Babel's tower revisited: a universal resource for cross-referencing across annotation databases is a research paper published in Bioinformatics (2006). On theSindex it has a DataRank of 3.4. It has been cited 51 times, with 47 citing works in its 1-hop citation network.
Abstract Motivation: Annotation databases are widely used as public repositories of biological knowledge. However, most of these resources have been developed by independent groups which used different designs and different identifiers for the same biological entities. As we show in this article, incoherent name spaces between various databases represent a serious impediment to using the existing annotations at their full potential. Navigating between various such name spaces by mapping IDs from one database to another is a very important issue which is not properly addressed at the moment. Results: We have developed a web-based resource, Onto-Translate (OT), which effectively addresses this problem. OT is able to map onto each other different types of biological entities from the following annotation databases: Swiss-Prot, TrEMBL, NREF, PIR, Gene Ontology, KEGG, Entrez Gene, GenBank, GenPept, IMAGE, RefSeq, UniGene, OMIM, PDB, Eukaryotic Promoter Database, HUGO Gene Nomenclature Committee and NetAffx. Currently, OT is able to perform 462 types of mappings between 29 different types of IDs from 17 databases concerning 53 organisms. Among these, over 300 types of translations and 15 types of IDs are not currently supported by any other tool or resource. On average, OT is able to correctly map between 96 and 99% of the biological entities provided as input. In terms of speed, sets of ∼20 000 IDs can be translated in <30 s, in most cases. Availability: OT is a part of Onto-Tools, which is freely available at Contact: [email protected]
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.593
From this paper's citation signal
Citation Network Contribution
2.8
From 34 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 17% comes from its base citations and 83% from the citation network (34 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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