LitDB - Keeping Track of Research Papers From Your Institute Made Simple

Background

In science peer-reviewed publications serve as an important indicator of scientific excellence and productivity. Therefore, every scientist and institution must carefully maintain and update records of their scientific publications. However, in most institutions and universities articles are often managed in a redundant file-based and non-central way. Whereas excellent reference management software packages such as Zotero, Endnote or Mendeley exist to manage bibliographies and references when writing scientific articles, we are not aware of any open source database solution keeping track of publication records from large scientific groups, entire institutions and/or universities.

Results

We here describe LitDB, a novel open source literature database solution for easy maintenance of publication lists assigned to various topics. In the last 2 years more than 50 users have been using LitDB at our research institute. The LitDB system is accessed via a web browser. Publications can be uploaded through direct exports from reference manager libraries or by entering PubMed IDs. Single users or user groups can track their citation counts, h-index and impact factor statistics and gain insights into the publication records of other users. It offers various visualization functions like coauthor networks and provides ways to organize publications from dedicated projects and user groups. The latter is in particular beneficial to manage publication lists of large research groups and research initiatives through a “crowd-sourcing” effort.

Conclusions

Keeping track of papers authored and published by a research group, institute or university is an important and non-trivial task. By using a centralized web-based platform for publication management such as LitDB the compilation of project- and group-related publication lists becomes easily manageable and it is less likely that papers are forgotten along the way.

     

How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads,Twitter Mentions,and Citations

We analyze the online response to the preprint publication of a cohort of 4,606 scientific articles submitted to the preprint database arXiv.org between October 2010 and May 2011. We study three forms of responses to these preprints: downloads on the arXiv.org site, mentions on the social media site Twitter, and early citations in the scholarly record. We perform two analyses. First, we analyze the delay and time span of article downloads and Twitter mentions following submission, to understand the temporal configuration of these reactions and whether one precedes or follows the other. Second, we run regression and correlation tests to investigate the relationship between Twitter mentions, arXiv downloads, and article citations. We find that Twitter mentions and arXiv downloads of scholarly articles follow two distinct temporal patterns of activity, with Twitter mentions having shorter delays and narrower time spans than arXiv downloads. We also find that the volume of Twitter mentions is statistically correlated with arXiv downloads and early citations just months after the publication of a preprint, with a possible bias that favors highly mentioned articles.     

Building protein diagrams on the web with the residue-based diagram editor RbDe

The residue-based diagram editor (RbDe) is web-based software that greatly simplifies the construction of schematic diagrams of proteins. Residue-based diagrams display the sequence of a given protein in the context of its secondary and tertiary structure. Such diagrams are frequently used to summarize mutations or sequence features, in the context of the overall topology of a protein. The initial version of RbDe was designed for transmembrane proteins and has enabled many users to create diagrams of large systems such as G protein-coupled receptors or transporters. We present an extended diagram editor that supports other families of proteins. Users can now import custom-diagram layouts, use them to render members of any protein family and generate high-quality output for publication purposes. RbDe is available free over the web, at http://icb.mssm.edu/crt/RbDe     

Ranking the whole MEDLINE database according to a large training set using text indexing

Background  

The MEDLINE database contains over 12 million references to scientific literature, with about 3/4 of recent articles including an abstract of the publication. Retrieval of entries using queries with keywords is useful for human users that need to obtain small selections. However, particular analyses of the literature or database developments may need the complete ranking of all the references in the MEDLINE database as to their relevance to a topic of interest. This report describes a method that does this ranking using the differences in word content between MEDLINE entries related to a topic and the whole of MEDLINE, in a computational time appropriate for an article search query engine.     

The spread of scientific information: insights from the web usage statistics in PLoS article-level metrics

The presence of web-based communities is a distinctive signature of Web 2.0. The web-based feature means that information propagation within each community is highly facilitated, promoting complex collective dynamics in view of information exchange. In this work, we focus on a community of scientists and study, in particular, how the awareness of a scientific paper is spread. Our work is based on the web usage statistics obtained from the PLoS Article Level Metrics dataset compiled by PLoS. The cumulative number of HTML views was found to follow a long tail distribution which is reasonably well-fitted by a lognormal one. We modeled the diffusion of information by a random multiplicative process, and thus extracted the rates of information spread at different stages after the publication of a paper. We found that the spread of information displays two distinct decay regimes: a rapid downfall in the first month after publication, and a gradual power law decay afterwards. We identified these two regimes with two distinct driving processes: a short-term behavior driven by the fame of a paper, and a long-term behavior consistent with citation statistics. The patterns of information spread were found to be remarkably similar in data from different journals, but there are intrinsic differences for different types of web usage (HTML views and PDF downloads versus XML). These similarities and differences shed light on the theoretical understanding of different complex systems, as well as a better design of the corresponding web applications that is of high potential marketing impact.     

BioThesaurus: a web-based thesaurus of protein and gene names

BioThesaurus is a web-based system designed to map a comprehensive collection of protein and gene names to protein entries in the UniProt Knowledgebase. Currently covering more than two million proteins, BioThesaurus consists of over 2.8 million names extracted from multiple molecular biological databases according to the database cross-references in iProClass. The BioThesaurus web site allows the retrieval of synonymous names of given protein entries and the identification of protein entries sharing the same names. AVAILABILITY: BioThesaurus is accessible for online searching at http://pir.georgetown.edu/iprolink/biothesaurus     

A survey of the availability of primary bioinformatics web resources

The explosive growth of the bioinformatics field has led to a large amount of data and software applications publicly available as web resources. However, the lack of persistence of web references is a barrier to a comprehensive shared access. We conducted a study of the current availability and other features of primary bioinforo matics web resources （such as software tools and databases）. The majority （95%） of the examined bioinformatics web resources were found running on UNIX/Linux operating systems, and the most widely used web server was found to be Apache （or Apache-related products）. Of the overall 1,130 Uniform Resource Locators （URLs） examined, 91% were highly available （more than 90% of the time）, while only 4% showed low accessibility （less than 50% of the time） during the survey. Furthermore, the most common URL failure modes are presented and analyzed.     

Reference bias in reports of drug trials.

Articles published before 1985 describing double blind trials of two or more non-steroidal anti-inflammatory drugs in rheumatoid arthritis were examined to see whether there was any bias in the references they cited. Althogether 244 articles meeting the criteria were found through a Medline search and through examining the reference lists of the articles retrieved. The drugs compared in the studies were classified as new or as control drugs and the outcome of the trial as positive or not positive. The reference lists of all papers with references to other trials on the new drug were then examined for reference bias. Positive bias was judged to have occurred if the reference list contained a higher proportion of references with a positive outcome for that drug than among all the articles assumed to have been available to the authors (those published more than two years earlier than the index article). Altogether 133 of the 244 articles were excluded for various reasons--for example, 44 because of multiple publication and 19 because they had no references. Among the 111 articles analysed bias was not possible in the references of 35 (because all the references gave the same outcome); 10 had a neutral selection of references, 22 a negative selection, and 44 a positive selection--a significant positive bias. This bias was not caused by better scientific standing of the cited articles over the uncited ones. Thus retrieving literature by scanning reference lists may produce a biased sample of articles, and reference bias may also render the conclusions of an article less reliable.     

Scopus database: a review

The Scopus database provides access to STM journal articles and the references included in those articles, allowing the searcher to search both forward and backward in time. The database can be used for collection development as well as for research. This review provides information on the key points of the database and compares it to Web of Science. Neither database is inclusive, but complements each other. If a library can only afford one, choice must be based in institutional needs.     

On the lifetime of bioinformatics web services

Web services are used through all disciplines in life sciences and the online landscape is growing by hundreds of novel servers annually. However, availability varies, and maintenance practices are largely inconsistent. We screened the availability of 2396 web tools published during the past 10 years. All servers were accessed over 133 days and 318 668 index files were stored in a local database. The number of accessible tools almost linearly increases in time with highest availability for 2019 and 2020 (∼90%) and lowest for tools published in 2010 (∼50%). In a 133-day test frame, 31% of tools were always working, 48.4% occasionally and 20.6% never. Consecutive downtimes were typically below 5 days with a median of 1 day, and unevenly distributed over the weekdays. A rescue experiment on 47 tools that were published from 2019 onwards but never accessible showed that 51.1% of the tools could be restored in due time. We found a positive association between the number of citations and the probability of a web server being reachable. We then determined common challenges and formulated categorical recommendations for researchers planning to develop web-based resources. As implication of our study, we propose to develop a repository for automatic API testing and sustainability indexing.     

GALT Protein Database, a Bioinformatics Resource for the Management and Analysis of Structural Features of a Galactosemia-related Protein and Its Mutants

We describe the GALT-Prot database and its related web-based application that have been developed to collect information about the structural and functional effects of mutations on the human enzyme galactose-1-phosphate uridyltransferase (GALT) involved in the genetic disease named galactosemia type Ⅰ. Besides a list of missense mutations at gene and protein sequence levels, GALT-Prot reports the analysis results of mutant GALT structures. In addition to the structural information about the wild-type enzyme, the database also includes structures of over 100 single point mutants simulated by means of a computational procedure, and the analysis to each mutant was made with several bioinformatics programs in order to investigate the effect of the mutations. The web-based interface allows querying of the database, and several links are also provided in order to guarantee a high integration with other resources already present on the web. Moreover, the architecture of the database and the web application is flexible and can be easily adapted to store data related to other proteins with point mutations. GALT-Prot is freely available at http://bioinformatica.isa.cnr.it/GALT/.     

Examining the Impact of the National Institutes of Health Public Access Policy on the Citation Rates of Journal Articles

PurposeTo examine whether National Institutes of Health (NIH) funded articles that were archived in PubMed Central (PMC) after the release of the 2008 NIH Public Access Policy show greater scholarly impact than comparable articles not archived in PMC.MethodsA list of journals across several subject areas was developed from which to collect article citation data. Citation information and cited reference counts of the articles published in 2006 and 2009 from 122 journals were obtained from the Scopus database. The articles were separated into categories of NIH funded, non-NIH funded and whether they were deposited in PubMed Central. An analysis of citation data across a five-year timespan was performed on this set of articles.ResultsA total of 45,716 articles were examined, including 7,960 with NIH-funding. An analysis of the number of times these articles were cited found that NIH-funded 2006 articles in PMC were not cited significantly more than NIH-funded non-PMC articles. However, 2009 NIH funded articles in PMC were cited 26% more than 2009 NIH funded articles not in PMC, 5 years after publication. This result is highly significant even after controlling for journal (as a proxy of article quality and topic).ConclusionOur analysis suggests that factors occurring between 2006 and 2009 produced a subsequent boost in scholarly impact of PubMed Central. The 2008 Public Access Policy is likely to be one such factor, but others may have contributed as well (e.g., growing size and visibility of PMC, increasing availability of full-text linkouts from PubMed, and indexing of PMC articles by Google Scholar).     

Rising Publication Delays Inflate Journal Impact Factors

Journal impact factors have become an important criterion to judge the quality of scientific publications over the years, influencing the evaluation of institutions and individual researchers worldwide. However, they are also subject to a number of criticisms. Here we point out that the calculation of a journal’s impact factor is mainly based on the date of publication of its articles in print form, despite the fact that most journals now make their articles available online before that date. We analyze 61 neuroscience journals and show that delays between online and print publication of articles increased steadily over the last decade. Importantly, such a practice varies widely among journals, as some of them have no delays, while for others this period is longer than a year. Using a modified impact factor based on online rather than print publication dates, we demonstrate that online-to-print delays can artificially raise a journal’s impact factor, and that this inflation is greater for longer publication lags. We also show that correcting the effect of publication delay on impact factors changes journal rankings based on this metric. We thus suggest that indexing of articles in citation databases and calculation of citation metrics should be based on the date of an article’s online appearance, rather than on that of its publication in print.     

Impact beyond the impact factor

The journal impact factor is an annually calculated number for each scientific journal, based on the average number of times its articles published in the two preceding years have been cited. It was originally devised as a tool for librarians and publishers to provide information about the citation performance of a journal as a whole, but over the last few decades it has increasingly been used to assess the quality of specific articles and the research performance of individual investigators, institutions, and countries. In addition to this clear abuse of the journal impact factor, several conceptual and technical issues limit its usability as a measure of journal reputation, especially when journals are compared across different fields. An author’s decision regarding the suitability of a scholarly journal for publication should, therefore, be based on the impact that this journal makes in the field of research, rather than on the journal impact factor.     

Growth and development of biofeedback: A bibliographic analysis

A computerized search was performed, and a bibliography was prepared on the subject of biofeedback covering the years from 1964 to 1985. Growth curves were produced for various publication media. The search produced references to 2,431 journal articles, 102 books, 79 popular magazine articles, and 551 doctoral dissertations. The journal articles were sorted according to the country of publication, language, and primary topic of the journal. Citations were found from 35 countries, written in 18 languages. All the media studied showed a period of rapid growth during the early to middle 1970s, but there was a tendency for leveling off or slight decline during the early 1980s. Publication of articles in medical journals has shown the greatest growth, and more articles are published yearly in medical journals than in journals of any other discipline or all specialty journals combined. Publication in psychological journals has shown a decline since 1977. Dental, nursing, and educational journals have shown a low rate of publication of biofeedback articles, indicating little or no growth.We thank Ken Hartman for his assistance in performing this study.     

Three options for citation tracking: Google Scholar,Scopus and Web of Science

Background

Researchers turn to citation tracking to find the most influential articles for a particular topic and to see how often their own published papers are cited. For years researchers looking for this type of information had only one resource to consult: the Web of Science from Thomson Scientific. In 2004 two competitors emerged – Scopus from Elsevier and Google Scholar from Google. The research reported here uses citation analysis in an observational study examining these three databases; comparing citation counts for articles from two disciplines (oncology and condensed matter physics) and two years (1993 and 2003) to test the hypothesis that the different scholarly publication coverage provided by the three search tools will lead to different citation counts from each.

Methods

Eleven journal titles with varying impact factors were selected from each discipline (oncology and condensed matter physics) using the Journal Citation Reports (JCR). All articles published in the selected titles were retrieved for the years 1993 and 2003, and a stratified random sample of articles was chosen, resulting in four sets of articles. During the week of November 7–12, 2005, the citation counts for each research article were extracted from the three sources. The actual citing references for a subset of the articles published in 2003 were also gathered from each of the three sources.

Results

For oncology 1993 Web of Science returned the highest average number of citations, 45.3. Scopus returned the highest average number of citations (8.9) for oncology 2003. Web of Science returned the highest number of citations for condensed matter physics 1993 and 2003 (22.5 and 3.9 respectively). The data showed a significant difference in the mean citation rates between all pairs of resources except between Google Scholar and Scopus for condensed matter physics 2003. For articles published in 2003 Google Scholar returned the largest amount of unique citing material for oncology and Web of Science returned the most for condensed matter physics.

Conclusion

This study did not identify any one of these three resources as the answer to all citation tracking needs. Scopus showed strength in providing citing literature for current (2003) oncology articles, while Web of Science produced more citing material for 2003 and 1993 condensed matter physics, and 1993 oncology articles. All three tools returned some unique material. Our data indicate that the question of which tool provides the most complete set of citing literature may depend on the subject and publication year of a given article.