Topic
Annotation
About: Annotation is a research topic. Over the lifetime, 6719 publications have been published within this topic receiving 203463 citations. The topic is also known as: note & markup.
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TL;DR: The latest version of PANTHER, 10.0, includes almost 5000 new protein families (for a total of over 12 000 families), each with a reference phylogenetic tree including protein-coding genes from 104 fully sequenced genomes spanning all kingdoms of life.
Abstract: PANTHER (Protein Analysis THrough Evolutionary Relationships, http://pantherdb.org) is a widely used online resource for comprehensive protein evolutionary and functional classification, and includes tools for large-scale biological data analysis. Recent development has been focused in three main areas: genome coverage, functional information (‘annotation’) coverage and accuracy, and improved genomic data analysis tools. The latest version of PANTHER, 10.0, includes almost 5000 new protein families (for a total of over 12 000 families), each with a reference phylogenetic tree including protein-coding genes from 104 fully sequenced genomes spanning all kingdoms of life. Phylogenetic trees now include inference of horizontal transfer events in addition to speciation and gene duplication events. Functional annotations are regularly updated using the models generated by the Gene Ontology Phylogenetic Annotation Project. For the data analysis tools, PANTHER has expanded the number of different ‘functional annotation sets’ available for functional enrichment testing, allowing analyses to access all Gene Ontology annotations—updated monthly from the Gene Ontology database—in addition to the annotations that have been inferred through evolutionary relationships. The Prowler (data browser) has been updated to enable users to more efficiently browse the entire database, and to create custom gene lists using the multiple axes of classification in PANTHER.
798 citations
TL;DR: The DAVID Gene system as discussed by the authors was rebuilt to gain coverage of more organisms, which increased the taxonomy coverage from 17 399 to 55 464, and the number of gene-term records for most annotation types within the updated knowledgebase have significantly increased.
Abstract: Abstract DAVID is a popular bioinformatics resource system including a web server and web service for functional annotation and enrichment analyses of gene lists. It consists of a comprehensive knowledgebase and a set of functional analysis tools. Here, we report all updates made in 2021. The DAVID Gene system was rebuilt to gain coverage of more organisms, which increased the taxonomy coverage from 17 399 to 55 464. All existing annotation types have been updated, if available, based on the new DAVID Gene system. Compared with the last version, the number of gene-term records for most annotation types within the updated Knowledgebase have significantly increased. Moreover, we have incorporated new annotations in the Knowledgebase including small molecule-gene interactions from PubChem, drug-gene interactions from DrugBank, tissue expression information from the Human Protein Atlas, disease information from DisGeNET, and pathways from WikiPathways and PathBank. Eight of ten subgroups split from Uniprot Keyword annotation were assigned to specific types. Finally, we added a species parameter for uploading a list of gene symbols to minimize the ambiguity between species, which increases the efficiency of the list upload and eliminates confusion for users. These current updates have significantly expanded the Knowledgebase and enhanced the discovery power of DAVID.
797 citations
26 Oct 2010
TL;DR: The authors designed and implemented TAGME, a system that is able to efficiently and judiciously augment a plain-text with pertinent hyperlinks to Wikipedia pages, which is extremely informative, so any task that is currently addressed using the bag-of-words paradigm could benefit from using this annotation to draw upon Wikipedia pages and their interrelations.
Abstract: We designed and implemented TAGME, a system that is able to efficiently and judiciously augment a plain-text with pertinent hyperlinks to Wikipedia pages. The specialty of TAGME with respect to known systems [5,8] is that it may annotate texts which are short and poorly composed, such as snippets of search-engine results, tweets, news, etc.. This annotation is extremely informative, so any task that is currently addressed using the bag-of-words paradigm could benefit from using this annotation to draw upon (the millions of) Wikipedia pages and their inter-relations.
795 citations
TL;DR: To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization.
Abstract: The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.
784 citations
01 Apr 2001
TL;DR: The paper presents the overall design of Annotea and describes some of the issues the project faced and how it has solved them, including combining RDF with XPointer, XLink, and HTTP.
Abstract: Annotea is a Web-based shared annotation system based on a general-purpose open RDF infrastructure, where annotations are modeled as a class of metadata. Annotations are viewed as statements made by an author about a Web document. Annotations are external to the documents and can be stored in one or more annotation servers. One of the goals of this project has been to re-use as much existing W3C technology as possible. We have reached it mostly by combining RDF with XPointer, XLink, and HTTP. We have also implemented an instance of our system using the Amaya editor/browser and a generic RDF database, accessible through an Apache HTTP server. In this implementation, the merging of annotations with documents takes place within the client. The paper presents the overall design of Annotea and describes some of the issues we have faced and how we have solved them.
765 citations