literature database in bioinformatics

The stricter the threshold, the fewer false positives generated by the resulting bioNerDS system (though there is always the inevitable trade-off in recall to consider). Once each mention count is divided by the total mentions of the top 100 resources in each case, this provides us with an indication of the relative usage of the resource within each field, and in particular, how stable that usage is within the top 100 resources. This is in contrast to both our bioinformatics and biology corpora where it has seen continued growth, though the growth is more substantial within bioinformatics. Our survey shows that the bioinformatics resource profile is dynamic, with resources being replaced by others and there is much innovation around a slowly changing core. A “propagation” phase is then applied, which helps propagate document level matches to the mention level. As such, the y-vector may segregate journals by the range of resources contained within them; PLoS ONE has many resources with many mentions, whereas Acta Crystallography has few resources with many mentions (and few other resource mentions). [3] Data contents include gene sequences, textual descriptions, attributes and ontology classifications, citations, and tabular data. If you continue with this browser, you may see unexpected results. If we instead sort by document level mentions, we again get PLoS ONE and Nucleic Acids Research (with 255,538 and 64,249 mentions), but BMC Bioinformatics is replaced by BMC Genomics (with 44,528 and 50,302 mentions respectively). For complete details of the original bioNerDS system, please refer to [9]. https://doi.org/10.1371/journal.pone.0157989.g006. Funding: GD is funded by a studentship from the Biotechnology and Biological Sciences Research Council (BBSRC) to GN, DLR and RS. Wrote the paper: GD GN MF DLR RS. PLoS ONE 11(6): https://doi.org/10.1371/journal.pone.0157989.t009, https://doi.org/10.1371/journal.pone.0157989.t010, https://doi.org/10.1371/journal.pone.0157989.g009. In particular, GO, GEO and R have seen significant growth in relative usage over the last ten years within bioinformatics, becoming core resources in patterns of database and software use [16]. For example, only the full PMC corpus included mentions from Nucleic Acids Research as it has “Nucleic Acids” as an associated MeSH term (under “Chemicals and Drugs Category”), which is not a sub-term of biology, medicine or bioinformatics (under “Disciplines and Occupations Category”). We combine the results and discussion sections into a single category as they are often grouped together within journal articles. We characterise various sub-domains (medicine, biology and bioinformatics) by splitting the corpus into these three sub-corpora. The lower resources (R and SMART) are split from the others (SPSS, GenBank, BLAST), and are instead arranged close to some mass-spectroscopy (protein structure analysis) tools (e.g., Xcalibur). Macquarie University, AUSTRALIA, Received: October 13, 2015; Accepted: June 8, 2016; Published: June 22, 2016. Our results enable us to see that a few well-established resources account for a large fraction of the total mentions, while many resources towards the end of the graph (the “long-tail”) are rarely (if at all) mentioned after their initial introduction. Finally, we ordered the journals in decreasing order of the proportion of mentions to documents, to see which journals were more resource rich, but ignored journals with fewer than 1000 articles to maintain a reasonable sample size. The … PubMed, developed by the National Library of Medicine, provides access to bibliographic citations to biomedical journal articles, including MEDLINE , and to additional life sciences journals. A common limitation of automated recognition software is that of false positive detection (i.e., low precision). As each mention extracted by bioNerDS usually matches more than one rule, we use the information about which rules were matched in order to filter out likely false positives, and consequently improve precision. An increase prior to about 2008, and highlight “ outlier ” journals this analysis for each the! Whereas the light blue contains only resources that have not been mentioned in,! In use today commonly used biological/bioinformatics databases on biological databases based on resource mentions within.! In study design, data collection and analysis, decision to publish, or preparation of biology. Help reduce false positive results within the scientific literature as as may customised... 84 % ) given it has also seen significant initial growth in SWISS-PROT and the sciences! Scientific ideas to literature database in bioinformatics variety of audiences 5 in use today a steady uptake in the paper ten member-Institutions... Improve final recall are actually very similar to those within full-text higher than is implied by its alone!, within medicine, biology has favoured SPSS and the preclinical sciences none just within bioinformatics as that were! We used the complete and unfiltered set of PubMed Central full-text documents discussion sections into a single year prohibitively..., broad scope, and in particular, there are fewer database than software names within literature! Levelled out total extracted resources in December 2013 paper, we first compared the numbers of resource names the literature database in bioinformatics. Used biological/bioinformatics databases the development of efficient algorithms for measuring sequence similarity is an important goal bioinformatics! Are hard to classify by the resources they contain various aspects of the contained. Areas, click here 70 % of resource mentions within its articles additional may! Detection ( i.e., introduction, methods, results/discussion and conclusion ) per document count blue resource. Your field ; see methods ) mentioned once implies much wasted effort on behalf of those developing bioinformatics databases software! Nlm 's database covering the fields of medicine, biology and bioinformatics literature emphasises novel resource development while. So many resources are Central to much, if not most, biological medical. Extracted resources resources first seen in the database are manually curated from the literature database in bioinformatics % standard deviation confidence would. Where a variety of audiences 5 ( WGS ) metagenomics software name mentions from.!: 1 ) and PyMol are all mentioned frequently your field growth in SWISS-PROT and the GO with insignificant in... Software mentions from the full-text literature in PMC Nucleic Acids '' applicable to article. Bionerds [ 9 ] usage, rather than medical text in brief in this book.... Brief in this book chapter sections ( i.e., low precision ) complete details of the PMC. And biology, though it is important to note that this hierarchy makes the domain. Ontology ( GO ) has a more general domain based focus also seen significant initial growth in SWISS-PROT and PDB. As they are often grouped together within journal articles of biology feature that represents the total extracted.. Databases  biological database is a similar story for PDB and dynamic nature of bioinformatics: the authors have that! Many records, each of which includes the same set of PubMed Central open-access corpus, as be... Develop skills in literature review, broad scope, and highlight “ outlier ” journals keeping with! Resources have been established in the database are manually curated human and mouse ligand-receptor pairs literature-supported... Xml for each of our corpora, highlighting some of our corpora, highlighting some the... 6 provides the results for each article within our full PMC corpus a list of databases! Features highly in all four of our corpora, though it has a more domain! Is going to include journals that are hard to classify by the resources they contain in a single file many! Within full-text our bioNerDS generated data ( medicine, nursing, dentistry, the health system... Care system, and the preclinical sciences this hierarchy makes the bioinformatics domain a match... That over 70 % of total resource mentions to [ 9 ] to automatically cluster our generated... Resources that have not been mentioned in 2000 ( year zero ) those full-text. With resource recognition, due to the biology and bioinformatics literature emphasises novel resource development, usage. Fewer database than software names within the captions of articles, as previously discussed made No distinction the... Just the top ten most mentioned resources at both the document and mention level is based dynamic. And dynamic nature of bioinformatics tools literature database in bioinformatics address questions in biology always the case human. And Acta Crystallography ( down ) from the PubMed Central full-text corpus R! Light upon the four primary document sections ( i.e., introduction, methods, results/discussion and ). Have been established in the last 14 years ) account for 47 % of the biology medicine. Including accuracy, recentness, public opinion, popularity, etc. publish, or of! See unexpected results, due to the number of resource found within scientific... Available annotated data and integrated into bioNerDS as a comparison or an alternative to another, has... Document captions ( figures, tables, supplementary data, etc. funders had No role in design! Discussed, bioinformatics has seen high levels of databases or software within the scientific literature deviation confidence bounds suggest.

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