Visualization is key for expanding and communicating knowledge to both specialized and broad audiences-after all, "a picture is worth a thousand words," right?That much has become clear during the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) outbreak when "Flatten the curve!" [1] turned into a catchier watchword than the usual "Wash your hands!," by referring to the related graphics rather than the health discourses themselves.Coronavirus Disease 2019 (COVID-19) visualizations, good and bad [2], became omnipresent in the public debates, with interactive and dynamic visualization platforms like Nextstrain [3] gaining a lot of popularity.We are now used to seeing graphs and charts in our everyday lives and creating them for scientific papers as part of research.Unfortunately, most of the time, classic visual representations are insufficient to effectively communicate data complexity, and as O'Donoghue puts it, "often dedicated communication approaches need to be developed to address specific data challenges, especially when conveying complex or unfamiliar ideas" [4].Given the gap between creating static figures and building a visualization tool from the ground up, it can be easy to get lost in this nontrivial journey.Our following 10 simple rules are dedicated to biologists and bioinformaticians who, while already being at the crossroads of many fields, want to venture further into the land of Data Visualization ("datavis" or "dataviz" for short).They combine tips and advice that we would have wanted when we first started our own journeys, gathered from our experiences in building genomic and/or datavis tools, and the time spent with related communities.Additionally, they address current challenges in computational biology and the needs of the community.We aim these rules at bioinfo-to-datavis novices looking for guidelines, particularly regarding genomics visualization tools, but experienced practitioners may find it useful to see them gathered in one place too.For better reading comfort, we organized the rules chronologically depending on when they would matter the most during a visualization tool's life cycle, starting with the design (Rules 1 to 5) then development (Rules 5 to 8-ish) phases until it is shared with the rest of the world.Please note, however, that they are still relevant during the whole gestation and that creating a visualization tool is rarely a fully linear process-it does not even end after the initial release, as continued development and support is a cyclic process to be sustained over the years.

Summary: The Genome Context Viewer is a visual data-mining tool that allows users to search across multiple providers of genome data for regions with similarly annotated content that may be aligned and visualized at the level of their shared functional elements. By handling ordered sequences of gene family memberships as a unit of search and comparison, the user interface enables quick and intuitive assessment of the degree of gene content divergence and the presence of various types of structural events within syntenic contexts. Insights into functionally significant differences seen at this level of abstraction can then serve to direct the user to more detailed explorations of the underlying data in other interconnected, provider-specific tools. Availability and implementation: GCV is provided under the GNU General Public License version 3 (GPL-3.0). Source code is available at https://github.com/legumeinfo/lis_context_viewer. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract Motivation: Heterogeneity of databases and software resources continues to hamper the integration of biological information. Top-down solutions are not feasible for the full-scale problem of integration across biological species and data types. Bottom-up solutions so far have not integrated, in a maximally flexible way, dynamic and interactive graphical-user-interface components with data repositories and analysis tools. Results: We present a component-based approach that relies on a generalized platform for component integration. The platform enables independently-developed components to synchronize their behavior and exchange services, without direct knowledge of one another. An interface-based data model allows the exchange of information with minimal component interdependency. From these interactions an integrated system results, which we call ISYS\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(^{TM}\) \end{document}. By allowing services to be discovered dynamically based on selected objects, ISYS encourages a kind of exploratory navigation that we believe to be well-suited for applications in genomic research. Availability: A ‘developer’s kit’ for creating software that uses the ISYS platform is available at www.ncgr.org/research/isys/devrel.html. It includes a more refined and fully documented version of the platform and a starting set of ISYS-ready components. Up-to-date descriptions of the ISYS project can be found at www.ncgr.org/research/isys. Contact: [email protected] * To whom correspondence should be addressed.

MOTIVATION: The nucleotide sequence databases are invaluable tools both for the private and the academic research communities, from the retrieval of sequences to homology searching. Several issues related to data quality, such as the existence of sequencing artifacts and errors, are facing the databases. We investigated a major source of these errors, i.e. the presence of vector-contaminated sequences. RESULTS: Using a panel of 180 vector polylinker sequences, we found 0.36% or 3029 vector-matching sequences in GenBank Release 95-96, with an average vector-matching length of 72 nucleotides. The number of vector-contaminated sequences has been growing with the database; however, the percent contamination has remained approximately constant at an average of 0.28% from 1982 to 1996. AVAILABILITY: Access to the database of vector polylinker sequences via sequence similarity searching is available at http://seqsim.ncgr.org/vector/ CONTACT: [email protected]