genomic information. To this end, Apollo is an open source software package that enables researchers to efficiently inspect and refine the precise structure and role of genomic features in a graphical browser-based platform.In this paper we first outline some of Apollo’s newer user interface features, which were driven by the needs of this expanding ge...
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BioJS is an open source software project that develops visualization tools for different types of biological data. Here we report on the factors that influenced the growth of the BioJS user and developer community, and outline our... more
BioJS is an open source software project that develops visualization tools for different types of biological data. Here we report on the factors that influenced the growth of the BioJS user and developer community, and outline our strategy for building on this growth. The lessons we have learned on BioJS may also be relevant to other open source software projects.
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Biocuration has become a cornerstone for analyses in biology, and to meet needs, the amount of annotations has considerably grown in recent years. However, the reliability of these annotations varies; it has thus become necessary to be... more
Biocuration has become a cornerstone for analyses in biology, and to meet needs, the amount of annotations has considerably grown in recent years. However, the reliability of these annotations varies; it has thus become necessary to be able to assess the confidence in annotations. Although several resources already provide confidence information about the annotations that they produce, a standard way of providing such information has yet to be defined. This lack of standardization undermines the propagation of knowledge across resources, as well as the credibility of results from high-throughput analyses. Seeded at a workshop during the Biocuration 2012 conference, a working group has been created to address this problem. We present here the elements that were identified as essential for assessing confidence in annotations, as well as a draft ontology--the Confidence Information Ontology--to illustrate how the problems identified could be addressed. We hope that this effort will pro...