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Preprints have arrived. In increasing numbers, researchers across the life sciences are embracing the once-niche practice, shaking off decades of reluctance and posting hundreds of papers per week to preprint servers, sharing their findings with the community before embarking on the weary march through peer review. However, there are limited methods for individuals sifting through this avalanche of research to identify the preprints that are most relevant to their interests. Here, we describe , a website that indexes all preprints posted to , the largest preprint server in the life sciences, and allows users to filter and sort papers based on download metrics and Twitter activity over a variety of categories and time periods. In this work, we hope to make it easier for readers to find relevant research on bioRxiv and to improve the visibility of preprints currently being read and discussed online. [ABSTRACT FROM AUTHOR]

Developing new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through uniform resource locators (URLs) published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed “easy to install,” and 28% of the tools failed to be installed at all because of problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software. [ABSTRACT FROM AUTHOR]

The Internet is rapidly changing the way the results of academic research are communicated within communities and with the wider public. In a push to accelerate change and make the results of research immediately and freely available online for all to read and use, the European Commission, with support from a group of high-profile funders, has proposed a plan to influence the way academic research is published. Here, we discuss the likely impact of this plan on the publishing landscape, the potential benefits, and some possible unintended consequences. [ABSTRACT FROM AUTHOR]

Citation data have remained hidden behind proprietary, restrictive licensing agreements, which raises barriers to entry for analysts wishing to use the data, increases the expense of performing large-scale analyses, and reduces the robustness and reproducibility of the conclusions. For the past several years, the National Institutes of Health (NIH) Office of Portfolio Analysis (OPA) has been aggregating and enhancing citation data that can be shared publicly. Here, we describe the NIH Open Citation Collection (NIH-OCC), a public access database for biomedical research that is made freely available to the community. This dataset, which has been carefully generated from unrestricted data sources such as MedLine, PubMed Central (PMC), and CrossRef, now underlies the citation statistics delivered in the NIH iCite analytic platform. We have also included data from a machine learning pipeline that identifies, extracts, resolves, and disambiguates references from full-text articles available on the internet. Open citation links are available to the public in a major update of iCite (). [ABSTRACT FROM AUTHOR]

Science advances through rich, scholarly discussion. More than ever before, digital tools allow us to take that dialogue online. To chart a new future for open publishing, we must consider alternatives to the core features of the legacy print publishing system, such as an access paywall and editorial selection before publication. Although journals have their strengths, the traditional approach of selecting articles before publication (“curate first, publish second”) forces a focus on “getting into the right journals,” which can delay dissemination of scientific work, create opportunity costs for pushing science forward, and promote undesirable behaviors among scientists and the institutions that evaluate them. We believe that a “publish first, curate second” approach with the following features would be a strong alternative: authors decide when and what to publish; peer review reports are published, either anonymously or with attribution; and curation occurs after publication, incorporating community feedback and expert judgment to select articles for target audiences and to evaluate whether scientific work has stood the test of time. These proposed changes could optimize publishing practices for the digital age, emphasizing transparency, peer-mediated improvement, and post-publication appraisal of scientific articles. [ABSTRACT FROM AUTHOR]

PubMed is a free search engine for biomedical literature accessed by millions of users from around the world each day. With the rapid growth of biomedical literature—about two articles are added every minute on average—finding and retrieving the most relevant papers for a given query is increasingly challenging. We present Best Match, a new relevance search algorithm for PubMed that leverages the intelligence of our users and cutting-edge machine-learning technology as an alternative to the traditional date sort order. The Best Match algorithm is trained with past user searches with dozens of relevance-ranking signals (factors), the most important being the past usage of an article, publication date, relevance score, and type of article. This new algorithm demonstrates state-of-the-art retrieval performance in benchmarking experiments as well as an improved user experience in real-world testing (over 20% increase in user click-through rate). Since its deployment in June 2017, we have observed a significant increase (60%) in PubMed searches with relevance sort order: it now assists millions of PubMed searches each week. In this work, we hope to increase the awareness and transparency of this new relevance sort option for PubMed users, enabling them to retrieve information more effectively. [ABSTRACT FROM AUTHOR]

Blogs have stormed the Internet, providing an interactive medium for rapid and wide-reaching information dispersal. But is there a place for blogs in academia? [ABSTRACT FROM AUTHOR]

Reporting of the actual data in graphs and plots increases transparency and enables independent evaluation. On the other hand, data summaries are often used in graphs because they aid interpretation. To democratize state-of-the-art data visualization of raw data with a selection of statistical summaries, a freely available, open-source web app was written using R/shiny that uses the ggplot2 package for generating plots. Users can to choose how to display the data and which of the data summaries to add. In addition, the 95% confidence intervals (95CIs) can be added for visual inferences. By adjusting the visibility of the layers, the visualization of the raw data and their summaries can be tuned for optimal presentation and interpretation. The app is dubbed PlotsOfData and is available at . [ABSTRACT FROM AUTHOR]

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at . [ABSTRACT FROM AUTHOR]

Crowdfunding represents an attractive new option for funding research projects, especially for students and early-career scientists or in the absence of governmental aid in some countries. The number of successful science-related crowdfunding campaigns is growing, which demonstrates the public’s willingness to support and participate in scientific projects. Putting together a crowdfunding campaign is not trivial, however, so here is a guide to help you make yours a success. [ABSTRACT FROM AUTHOR]