! output from make_go_references_txt.pl ! input files: /var/pomcur/sources/go-site/metadata/gorefs/* ! recreate by running: ! make_go_references_txt.pl > go_references.txt ! in pombe-embl/supporting_files/ ! after "git pull" in /var/pomcur/sources/go-site ref_id: GO_REF:0000004 title: Comments year: 2000 authors: GOA curators abstract: Transitive assignments using UniProtKB keywords. The UniProtKB keyword controlled vocabulary has been created and used by the UniProt Knowledgebase (UniProtKB) to supply 10 different categories of information to UniProtKB entries. Further information on the UniProtKB keyword resource can be found at http://www.uniprot.org/docs/keywlist.
Further information on the UniProt annotation methods is available at https://www.uniprot.org/help/manual_curation and https://www.uniprot.org/help/automatic_annotation. ref_id: GO_REF:0000104 title: Electronic Gene Ontology annotations created by transferring manual GO annotations between related proteins based on shared sequence features. year: 2015 authors: UniProt curators abstract: GO terms are manually assigned to each rule in UniRule. These rules are prepared manually by UniProt curators based on the annotations present in reviewed UniProtKB/Swiss-Prot records that share sequence features, sequence similarity and taxonomy. The assigned GO terms are then transferred to all unreviewed UniProtKB/TrEMBL proteins that meet the conditions given in the UniRule rule. GO annotations using this technique receive the evidence code Inferred from Electronic Annotation (IEA; ECO:0000501). These annotations are updated regularly by UniProt and are available for download on both the GO and GOA EBI ftp sites. To report an annotation error or inconsistency, or for further information, please contact the UniProt Automated Annotation team at automated_annotation@ebi.ac.uk. UniRule is a collaboration between the European Bioinformatics Institute (EMBL-EBI), the Swiss Institute of Bioinformatics (SIB), and the Protein Information Resource at Georgetown University (PIR). For further information, please see UniProt: a hub for protein information Nucleic Acids Res. 2015, 43, D204, doi: 10.1093/nar/gku989 or www.uniprot.org. ref_id: GO_REF:0000090 title: Automatic creation of relationships between ontology branches in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a rule-based approach to create relations between the branches of the Gene Ontology. The approach uses the equivalence axioms and a given pattern to create non-subClassOf relationships between the three different branches of the Gene Ontology (biological process, molecular function, cellular component). Currently, there are the following rules: "'transporter activity' and 'transports_or_maintains_localization_of' some X' -part_of-> "transport and 'transports_or_maintains_localization_of' some X"; "'transmembrane transporter activity' and 'transports_or_maintains_localization_of' some X -part_of-> 'transmembrane transport' and 'transports_or_maintains_localization_of' some X" ref_id: GO_REF:0000062 title: Representation of processes occurring in parts of the cell in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing processes occurring in parts of the cell. The underlying equivalence axiom template is "P and 'occurs in' some C", where P is a biological process and C is a cellular component. ref_id: GO_REF:0000058 title: Representation of regulation in the Gene Ontology (biological process) year: 2013 authors: GO ontology editors abstract: We have created a standard template for the definition of classes for the regulation of a biological process. This includes the definitions for positive and negative regulation. The equivalence axiom templates are "GO:0065007 and 'regulates' some X" (regulation), "GO:0065007 and 'negatively_regulates' some X" (negative regulation), and "GO:0065007 and 'positively_regulates' some X" (positive regulation), where X is a biological process. ref_id: GO_REF:0000092 title: Representation for the biosynthesis from or via a chemical as biological process in the Gene Ontology year: 2014 authors: GO ontology editors abstract: We have created a standard template for classes describing the biosynthesis of a chemical entity from or via an other chemical entity as biological processes. The underlying equivalence axiom templates are "GO:0009058 and 'has output' some T and 'has input' some F" (biosynthesis from) and "GO:0009058 and 'has output' some T and 'has intermediate' some I" (biosynthesis via), where T,F, and I are chemical entities (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000050 title: Manual transfer of GO annotation data to genes by curator judgment of sequence model year: 2012 authors: PomBase curators abstract: Transitive assignment of GO terms to a gene based on a curator's judgment of its match to a sequence model,such as a Pfam or InterPro entry, that has manually curated GO annotations, mappings to GO terms, or a description from which GO terms can be inferred. A statistical model of a sequence or group of sequences is used to make a prediction about the function of a protein or RNA. Annotations are created when a curator evaluates the results, using criteria that include excluding false positives and ensuring that the annotation is accurate for all matches. Statistical scores (such as e values and cutoff scores) and the functional specificity of the model may also be (but are not always) considered. Annotations resulting from the transfer of GO terms use the 'ISM' evidence code and include an accession for the model from which the annotation was projected in the 'with' field (column 8). ref_id: GO_REF:0000025 title: Operon structure as IGC evidence year: 2007 authors: Michelle Gwinn, TIGR curators abstract: Genes in prokaryotic organisms are often arranged in operons. Genes in an operon are all transcribed into one mRNA. Generally the genes in the operons code for proteins that all have related functions. For example, they may be the steps in a biochemical pathway, or they may be the subunits of a protein complex. Often the genes in operons shared between organisms are syntenic; that is, the same genes are in the same order in the operon in different species. When assessing sequence-comparison-based evidence during the process of manual annotation of a genome, it is often the case that some of the genes in the operon will have strong sequence-based evidence while others will have weak evidence. If seen alone, not in the presence of an operon, the weak evidence in question may not be sufficient to make a functional annotation. However, in the presence of an operon in which there is strong evidence for some of the genes, the very presence of the gene in the operon is a strong indication that the gene shares in the process carried out by the operon. If the putative function is one expected to exist for the process in question and particularly if that function has been observed in the same operon in another species, then the annotation should be made. This type of evidence is inferred from the context of the gene in an operon, and therefore the evidence code is IGC "inferred from genomic context." ref_id: GO_REF:0000080 title: Representation of plant development as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the development of a plant structure as a biological process. The underlying equivalence axiom template is "'anatomical structure development' and 'results in development of' some P", where P is a plant anatomical entity (PO:0025131). ref_id: GO_REF:0000070 title: Representation of transmembrane transporter activity as molecular function in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the transmembrane transporter activity a chemical entity (ChEBI) as molecular function. This includes variants for secondary active transmembrane transporter activity (GO:0015291), uptake transmembrane transporter activity (GO:0015563), and ATPase activity, coupled to transmembrane movement of substances (GO:0042626). The underlying equivalence axiom template is "G and 'transports or maintains localization of' some X", where the genus G is either GO:0022857 (transmembrane transporter activity), GO:0015291, GO:0015563, or GO:0042626 depending on the variant. The variable X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000119 title: Automated transfer of experimentally-verified manual GO annotation data to mouse-human orthologs year: 2023 authors: The Gene Ontology Consortium abstract: The Alliance of Genome Resources (https://www.alliancegenome.org/) has procedures in place to establish orthology relationships ref_id: GO_REF:0000093 title: Representation for the degradation to or via a chemical as biological process in the Gene Ontology year: 2014 authors: GO ontology editors abstract: We have created a standard template for classes describing the degradation of a chemical entity to or via an other chemical entity as biological processes. The underlying equivalence axiom templates are "GO:0009056 and 'has input' some S and 'has output' some T" (catabolism to) and "GO:0009056 and 'has input' some S and 'has intermediate' some I" (catabolism via), where S,T, and I are chemical entities (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000047 title: Gene Ontology annotation based on absence of key sequence residues. year: 2012 authors: GO curators abstract: This describes a method for supplying a NOT-qualified, IKR-evidenced GO annotation to a gene product, when general sequence homology considerations would suggest a function or location, or a role in a biological process, but where a curator has determined that the absence of key sequence residues, known to be required for an expected activity or location, indicating the gene product is unlikely to be able to carry out the implied activity, involvement in a process or cellular component location. This reference should only be used used when an IKR-evidenced annotation is made based on curator judgement from manually reviewing the sequence of the gene product and where no publication can be found to support the curators conclusion. It is preferable to cite a peer-reviewed publication (such as a PubMed identifier) for IKR-evidenced annotations whenever possible. Curators will have carefully reviewed the sequence of the annotated protein, and established that the key residues known to be required for an expected activity or location are not present. Inclusion of an identifier in the 'with/from' field, that highlights to the user the lacking residues(e.g. an alignment, domain or rule identifier) is absolutely required when annotating to IKR with this GO_REF. Documentation on the GOC website provides more details on the correct use of the IKR evidence code. ref_id: GO_REF:0000108 title: Automatic assignment of GO terms using logical inference, based on on inter-ontology links. year: 2016 authors: GOA curators abstract: GO terms are automatically assigned based on inter-ontology links to generate inferred annotations. Annotations from Molecular Function to Biological Process can be propagated, as well as between Biological Process and Cellular Component. Annotations that are created using this inference method receive either the evidence code ECO:0000366 (evidence based on logical inference from automatic annotation used in automatic assertion) or ECO:0000364 (evidence based on logical inference from manual annotation used in automatic assertion), depending on whether the source annotation has a manual or automatic evidence code. Both of these codes map up to the GO Inferred from Electronic Annotation (IEA) evidence code. ref_id: GO_REF:0000033 title: Annotation inferences using phylogenetic trees year: 2010 authors: Marc Feuermann, Huaiyu Mi, Pascale Gaudet, Dustin Ebert, Anushya Muruganujan, Paul Thomas abstract: The Phylogenetic ANnotation using Gene Ontology (PAN-GO) method annotates evolutionary trees from the PANTHER database with GO terms describing molecular function, biological process and cellular component. The GO terms are manually selected by a curator and used to annotate ancestral genes in the phylogenetic tree using the evidence code IBA (Inferred from Biological Ancestor). All supporting annotations must be based on experimental data from the scientific literature. The PAN-GO annotations are fully traceable from the data in the 'with/from' column of the annotation, which provides the PANTHER node ID (PTN) from which the annotation is derived, as well as all descendants sequences that support the annotation of the ancestral node. ref_id: GO_REF:0000097 title: Gene Ontology annotation based on personal communication to FlyBase year: 2014 authors: FlyBase abstract: FlyBase occasionally makes GO annotations based on information that has been sent to us directly by researchers as a personal communication to FlyBase. In each case, the full details of the communication including any associated data and analyses are recorded in a FlyBase publication (FBrf) available from our website (http://flybase.org). ref_id: GO_REF:0000036 title: Manual annotations that require more than one source of functional data to support the assignment of the associated GO term year: 2011 authors: GO Annotation working group abstract: The Gene Ontology Consortium uses the IC (Inferred by Curator) evidence code when an annotation cannot be supported by any direct evidence, but can be inferred by GO annotations that have been annotated to the same gene/gene product identifier in conjunction with the curator's knowledge of biology (supporting GO annotations must not be IC-evidenced). In many cases an IC-evidenced annotation simply applies the same reference that was used in the supporting GO annotation. The use of IC evidence code in an annotation with reference GO_REF:0000036 signifies a curator inferred the GO term based on evidence from multiple sources of evidence/GO annotations. The 'with/from' field in these annotations will therefore supply more than one GO identifier, obtained from the set of supporting GO annotations assigned to the same gene/gene product identifier which cite publicly-available references. ref_id: GO_REF:0000085 title: Representation of cell apoptotic process as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the apoptotic process for a cell type as a biological process. The underlying equivalence axiom template is "'apoptotic process' and 'occurs in' some C", where C is a native cell (CL:0000003). ref_id: GO_REF:0000071 title: Representation of response to and cellular response to a chemical as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the response to and cellular response to a chemical entity (ChEBI) as a biological process. The underlying equivalence axiom templates are "GO:0050896 and 'has input' some X" (response to) and "GO:0070887 and 'has input' some X" (cellular response to), where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000091 title: Representation of cell migration as biological processes in the Gene Ontology year: 2014 authors: GO ontology editors abstract: We have created a standard template for classes describing the cell migration process for a cell type as a biological process. The underlying equivalence axiom template is "'cell migration' and 'alters_location_of' some C", where C is a native cell (CL:0000004). ref_id: GO_REF:0000015 title: Use of the ND evidence code for Gene Ontology (GO) terms. year: 2002 authors: GO Curators abstract: Direct annotations to any of the three root terms 'molecular function; GO:0003674', 'biological process; GO:0008150' or 'cellular component; GO:0005575' indicate that curators have found no data supporting an annotation to a more specific term, either in the literature and/or by sequence similarity for this gene or protein as of the date of the annotation. ref_id: GO_REF:0000109 title: Gene Ontology annotation based on curation of genome-wide subcellular localisation of proteins using fluorescent protein tagging in Trypanosoma brucei year: 2016 authors: TrypTag abstract: Trypanosomes are exquisitely structured cells in which protein localisation can be extremely informative for likely function. TrypTag is a project using expression of N- and C-terminal mNeonGreen fusion proteins from the endogenous loci to determine the subcellular localisation of every gene in the Trypanosoma brucei genome. GO Cellular Component terms are manually assigned by curators studying fluorescence microscope images of the resulting cells labelled with mNeonGreen fusion proteins. As trypanosomes are a pathogenic basal eukaryote, this will indicate likely function of both highly conserved eukaryote genes and parasite-specific genes. Resource URL: http://www.tryptag.org Protein subcellular localisation images can be viewed on the Tryptag website, e.g. http://www.tryptag.org?id=Tb927.8.1550 ref_id: GO_REF:0000073 title: Representation of import of a chemical as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the import of a chemical entity (ChEBI) as a biological process. The underlying equivalence axiom template is "GO:0006810 and 'imports' some X", where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000011 title: Hidden Markov Models (TIGR) year: 2003 authors: Michelle Gwinn, TIGR curators abstract: A Hidden Markov Model (HMM) is a statistical representation of patterns found in a data set. When using HMMs with proteins, the HMM is a statistical model of the patterns of the amino acids found in a multiple alignment of a set of proteins called the "seed". Seed proteins are chosen based on sequence similarity to each other. Seed members can be chosen with different levels of relationship to each other. They can be members of a superfamily (ex. ABC transporter, ATP-binding proteins), they can all share the same exact specific function (ex. biotin synthase) or they could share another type of relationship of intermediate specificity (ex. subfamily, domain). New proteins can be scored against the model generated from the seed according to how closely the patterns of amino acids in the new proteins match those in the seed. There are two scores assigned to the HMM which allow annotators to judge how well any new protein scores to the model. Proteins scoring above the "trusted cutoff" score can be assumed to be part of the group defined by the seed. Proteins scoring below the "noise cutoff" score can be assumed to NOT be a part of the group. Proteins scoring between the trusted and noise cutoffs may be part of the group but may not. One of the important features of HMMs is that they are built from a multiple alignment of protein sequences, not a pairwise alignment. This is significant, since shared similarity between many proteins is much more likely to indicate shared functional relationship than sequence similarity between just two proteins. The usefulness of an HMM is directly related to the amount of care that is taken in chosing the seed members, building a good multiple alignment of the seed members, assessing the level of specificity of the model, and choosing the cutoff scores correctly. In order to properly assess what functional relevance an above-trusted scoring HMM match has to a query, one must carefully determine what the functional scope of the HMM is. If the HMM models proteins that all share the same function then it is likely possible to assign a specific function to high-scoring match proteins based on the HMM. If the HMM models proteins that have a wide variety of functions, then it will not be possible to assign a specific function to the query based on the HMM match, however, depending on the nature of the HMM in question, it may be possible to assign a more general (family or subfamily level) function. In order to determine the functional scope of an HMM, one must carefully read the documentation associated with the HMM. The annotator must also consider whether the function attributed to the proteins in the HMM makes sense for the query based on what is known about the organism in which the query protein resides and in light of any other information that might be available about the query protein. After carefully considering all of these issues the annotator makes an annotation. ref_id: GO_REF:0000008 title: Gene Ontology annotation by the MGI curatorial staff, curated orthology year: 2001 authors: Mouse Genome Informatics scientific curators abstract: The sequence conservation that permits the establishment of orthology between mouse and rat or mouse and human genes is a strong predictor of the conservation of function for the gene product across these species. Therefore, in instances where a mouse gene product has not been functionally characterized, but its human or rat orthologs have, Mouse Genome Informatics (MGI) curators append the GO terms associated with the orthologous gene(s) to the mouse gene. Only those GO terms assigned by experimental determination to the ortholog of the mouse gene will be adopted by MGI. GO terms that are assigned to the ortholog of the mouse gene computationally (i.e. IEA), will not be transferred to the mouse ortholog. The evidence code represented by this citation is Inferred by Sequence Orthology (ISO). ref_id: GO_REF:0000107 title: Automatic transfer of experimentally verified manual GO annotation data to orthologs using Ensembl Compara. year: 2016 authors: GOA curators abstract: GO terms from a source species are projected onto one or more target species based on gene orthology obtained from Ensembl Compara. One-to-one, one-to-many and many-to-many orthology relations and anntations are transferred between orthologs that have at least a 40% peptide identity to each other. Only GO annotations with evidence codes ECO:0000314 (IDA), ECO:0000270 (IEP), ECO:0000316 (IGI), ECO:0000315 (IMP), and ECO:0000353 (IPI), or their descendants, are transferred; annotations with a 'NOT' qualifier are not transferred, and neither are annotations to GO:0005515 (protein binding). Annotations that are transferred using this method receive the evidence code ECO:0000265 (sequence orthology evidence used in automatic assertion), which maps up to the GO Inferred from Electronic Annotation (IEA) evidence code. The model organism database identifier of the annotation source will be indicated in the 'With' column of the GOA association file. ref_id: GO_REF:0000061 title: Representation of a molecular function involved in a biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing molecular function involved in other biological processes. The underlying equivalence axiom template is "P and 'part_of' some W", where P is a molecular function and W is a biological processes. ref_id: GO_REF:0000067 title: Representation of binding to a chemical entity as molecular function in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the binding to a chemical entity (ChEBI) as a molecular function. The underlying equivalence axiom template is "GO:0005488 and 'has input' some X", where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000118 title: TreeGrafter-generated GO annotations year: 2023 authors: Haiming Tang, Dustin Ebert, Matthias Blum, Robert Finn, Paul Thomas abstract: TreeGrafter is a software tool for annotating protein sequences using pre-annotated PANTHER phylogenetic trees. TreeGrafter takes an input query protein sequence, finds the best matching homologous family, and then grafts it to the best location in the tree. It then annotates the query sequence by propagating annotations from the appropriate ancestral node(s) in the reference tree, which were manually annotated using the PAN-GO method (see GOREF_0000033). This method is integrated into InterProScan, which produces annotations to millions of genes across tens of thousands of organisms. ref_id: GO_REF:0000054 title: Gene Ontology annotation based on curation of intracellular localizations of expressed fusion proteins in living cells. year: 2013 authors: LIFEdb abstract: LIFEdb is a database that was created to manage the experimental data produced by the German Cancer Research Institute (DKFZ) and its collaborators, from work on cDNAs contained in the German cDNA Consortium collection.
A novel cloning technology was used to rapidly generate N- and C-terminal green fluorescent protein fusions of cDNAs to examine the intracellular localizations of expressed fusion proteins in living cells. GO Cellular Component terms are manually assigned by curators studying fluorescence microscope images of cells labelled with GFP-fused cDNAs. Protein coding regions of novel full length cDNAs are tagged with the coding sequence of the green fluorescent protein, the fusion proteins are then expressed and analyzed for their subcellular localization.
Prior to February 2013, all LIFEdb annotations were referenced by PMID: 11256614 (Simpson et al. 2000 EMBO Rep. 1:287-292), a paper describing the protein subcellular localization pilot study and methodology used by LIFEdb. However, it has been decided that these annotations are more correctly described by a GO reference.
Resource URL: http://www.dkfz.de/en/mga/Groups/LIFEdb-Database.html
Protein subcellular localization images can be viewed on the LIFEdb website, http://www.dkfz.de/gpcf/lifedb.php ref_id: GO_REF:0000024 title: Manual transfer of experimentally-verified manual GO annotation data to orthologs by curator judgment of sequence similarity. year: 2011 authors: AgBase, BHF-UCL, Parkinson's UK-UCL, dictyBase, HGNC, Roslin Institute, FlyBase and UniProtKB curators. abstract: Method for transferring manual annotations to an entry based on a curator's judgment of its similarity to a putative ortholog that has annotations that are supported with experimental evidence. Annotations are created when a curator judges that the sequence of a protein shows high similarity to another protein that has annotation(s) supported by experimental evidence (and therefore display one of the evidence codes EXP, IDA, IGI, IMP, IPI or IEP). Annotations resulting from the transfer of GO terms display the 'ISS' evidence code and include an accession for the protein from which the annotation was projected in the 'with' field (column 8). This field can contain either a UniProtKB accession or an IPI (International Protein Index) identifier. Only annotations with an experimental evidence code and which do not have the 'NOT' qualifier are transferred. Putative orthologs are chosen using information combined from a variety of complementary sources. Potential orthologs are initially identified using sequence similarity search programs such as BLAST. Orthology relationships are then verified manually using a combination of resources including sequence analysis tools, phylogenetic and comparative genomics databases such as Ensembl Compara, INPARANOID and OrthoMCL, as well as other specialised databases such as species-specific collections (e.g. HGNC's HCOP). In all cases curators check each alignment and use their experience to assess whether similarity is considered to be strong enough to infer that the two proteins have a common function so that they can confidently project an annotation. While there is no fixed cut-off point in percentage sequence similarity, generally proteins which have greater than 30% identity that covers greater than 80% of the length of both proteins are examined further. For mammalian proteins this cut-off tends to be higher, with an average of 80% identity over 90% of the length of both proteins. Strict orthologs are desirable but not essential. In general, when there is evidence of multiple paralogs for a single species, annotations using less specific GO terms are transferred to the paralogs, however, annotations using more specific GO terms may be transferred to the most similar paralog in each species, this decision is taken on a case by case basis and may be influenced by statements by researchers in the field. Further detailed information on this procedure, including how ISS annotations are made to protein isoforms, can be found at: http://www.ebi.ac.uk/GOA/ISS_method.html. ref_id: GO_REF:0000115 title: Automatic Gene Ontology annotation of non-coding RNA sequences through association of Rfam records with GO terms year: 2018 authors: RNAcentral (1). (1) European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, United Kingdom abstract: Rfam (http://rfam.org, PMID:29112718) is a database of non-coding RNA families which are manually ref_id: GO_REF:0000003 title: Gene Ontology annotation based on Enzyme Commission mapping year: 2001 authors: GOA curators, MGI curators abstract: Transitive assignment using Enzyme Commission identifiers. This method is used for any database entry, such as a protein record in UniProtKB or TrEMBL, that has had an Enzyme Commission number assigned. The corresponding GO term is determined using the EC cross-references in the GO molecular function ontology. Also see Hill et al., Genomics (2001) 74:121-128. The mapping file is available at http://www.geneontology.org/external2go/ec2go. ref_id: GO_REF:0000028 title: Criteria for IDA, IEP, ISS, IGC, RCA, and IEA assignment in PAMGO_MGG year: 2008 authors: PAMGO_MGG curators abstract: This GO reference describes the criteria used in assigning the evidence codes of IDA (ECO:0000314), IEP (ECO:0000270), ISS (ECO:0000250), IGC (ECO_0000317), RCA (ECO:0000245) and IEA (ECO:0000501) to annotate gene products from PAMGO_MGG. Standard BLASTP from NCBI was used (http://www.ncbi.nih.gov/blast) to iteratively search reciprocal best hits and thus identify orthologs between predicted proteins of Magnaporthe grisea and GO proteins from multiple organisms with published association to GO terms. The alignments were manually reviewed for those hits with e-value equal to zero and with 80% or better coverage of both query and subject sequences, and for those hits with e<=10^-20, pid >=35 and sequence coverage >=80%. Furthermore, experimental or reviewed data from literature and other sources were incorporated into the GO annotation. IDA was assigned to an annotation if normal function of its gene was determined through transfections into a cell line and overexpression. IEP was assigned to an annotation if according to microarray experiments, its gene was upregulated in a biological process and the fold change was equal to or bigger than 10, or if according to Massively Parallel Signature Sequencing (MPSS), its gene was upregulated only in a certain biological process and the fold change was equal to or bigger than 10. ISS was assigned to an annotation if the entry at the With_column was experimentally characterized and the pairwise alignments were manually reviewed. IGC was assigned to an annotation if it based on comparison and analysis of gene location and structure, clustering of genes, and phylogenetic reconstruction of these genes. RCA was assigned to an annotation if it based on integrated computational analysis of whole genome microarray data, and matches to InterPro, pfam, and COG etc. IEA was assigned to an annotation if its function assignment based on computational work, and no manual review was done. ref_id: GO_REF:0000069 title: Representation of transmembrane transport of a chemical as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the transmembrane transport of a chemical entity (ChEBI) as a biological process. The underlying equivalence axiom template is "GO:0055085 and 'transports or maintains localization of' some X", where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000076 title: Representation of transport or vesicle-mediated transport from cell component to cell component as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the transport or vesicle-mediated transport from cellular component to cellular component as a biological process. The underlying equivalence axiom templates are "GO:0006810 and 'has_target_start_location' some F and 'has_target_end_location' some T" (transport) and "GO:0016192 and 'has_target_start_location' some F and 'has_target_end_location' some T" (vesicle-mediated transport), where F and T are a cellular components. ref_id: GO_REF:0000105 title: Gene Ontology annotation of transfer RNAs based on tRNAscan-SE analysis of the Drosophila melanogaster genome (2002). year: 2016 authors: FlyBase abstract: Gene Ontology annotation based on predicted cytoplasmic tRNAs using tRNAscan-SE analysis (doi: 10.1093/nar/25.5.0955) of the Drosophila melanogaster genome (2002). Annotations have been reviewed by FlyBase (2015) and found to be consistent when compared with the most recent tRNAscan-SE analysis of the genome (http://gtrnadb.ucsc.edu/genomes/eukaryota/Dmela6/). ref_id: GO_REF:0000027 title: BLAST search criteria for ISS assignment in PAMGO_GAT year: 2007 authors: PAMGO_GAT curators abstract: This GO reference describes the criteria used in assigning the evidence code of ISS via BLAST searches to annotate gene products from PAMGO_GAT. Standard BLASTP from NCBI was used (http://www.ncbi.nih.gov/blast) to query the non-redundant (NR) database. Hits are considered to be significant if the E-value is at or less than 10^-4. All other parameters are default according to http://www.ncbi.nih.gov/blast. ref_id: GO_REF:0000002 title: Comments year: 2001 authors: DDB, FB, MGI, GOA, ZFIN curators abstract: Transitive assignment of GO terms based on InterPro classification. For any database entry (representing a protein or protein-coding gene) that has been annotated with one or more InterPro domains, the corresponding GO terms are obtained from a translation table of InterPro entries to GO terms (interpro2go) generated manually by the InterPro team at EBI. The mapping file is available at http://www.geneontology.org/external2go/interpro2go. ref_id: GO_REF:0000064 title: Representation of cell components as part of other cell components in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing cell components as part of other cell components. The underlying equivalence axiom template is "P and 'part_of' some W", where P and W are cell components. ref_id: GO_REF:0000096 title: Automated transfer of experimentally-verified manual GO annotation data to close orthologs. year: 2014 authors: Mouse Genome Informatics scientific curators abstract: Mouse Genome Database (MGD), The HUGO Gene Nomenclature Committee (HGNC), and Rat Genome Database (RGD) have extensive procedures in place, overseen by expert curation, to establish orthology relationships between their genes. The Experimentally based annotations annotated by each group (IDA, IMP IPI, IGI, and EXP) are used to provide annotations to the respective mouse and rat orthologs, and given the ISO evidence code and an entry in the inferred_from field to indicate the orthologous entity. ref_id: GO_REF:0000059 title: Representation of regulation in the Gene Ontology (molecular function) year: 2013 authors: GO ontology editors abstract: We have created a standard template for the definition of classes for the regulation of a molecular function. This includes the definitions for positive and negative regulation. The equivalence axiom templates are "GO:0065007 and 'regulates' some X" (regulation), "GO:0065007 and 'negatively_regulates' some X" (negative regulation), and "GO:0065007 and 'positively_regulates' some X" (positive regulation), where X is a molecular function. ref_id: GO_REF:0000117 title: Electronic Gene Ontology annotations created by ARBA machine learning models year: 2021 authors: UniProt abstract: Association-Rule-Based Annotator (ARBA) predicts Gene Ontology (GO) terms among other types of functional annotation such as Protein Description (DE), Keywords (KW), Enzyme Commission numbers (EC), subcellular LOcation (LO), etc. For all annotation types, reviewed UniProtKB/Swiss-Prot records having manual annotations as reference data are used to perform the machine learning phase and generate prediction models. For GO terms, ARBA has an additional feature to augment reference data using the relations between GO terms in the GO graph. The data augmentation is based on adding more general annotations into records containing manual GO terms, which will result in richer reference data. The predicted GO terms are then propagated to all unreviewed UniProtKB/TrEMBL proteins that meet the conditions of ARBA models. GO annotations using this technique receive the evidence code Inferred from Electronic Annotation (IEA; ECO:0000501). ref_id: GO_REF:0000081 title: Representation of plant formation as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the formation of a plant structure as a biological process. The underlying equivalence axiom template is "'anatomical structure formation involved in morphogenesis' and 'results in formation of' some P", where P is a plant anatomical entity (PO:0025131). ref_id: GO_REF:0000101 title: Automated transfer of experimentally-verified GO annotation data to close orthologs year: 2015 authors: Sascha Steinbiss, GeneDB curators abstract: This reference is used to describe functional annotations transferred from one or more reference ("source") organisms to a newly annotated ("target") organism on the basis of ortholog cluster membership. In detail, predicted (e.g. by AUGUSTUS, see doi:10.1186/1471-2105-7-62) or transferred (e.g. via RATT, see doi:10:1093/nar/gkg1268) gene models in the target genome are translated and processed by OrthoMCL 1.4 together with reference protein sequences to produce clusters of gene products derived from orthologous genes. For each cluster, GO terms are automatically transferred from source products to the target gene products if they are experimentally verified (IDA (ECO:0000314), IMP (ECO:0000315), IPI (ECO:0000353), IGI (ECO:0000316), (EXP ECO:0000269). They are tagged with the ISO evidence code and the "with/from" is populated with the source feature references (e.g. "GeneDB:LmjF.28.0960"). OrthoMCL runs are done using the parameterization suggested in the OrthoMCL algorithm document (blastall -F 'm S' -e 1e-5). ref_id: GO_REF:0000110 title: Gene Ontology annotation of Drosophila melanogaster nuclear genes encoding proteins targeted to the mitochondrion. year: 2003 authors: FlyBase abstract: Gene Ontology annotation of Drosophila melanogaster nuclear genes encoding proteins targeted to the mitochondrion based on analysis by MitoDrome (http://mitodrome.ba.itb.cnr.it/) by comparison of human mitochondrial proteins available in SWISSPROT vs. the Drosophila genome, ESTs and cDNA sequences available in the FlyBase database (PMID:12520013). ref_id: GO_REF:0000065 title: Representation of transport of a chemical entity as a biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing transport of a chemical entity (ChEBI) as a biological process. The underlying equivalence axiom template is "GO:0006810 and 'transports or maintains localization of' some X", where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000087 title: Representation of protein localization and establishment of protein localization as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the protein localization and establishment of protein localization to a cellular component as a biological process. The underlying equivalence axiom templates are "GO:0008104 and 'has_target_end_location' some C" (protein localization) and "GO:0045184 and 'has_target_end_location' some C" (establishment of protein localization), where C is cellular component. ref_id: GO_REF:0000012 title: Pairwise alignment (TIGR) year: 2003 authors: Michelle Gwinn, TIGR curators abstract: Pairwise alignments are generated by taking two sequences and aligning them so that the maximum number of amino acids in each protein match, or are similar to, each other. Tools such as BLAST work by comparing a protein-of-interest individually with every protein in a database of known protein sequences and retaining only those matches with a high probability of being significant. Basic BLAST generates local alignments between proteins for regions of high similarity. Other pairwise alignment tools attempt to generate global (full-length) protein alignments. A tool called Blast_Extend_repraze (BER, http://ber.sourceforge.net) has some benefits over basic BLAST. Input into the BER tool includes the underlying DNA sequence for each protein as well as 300 nucleotides upstream and downstream of the predicted boundaries of the protein coding sequence. This allows annotators to see the DNA sequence that underlies the query protein as part of the alignment. In addition, the BER tool is able to look for continuation of regions of similarity through frameshifts and in-frame stop codons. If such regions are found the alignment is continued. BER searches are done in a two-step process: step one is a BLAST search against a non-redundant protein database, significant BLAST hits are stored in a mini-database for each query protein; step two is a modified Smith-Waterman alignment between the query and the proteins in its mini-database. In order to assess whether a given BER alignment is good enough to assert that the query shares the function of the match protein, one must look at a several factors. First of all, the match protein must itself be experimentally characterized in order to avoid transitive annotation errors. In addition, any residues or secondary structures known to be important for function in the match protein must be conserved in the query. The alignment should be visually inspected to look for any areas of lesser quality that might indicate the two proteins do not share the same function. Although it is impossible to set cutoff values for percent identity and length of match that will apply for every alignment, there are some guidelines. In general at least 40% identity that extends over the full lengths of both proteins is required in order to even consider functional equivalence. However, this percentage is highly dependent on the length and complexity of the proteins. 40% identity between two proteins 500 amino acids long is much more significant that 40% identity between two proteins that are only 100 amino acids long. Therefore, the annotator's experience and knowledge of what is considered significant for the organism and protein family in question is very important. Some sets of proteins are much more highly conserved than others and therefore tolerances for percent identity may have to be adjusted. Finally, the alignment must be considered in the context of what else is known about the query protein and the organism as a whole. ref_id: GO_REF:0000086 title: Representation of cell differentiation as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the differentiation process for a cell type as a biological process. The underlying equivalence axiom template is "GO:0030154 and 'results in acquisition of features of' some C", where C is a native cell (CL:0000003). ref_id: GO_REF:0000052 title: Gene Ontology annotation based on curation of immunofluorescence data year: 2013 authors: Human Protein Atlas abstract: GO Cellular Component terms are manually assigned by curators studying high resolution confocal microscopy images of immunohistochemically stained tissue. The methodology uses antibody-based proteomics which combines high-throughput generation of affinity-purified antibodies with protein profiling in a variety of cells and tissues. Further information on the annotation methods can be found at http://www.proteinatlas.org/about/assays+annotation
Annotations are only exported to the GO Consortium if the localizations are supported by literature, according to the following validation grading:
Supportive - Subcellular localization supported by literature.
1) One/multiple localizations supported by literature.
2) Multiple localizations partly supported (at least one) by literature.
3) One/multiple localizations in cytoplasm (i.e. Golgi, mitochondria, ER etc) with literature supporting cytoplasmic localization.
Prior to February 2013, all Human Protein Atlas annotations were referenced by PMID:18029348 (Barbe et al. 2008 Mol. Cell Proteomics. 7:499-508), a paper describing the protein localization pilot study and methodology used by the Human Protein Atlas. However, it has been decided that these annotations are more correctly described by a GO reference.
Resource URL: http://www.proteinatlas.org
Protein subcellular localization images can be viewed on the Human Protein Atlas website, e.g. http://www.proteinatlas.org/ENSG00000175899/summary#ifcelline ref_id: GO_REF:0000088 title: Representation of protein complex by molecular function in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes defining a protein complex by a molecular function as a cellular component. The underlying equivalence axiom template is "GO:0043234 and 'capable_of' some ?A", where A is a molecular function. ref_id: GO_REF:0000084 title: Representation of plant structural organization as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the structural organization of a plant structure as a biological process. The underlying equivalence axiom template is "'anatomical structure arrangement' and 'results in structural organization of' some P", where P is a plant anatomical entity (PO:0025131). ref_id: GO_REF:0000116 title: Automatic Gene Ontology annotation based on Rhea mapping. year: 2020 authors: GO Central curators, GOA curators, Rhea curators abstract: Rhea (https://www.rhea-db.org/, PMID:30272209) is an expert-curated knowledgebase of chemical and transport reactions of biological interest - and the standard for enzyme and transporter annotation in UniProtKB (PMID:31688925). Rhea uses the chemical dictionary ChEBI (Chemical Entities of Biological Interest) to describe reaction participants and their chemical transformations in a computationally tractable manner. GO terms corresponding to Rhea reactions are assigned a Rhea database cross-reference. The corresponding GO term is automatically applied to all UniProt entries annotated with a Rhea reaction. The mapping file is available at: http://current.geneontology.org/ontology/external2go/rhea2go. ref_id: GO_REF:0000068 title: Representation of metabolic triad (metabolism, catabolism, biosynthesis) as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes each describing the metabolism, catabolism, or biosynthesis of a chemical entity (ChEBI) as a process. The underlying equivalence axiom templates are "GO:0008152 and 'has participant' some X" (metabolism), "GO:0009056 and 'has input' some X" (catabolism), "GO:0009058 and 'has output' some X" and (biosynthesis), where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000072 title: Representation of chemical homeostasis and cellular chemical homeostasisl as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the homeostasis and cellular homeostasis for a chemical entity (ChEBI) as a biological process. The underlying equivalence axiom templates are "GO:0048878 and 'regulates level of' some X" (homeostasis) and "GO:0055082 and 'regulates level of' some X" (cellular homeostasis), where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000034 title: Phenoscape Skeletal Anatomy Jamboree year: 2010 authors: Brian K. Hall (Dalhousie University), Matthew Vickaryous (Ontario Veterinary College, University of Guelph), David Blackburn, University of Kansas; Wasila Dahdul, University of South Dakota and NESCent; Alexander Diehl, Mouse Genome Informatics (MGI); Melissa Haendel, Oregon Health Sciences University; John G. Lundberg, Department of Ichthyology, Academy of Natural Sciences, Philadelphia; Paula Mabee, Department of Biology, University of South Dakota; Martin Ringwald, Mouse Genome Informatics (MGI); Erik Segerdell, Oregon Health Sciences University; Ceri Van Slyke, Zebrafish Information Network (ZFIN); Monte Westerfield, Zebrafish Information Network (ZFIN) and Institute of Neuroscience, University of Oregon. abstract: Skeletal cell terms and relationships were added and revised at the Skeletal Anatomy Jamboree held by Phenoscape (NSF grant BDI-0641025) and hosted by the National Evolutionary Synthesis Center (NESCent), April 9-10, 2010. ref_id: GO_REF:0000113 title: Gene Ontology annotation of human sequence-specific DNA binding transcription factors (DbTFs) based on the TFClass database year: 2018 authors: Marcio Luis Acencio (1), George Georghiou (2), Sandra Orchard (2), Liv Thommensen (1), Martin Kuiper (1) and Astrid Lægreid (1). (1) Norwegian University of Science and Technology (NTNU), Trondheim, Norway; (2) European Bioinformatics Institute (EBI), Hinxton, Cambridgeshire, United Kingdom abstract: The TFClass (http://tfclass.bioinf.med.uni-goettingen.de/index.jsf) database provides a comprehensive classification of mammalian DNA binding transcription factors (DbTFs) based on their DNA binding domains (DBDs) (PMID:29087517). TFClass classifies mammalian DbTFs by a five-level classification in which the four highest levels represent groups defined by structural and sequence similarities (superclass, class, family, subfamily, and genera) (more details at http://www.edgar-wingender.de/TFClass_schema.html). This classification is based on the combination of background knowledge of the molecular structural features of DBDs (PMID:9340487, PMID:23427989) and phylogenetic trees constructed via multiple sequence alignment with hierarchical clustering of manually validated DBDs and/or full-length protein sequences retrieved from UniProt (PMID:23427989, PMID:23180794, PMID:23427989). ref_id: GO_REF:0000051 title: S. pombe keyword mapping year: 2012 authors: PomBase curators abstract: Keywords derived from manually curated primary annotation, e.g. gene product descriptions, are mapped to GO terms. Annotations made by this method have the evidence code Non-traceable Author Statement (NAS), and are filtered from the PomBase annotation files wherever another annotation exists that is equally or more specific, and supported by experimental or manually evaluated comparative evidence (such as ISS and its subtypes). Formerly GOC:pombekw2GO. ref_id: GO_REF:0000079 title: Representation of assembly or disassembly of a cell component as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the assembly or disassembly of a cellular component as a biological process. The underlying equivalence axiom templates are "GO:0022607 and 'results_in_assembly_of' some C" (assembly) and "GO:0022411 and 'results_in_disassembly_of' some C" (disassembly), where C is a cellular component. ref_id: GO_REF:0000043 title: Gene Ontology annotation based on UniProtKB/Swiss-Prot keyword mapping year: 2012 authors: UniProt-GOA abstract: Transitive assignments using UniProtKB/Swiss-Prot keywords. The UniProtKB keyword controlled vocabulary contains 10 different categories of information to UniProtKB entries. Further information on the UniProtKB keyword resource can be found at https://www.uniprot.org/keywords/. ref_id: GO_REF:0000063 title: Representation of processes regulated by other regulating processes in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing processes regulated by other regulating processes. The underlying equivalence axiom template is "R and 'results_in' some P", where R is a biological process and P is a regulation of biological process subclass. ref_id: GO_REF:0000078 title: Representation for the transport or vesicle-mediated transport of a chemical from and/or to a cell component as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the transport or vesicle-mediated transport of a chemical entity (ChEBI) from and/or to a cellular component as a biological process. The underlying equivalence axiom templates are "GO:0006810 and 'transports or maintains localization of' some X [ and 'has_target_start_location' some F] [ and 'has_target_end_location' some T]" (transport) and "GO:0016192 and 'transports or maintains localization of' some X [ and 'has_target_start_location' some F] [ and 'has_target_end_location' some T]" (vesicle-mediated transport), where F and T are cellular components and X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000114 title: Manual transfer of experimentally-verified manual GO annotation data to homologous complexes by curator judgment of sequence, composition and function similarity year: 2018 authors: Birgit Meldal and Sandra Orchard (1). (1) European Bioinformatics Institute (EBI), Hinxton, Cambridgeshire, United Kingdom abstract: Method for transferring manual annotations to an entry based on a curator's judgment of its similarity to a putative homolog that has annotations that are supported with experimental evidence. Annotations are created when a curator judges that the sequence, composition and function of a complex shows high similarity to another complex that has annotation(s) supported by experimental evidence (and therefore display one of the evidence codes ECO:0000353 [IPI] or ECO:0005543). Annotations resulting from the transfer of GO terms display the ECO:0005610, ECO:0005544 or ECO:0005546 evidence codes and include an accession for the complex from which the annotation was projected in the 'with/from' field (column 8). This field MUST contain a Complex Portal accession identifier. Putative homologs are chosen using information combined from a variety of complementary sources. Potential homologs are initially identified using sequence similarity search programs such as BLAST. Homologous relationships are then verified manually using a combination of resources including sequence analysis tools, phylogenetic and comparative genomics databases such as Ensembl Compara, INPARANOID and OrthoMCL, as well as other specialised databases such as species-specific collections (e.g. HGNC's HCOP). In all cases curators check the alignments for each complex component and use their experience to assess whether similarity is considered to be strong enough to infer that the two proteins have a common function so that they can confidently project an annotation. While there is no fixed cut-off point in percentage sequence similarity, generally proteins which have greater than 70% identity that covers greater than 90% of the length of both proteins are examined further. Whilst we expect subunit composition to be conserved between closely related species, this is not an absolute rule and orthologous complexes may differ if a subunit cannot be traced in one species or is experimentally shown not to be present. When there is evidence of multiple paralogs for a single species, multiple variants of the complex can be inferred. ref_id: GO_REF:0000074 title: Representation of export of a chemical as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the export of a chemical entity (ChEBI) as a biological process. The underlying equivalence axiom template is "GO:0006810 and 'exports' some X", where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000044 title: Gene Ontology annotation based on UniProtKB/Swiss-Prot Subcellular Location vocabulary mapping, accompanied by conservative changes to GO terms applied by UniProt. year: 2012 authors: UniProt-GOA abstract: Transitive assignment of GO terms based on the UniProtKB/Swiss-Prot Subcellular Location vocabulary. UniProtKB Subcellular Location is a controlled vocabulary used to supply subcellular location information to UniProtKB entries in the SUBCELLULAR LOCATION lines. Terms from this vocabulary are annotated manually to UniProtKB/Swiss-Prot entries but are automatically assigned to UniProtKB/TrEMBL entries from the underlying nucleic acid databases and/or by the UniProt automatic annotation program. ref_id: GO_REF:0000022 title: Improving the representation of immunology in the biological process Ontology year: 2005 authors: Alison Deckhut Augustine (1), Alan Collmer (2), Judith A. Blake (3, 4), Candace W. Collmer (2, 3), Shane C. Burgess (5), Lindsay Grey Cowell (6), Jennifer I. Clark (3, 7), Bernard de Bono (7), Russell T. Collins (8), Alexander D. Diehl (3, 4), Michelle Gwinn Giglio (3, 9), Jamie A. Lee (10), Linda Hannick (3, 9), Jane Lomax (3, 7), Midori A. Harris (3, 7), Christopher J. Mungall (3, 11), David P. Hill (3, 4), Richard H. Scheuermann (10), Amelia Ireland (3, 7), Alessandro Sette (12) (1. NIAID, 2. Cornell University, 3. The GO Consortium, 4. Mouse Genome Informatics, 5. Mississippi State University, 6. Duke University, 7. EMBL-EBI, 8. University of Cambridge, 9. The Institute for Genomic Research, 10. U.T. Southwestern Medical Center, 11. HHMI, 12. La Jolla Institute for Allergy and Immunology) abstract: GO terms describing processes, functions, and cellular components related to the immune system have existed in the GO from its beginning and been used extensively in the annotation of gene products. However, particularly in the biological process ontology, the initial set of terms relating to immunology failed to cover the breadth of known immunological processes, and in many cases diverged from current usage and understanding in their names, definitions, and ontological placement. As part of a larger effort to improve the representation of immunology in the GO, a GO Content Meeting was held November 15-16, 2005, at The Institute for Genomic Research, to discuss improvements to representation of immunology in the biological process ontology of the GO. As a result of the meeting, a number of high level terms for immunological processes were created, an overall structure for immunologically related terms was established, and certain existing terms were renamed or redefined as well to bring them in line with current usage. ref_id: GO_REF:0000066 title: Representation of transport of a chemical entity as molecular function in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the transport of a chemical entity (ChEBI) as a molecular function. The underlying equivalence axiom template is "GO:0005215 and 'transports or maintains localization of' some X", where X is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341. ref_id: GO_REF:0000083 title: Representation of plant morphogenesis as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the morphogenesis of a plant structure as a biological process. The underlying equivalence axiom template is "'anatomical structure morphogenesis' and 'results in morphogenesis of' some P", where P is a plant anatomical entity (PO:0025131). ref_id: GO_REF:0000111 title: Gene Ontology annotations Inferred by Curator (IC) using at least one Inferred by Sequence Similarity (ISS) annotation to support the inference year: 2016 authors: TBD abstract: The Gene Ontology Consortium uses the IC (Inferred by Curator; ECO:0000305) evidence code when assignment of a GO term cannot be supported by direct experimental or sequence-based evidence, but can, based on a curator’s biological knowledge, be reasonably inferred from existing GO annotations to the same gene/gene product. Use of the IC evidence code with GO_REF:0000111 indicates that a curator inferred the GO term based on at least one supporting annotation with an 'Inferred from Sequence Similarity' (ISS; ECO:0000250) evidence code. Note that additional supporting annotations may be experimentally evidenced. When using GO_REF:0000111, the 'with/from' field must contain all GO identifiers used as supporting annotations. ref_id: GO_REF:0000095 title: Literature reference not indexed by PubMed year: 2014 authors: Mouse Genome Informatics scientific curators and FlyBase abstract: This article is not referenced in PubMed. Please see contributing data resource for details. ref_id: GO_REF:0000094 title: Representation of metazoan development as biological process in the Gene Ontology year: 2014 authors: GO ontology editors abstract: We have created a standard template for classes describing the development of a metazoan structure as a biological process. The underlying equivalence axiom template is "'anatomical structure development' and 'results in development of' some E", where E is a anatomical entity (UBERON:0001062). ref_id: GO_REF:0000089 title: Representation of single-organism and multi-organism biological processes in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the single-organism and multi-organism biological processes. The underlying equivalence axiom templates are "P and 'bearer_of' some PATO:0002487" (single-organism) and "P and 'bearer_of' some PATO:0002486" (multi-organism), where P is a biological process. ref_id: GO_REF:0000041 title: Gene Ontology annotation based on UniPathway vocabulary mapping. year: 2012 authors: UniProt-GOA abstract: Transitive assignment of GO terms based on the UniPathway pathway vocabulary. UniPathway is a manually curated resource of enzyme-catalyzed and spontaneous chemical reactions. It provides a hierarchical representation of metabolic pathways. Descriptions of the pathway(s) that a particular protein is involved in are included in UniProtKB records.
UniPathway data are cross-linked to existing pathway resources such as KEGG and MetaCyc. Further information on the UniPathway resource is available at http://www.unipathway.org/obiwarehouse/unipathway.
When a UniPathway pathway describes a concept that is within the scope of the Gene Ontology, it is investigated to determine whether it is appropriate to map the term to an equivalent term in GO. The mapping between UniPathway terms and GO terms is carried out manually. Definitions and hierarchies of the terms in the two resources are compared and the mapping generated will reflect the most correct correspondence. The translation table between GO terms and UniPathway pathways is maintained by the UniPathway team and is available at http://www.grenoble.prabi.fr/dev/obiwarehouse/download/unipathway/public/unipathway2go.tsv. ref_id: GO_REF:0000060 title: Representation of processes involved in other process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing processes involved in other processes. The underlying equivalence axiom template is "P and 'part_of' some W", where P and W are biological processes. ref_id: GO_REF:0000021 title: Improving the representation of central nervous system development in the biological process ontology year: 2006 authors: Judith Blake (1, 2), William Bug (3), Rex Chisholm (1, 4), Jennifer Clark (1, 5), Erika Feltrin (6), Jacqueline Finger (2), David Hill (1, 2), Midori Harris (1, 5), Terry Hayamizu (2), Doug Howe (9), Maryanne Martone (7), Kathleen Millen (8), Francis Sele (4) (1. The Gene Ontology Consortium, 2. Mouse Genome Informatics, Bar Harbor, ME, 3. Drexel University, Philadelphia, PA, 4. Northwestern University, Chicago, IL, 5. EMBL-EBI, Hinxton, Cambridgeshire, UK, 6. The University of Padua, Padua, Italy, 7. The University of California at San Diego, San Diego, CA, 8. The University of Chicago, Chicago, IL, 9. The Zebrafish Information Network, University of Oregon, Eugene, OR) abstract: Current genetic and molecular studies in many model organisms are aimed at understanding formation and development of the nervous system. Up until this point, the GO has had a very shallow representation of processes pertaining to the nervous system. In June 2006, curators from MGI and ZFIN met with researchers studying central nervous system development to improve the representation of these processes in GO. In particular, emphasis was placed on three areas that are being addressed actively in current research: forebrain development, hindbrain development and neural tube development. This collaboration resulted in the addition of over 500 terms that reflect the development of the forebrain, the hindbrain, and the neural tube from the perspective of biological process and anatomical structure. ref_id: GO_REF:0000075 title: Representation of transport of a chemical into a cellular component as biological process in the Gene Ontology year: 2013 authors: GO ontology editors abstract: We have created a standard template for classes describing the transport of a chemical entity (ChEBI) into a cellular component as a biological process. The underlying equivalence axiom template is "GO:0006810 and 'has_target_end_location' some T and 'imports' some S", where T is a cellular component and S is a chemical entity (CHEBI:24431). The approach to combine GO and ChEBI has been described in the following publication: PMID:23895341.