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All disciplines should follow the geosciences and demand best practice for publishing and sharing data, argue Shelley Stall and colleagues. All disciplines should follow the geosciences and demand best practice for publishing and sharing data, argue Shelley Stall and colleagues. Researchers repairs a broken GPS module at a research station in Greenland

We present the Polygenic Score (PGS) Catalog ( https://www.PGSCatalog.org ), an open resource of published scores (including variants, alleles and weights) and consistently curated metadata required for reproducibility and independent applications. The PGS Catalog has capabilities for user deposition, expert curation and programmatic access, thus providing the community with a platform for PGS dissemination, research and translation.

The aim of Jscatter is the processing of experimental data and physical models with the focus to enable the user to develop/modify their own models and use them within experimental data evaluation. The basic structures dataArray and dataList contain matrix-like data of different size including attributes to store corresponding metadata. The attributes are used in fit routines as parameters allowing multidimensional attribute dependent fitting. Several modules provide models mainly applied in neutron and X- ray scattering for small angle scattering (form factors and structure factors) and inelastic neutron scattering. The intention is to provide an environment with fit routines, data handling routines (based on NumPy arrays) and a model library to allow the user to focus onto user-written models for data analysis with the benefit of convenient documentation of scientific data evaluation in a scripting environment.

Background Thousands of research articles on neuroblastoma have been published over the past few decades; however, the heterogeneity and variable quality of scholarly data may challenge scientists or clinicians to survey all of the available information. Hence, holistic measurement and analyzation of neuroblastoma-related literature with the help of sophisticated mathematical tools could provide deep insights into global research performance and the collaborative architectonical structure within the neuroblastoma scientific community. In this scientometric study, we aim to determine the extent of the scientific output related to neuroblastoma research between 1980 and 2018. Methods We applied novel scientometric tools, including Bibliometrix R package, biblioshiny, VOSviewer, and CiteSpace IV for comprehensive science mapping analysis of extensive bibliographic metadata, which was retrieved from the Web of ScienceTM Core Collection database. Results We demonstrate the enormous proliferation of neuroblastoma research during last the 38 years, including 12,435 documents published in 1828 academic journals by 36,908 authors from 86 different countries. These documents received a total of 316,017 citations with an average citation per document of 28.35 ± 7.7. We determine the proportion of highly cited and never cited papers, “occasional” and prolific authors and journals. Further, we show 12 (13.9%) of 86 countries were responsible for 80.4% of neuroblastoma-related research output. Conclusions These findings are crucial for researchers, clinicians, journal editors, and others working in neuroblastoma research to understand the strengths and potential gaps in the current literature and to plan future investments in data collection and science policy. This first scientometric study of global neuroblastoma research performance provides valuable insight into the scientific landscape, co-authorship network architecture, international collaboration, and interaction within the neuroblastoma community.

Real‐world evidence (RWE) trials have a key advantage over conventional randomized controlled trials (RCTs) due to their potentially better generalizability. High generalizability of study results facilitates new biological insights and enables targeted therapeutic strategies. Random sampling of RWE trial participants is regarded as the gold standard for generalizability. Additionally, the use of sample correction procedures can increase the generalizability of trial results, even when using nonrandomly sampled real‐world data (RWD). This study presents descriptive evidence on the extent to which the design of currently planned or already conducted RWE trials takes sampling into account. It also examines whether random sampling or procedures for correcting nonrandom samples are considered. Based on text mining of publicly available metadata provided during registrations of RWE trials on clinicaltrials.gov, EU‐PAS, and the OSF‐RWE registry, it is shown that the share of RWE trial registrations with information on sampling increased from 65.27% in 2002 to 97.43% in 2022, with a corresponding increase from 14.79% to 28.30% for trials with random samples. For RWE trials with nonrandom samples, there is an increase from 0.00% to 0.95% of trials in which sample correction procedures are used. We conclude that the potential benefits of RWD in terms of generalizing trial results are not yet being fully realized.

In recent years, the explosion of genomic data and bioinformatic tools has been accompanied by a growing conversation around reproducibility of results and usability of software. However, the actual state of the body of bioinformatics software remains largely unknown. The purpose of this paper is to investigate the state of source code in the bioinformatics community, specifically looking at relationships between code properties, development activity, developer communities, and software impact. To investigate these issues, we curated a list of 1,720 bioinformatics repositories on GitHub through their mention in peer-reviewed bioinformatics articles. Additionally, we included 23 high-profile repositories identified by their popularity in an online bioinformatics forum. We analyzed repository metadata, source code, development activity, and team dynamics using data made available publicly through the GitHub API, as well as article metadata. We found key relationships within our dataset, including: certain scientific topics are associated with more active code development and higher community interest in the repository; most of the code in the main dataset is written in dynamically typed languages, while most of the code in the high-profile set is statically typed; developer team size is associated with community engagement and high-profile repositories have larger teams; the proportion of female contributors decreases for high-profile repositories and with seniority level in author lists; and, multiple measures of project impact are associated with the simple variable of whether the code was modified at all after paper publication. In addition to providing the first large-scale analysis of bioinformatics code to our knowledge, our work will enable future analysis through publicly available data, code, and methods. Code to generate the dataset and reproduce the analysis is provided under the MIT license at https://github.com/pamelarussell/github-bioinformatics. Data are available at https://doi.org/10.17605/OSF.IO/UWHX8.

Sharing, teaching and singing to bring people together on microscopy standards.

AimsWe aimed at developing a structured study protocol utilizing the bibliographic web-application science performance evaluation (SciPE) to perform comprehensive scientometric analyses.Methods and resultsMetadata related to publications derived from online databases were processed and visualized by transferring the information to an undirected multipartite graph and distinct partitioned sets of nodes. Also, institution-specific data were normalized and merged allowing precise geocoordinate positioning, to enable heatmapping and valid identification. As a result, verified, processed data regarding articles, institutions, journals, authors gender, nations and subject categories can be obtained. We recommend including the total number of publications, citations, the population, research institutions, gross domestic product, and the country-specific modified Hirsch Index and to form corresponding ratios (e.g., population/publication). Also, our approach includes implementation of bioinformatical methods such as heatmapping based on exact geocoordinates, simple chord diagrams, and the central implementation of specific ratios with plain visualization techniques.ConclusionThis protocol allows precise conduction of contemporaneous scientometric analyses based on bioinformatic and meta-analytical techniques, allowing to evaluate and contextualize scientific efforts. Data presentation with the depicted visualization techniques is mandatory for transparent and consistent analyses of research output across different nations and topics. Research performance can then be discussed in a synopsis of all findings.Graphic abstract