What is Biological Database • Biological databases are libraries of life sciences information ,collected from scientific experiments, published literature, high- throughput experiment technology and computational analysis. A database for the bacterium Escherichia coli K-12 MG1655. The random selection was performed by assigning each potential article an integer from 1 to n, and then by using random.org’s sequence generator with the same range (https://www.random.org/sequences/). To evaluate resource usage within the captions of articles, we first processed the XML for each article within our full PMC corpus. CellTalkDB is the first comprehensive database of manually curated human and mouse ligand-receptor pairs with literature-supported evidence. We have applied bioNerDS to 713,634 full-text articles taken from the PubMed Central open-access corpus, as downloaded in December 2013. It is a topical endeavor for providing access to scholarly electronic resources including full-text and bibliographic databases in all the life science subject disciplines to the DBT Instit… The full dataset generated and used for this study is free to access and reuse under the CC0 license here: http://dx.doi.org/10.6084/m9.figshare.1281371. Evaluate claims that only very few resources make up the majority of mentions, while most resources are rarely (if ever) used [. These resources could reasonably be split into four distinct groups: These four resource types should perhaps be treated differently as they are likely to be reported in different ways within the literature. bioNerDS attempts to minimise false positive results by recognising negative keywords surrounding potential resource names, and by requiring a minimum positive threshold before a term is accepted. We used both Fβ = 1 measure (Fig 1a) and Area Under the ROC Curve (AUC; Fig 1b) [21]. From these 25 articles, only 5.6% of the total mentions, and 5.2% of the document level mentions, were not of usage. In … Articles are scanned and made available online within a few days. Text mining has become established as a process with which to extract named entities—e.g., gene names [10], chemical names [11], species names [12], etc.—from the expansive literature now available. of India, to enhance information resources in its research Institution. A database of citations and abstracts for biomedical literature from MEDLINE and additional life science journals. Bioconductor additionally shows an increase prior to about 2008, and there is a similar story for PDB. The other direction appears to be organised in an unusual way. No, Is the Subject Area "Machine learning" applicable to this article? To evaluate the extent of this occurrence within the literature, we have manually annotated our evaluation set of 25 full-text articles (see methods) to analyse resource usage verses “passing mention”. Bioinformatics - Bioinformatics - Goals of bioinformatics: The development of efficient algorithms for measuring sequence similarity is an important goal of bioinformatics. For more information about PLOS Subject Areas, click 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). We provide no graph for our medicine corpus, however, as the relative usage numbers within that corpus were understandably low for recognised bioinformatics resources. These terms aim to describe a journal’s overall scope, but are only assigned to MEDLINE journals. This evidence not only confirms the pattern Galperin first saw [24], but shows that it also holds across the entire domain of bioinformatics. If there is book or journal article that is not owned in our collection, we can borrow it from another library and deliver it to you, usually free of charge. We analyse the variability and ambiguity of bioinformatics resource names and compare Analysis was performed on the 60 full-text articles initially used for bioNerDS development and evaluation [9], which have been shuffled 10 times with a 10-fold cross-validation technique applied (Table 2). Yes There are relatively few differences between the sections in terms of resource names, although there are between corpora as previously discussed. Demonstrate skills to communicate scientific ideas to a variety of audiences 5. 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. https://doi.org/10.1371/journal.pone.0157989.g007. The analysis is statistically significant (p = 2.8661 * 10−115 with ANOVA test), and indicates Random Forest to be the best performing model (Precision: 0.80, Recall: 0.64, F-score: 0.71). This filter separately scores only accepted terms, upon which an additional filter may be customised and used. https://doi.org/10.1371/journal.pone.0157989.t005, https://doi.org/10.1371/journal.pone.0157989.t006, https://doi.org/10.1371/journal.pone.0157989.t007, https://doi.org/10.1371/journal.pone.0157989.t008. No, Is the Subject Area "Gene ontologies" applicable to this article? 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. The 2018 issue has a list of about 180 such databases and … We characterise various sub-domains (medicine, biology and bioinformatics) by splitting the corpus into these three sub-corpora. Purdue University is an equal access/equal opportunity university. We find a striking imbalance in resource usage with the top 5% of resource names (133 names) accounting for 47% of total usage, and over 70% of resources extracted being only mentioned once each. 18 no. Specifically, 70% of the resource names we extracted from our bioinformatics corpus are only mentioned once each, and this 70% makes up only 11% of the total document level mentions we extracted. In addition, it suggests that proteomics has favoured resources infrequently seen within the rest of the literature, and that statistical programs such as Stata and GraphPad Prism have focused roles separating them from much more prolific tools such as BLAST and PDB. The resulting top ten journals, counts and proportions are provided in Tables 9 and 10. The mean for the entire PMC corpus was 5.5 mentions per document. Although the majority of scientific publications are nowadays electronically available, keeping up to date with recent findings remains a tedious task hampered by the difficulty of accessing the relevant literature. PubMed additionally showed a significant usage increase, but has since levelled out. We have automatically extracted bioinformatics database and software mentions from the full-text literature in PMC. In particular, the high dimensional nature of many modelling tasks in bioinformatics, going from sequence analysis over microarray analysis to spectral analyses and literature mining has given rise to a wealth of feature selection techniques being presented in the field. This links directly to our previous limitation as mentions do not equate directly to usage, though there is likely to be a sufficient correlation in our data on resource mentions to enable us to have appropriate answers to our questions. The authors would like to acknowledge the assistance given by IT Services and the use of the Computational Shared Facility at The University of Manchester, which enabled us to process the full PMC corpus with bioNerDS. Best-practice provides a way to help identify the most appropriate method for a given task. Through a comparison in resource usage between the medicine, biology and bioinformatics domains, we conclude that bioinformatics’ reputation as a resource dependant domain (or resourceome) is well founded. 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”). This was implemented as bioNerDS frequently generated false positive results within the “long-tail” of resource mentions. While rapid change is necessary for progress, there is a danger that useful innovations may be lost, resulting in a necessity for “reinventing the wheel”. Aside from this, as would be expected, bioinformatics shows consistently higher numbers of resource mentions, followed by biology and then medicine. Keeping up-to-date with bioinformatics resources is consequently difficult, but a necessary part of modern data management and analysis within biology and medicine. We provide an audit of the resources contained within the biomedical literature, and a comparison of their relative usage, both over time and between the sub-disciplines of bioinformatics, biology and medicine. These results additionally outperform a previously published machine learning approach for resource recognition, which had reported a strict f-score of 63% (and an associated lenient f-score of 70%) [22]. here. No, Is the Subject Area "Software tools" applicable to this article? Such knowledge could be useful for determining best-practice, depending on the actual metrics used [8], and could enable targeted and sustainable support of important resources by providing an overview of resource usage within the published literature (especially where citations alone may not provide the full picture). This analysis helps confirm our previous assessment, that medicine does indeed use different resources to bioinformatics, with biology frequently sitting in the centre of these two other disciplines. https://doi.org/10.1371/journal.pone.0157989.g008. Yes Automatic detection and extraction of bioinformatics resources from the literature would avoid the limitations of manual curation. In addition, it separates PLoS ONE (up) and Acta Crystallography (down) from the others. No, Is the Subject Area "Computer software" applicable to this article? Modern data management and analysis, decision to publish, or preparation of the total extracted resources several focus. A particular issue with resource recognition, due to the vast number of rules matched expression... Analysis for each article within our full PMC corpus, as previously discussed mentions, with peak... Online within a few days so many resources are Central to much, if a quantitative comparison is made! 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