The Year of the Rat: The Rat Genome Database at 20: a multi-species knowledgebase and analysis platform.

Formed in late 1999, the Rat Genome Database (RGD, https://rgd.mcw.edu) will be 20 in 2020, the Year of the Rat. Because the laboratory rat, Rattus norvegicus, has been used as a model for complex human diseases such as cardiovascular disease, diabetes, cancer, neurological disorders and arthritis, among others, for >150 years, RGD has always been disease-focused and committed to providing data and tools for researchers doing comparative genomics and translational studies. At its inception, before the sequencing of the rat genome, RGD started with only a few data types localized on genetic and radiation hybrid (RH) maps and offered only a few tools for querying and consolidating that data. Since that time, RGD has expanded to include a wealth of structured and standardized genetic, genomic, phenotypic, and disease-related data for eight species, and a suite of innovative tools for querying, analyzing and visualizing this data. This article provides an overview of recent substantial additions and improvements to RGD's data and tools that can assist researchers in finding and utilizing the data they need, whether their goal is to develop new precision models of disease or to more fully explore emerging details within a system or across multiple systems.

FAIRshake: Toolkit to Evaluate the FAIRness of Research Digital Resources.

As more digital resources are produced by the research community, it is becoming increasingly important to harmonize and organize them for synergistic utilization. The findable, accessible, interoperable, and reusable (FAIR) guiding principles have prompted many stakeholders to consider strategies for tackling this challenge. The FAIRshake toolkit was developed to enable the establishment of community-driven FAIR metrics and rubrics paired with manual and automated FAIR assessments. FAIR assessments are visualized as an insignia that can be embedded within digital-resources-hosting websites. Using FAIRshake, a variety of biomedical digital resources were manually and automatically evaluated for their level of FAIRness.

Predicting instances of pathway ontology classes for pathway integration.

BACKGROUND: To improve the outcomes of biological pathway analysis, a better way of integrating pathway data is needed. Ontologies can be used to organize data from disparate sources, and we leverage the Pathway Ontology as a unifying ontology for organizing pathway data. We aim to associate pathway instances from different databases to the appropriate class in the Pathway Ontology. RESULTS: Using a supervised machine learning approach, we trained neural networks to predict mappings between Reactome pathways and Pathway Ontology (PW) classes. For 2222 Reactome classes, the neural network (NN) model generated 10,952 class recommendations. We compared against a baseline bag-of-words (BOW) model for predicting correct PW classes. A 5% subset of Reactome pathways (111 pathways) was randomly selected, and the corresponding class recommendations from both models were evaluated by two curators. The precision of the BOW model was higher (0.49 for BOW and 0.39 for NN), but the recall was lower (0.42 for BOW and 0.78 for NN). Around 78% of Reactome pathways received pertinent recommendations from the NN model. CONCLUSIONS: The neural predictive model produced meaningful class recommendations that assisted PW curators in selecting appropriate class mappings for Reactome pathways. Our methods can be used to reduce the manual effort associated with ontology curation, and more broadly, for augmenting the curators' ability to organize and integrate data from pathway databases using the Pathway Ontology.

Genetics and Genomics in Clinical Practice: The Views of Wisconsin Physicians.

INTRODUCTION: Decreasing costs and increased availability of genetic testing and genome sequencing mean many physicians will consider using these services over the next few years. Despite this promising future, some argue the present roadmap for translating genetics and genomics into routine clinical practice is unclear. OBJECTIVE: We conducted a pilot study to explore Wisconsin physicians' views, practices and educational desires regarding genetic and genomic testing. METHODS: Our study consists of an Internet survey (n=155) conducted in August and September 2015 and follow-up phone interviews with a portion of survey participants. Physicians of all specialties were invited to participate. Variables measured include physicians' general knowledge and experience regarding genetic and genomic testing, attitudes and perceptions toward these tests, testing intentions, and educational desires. Sociodemographic variables included gender, age, and medical specialty. RESULTS: In our exploratory survey of Wisconsin physicians, adult primary care providers (PCPs) lagged behind other providers in terms of familiarity and experience with genetic and genomic testing. PCPs in our sample were less likely than other physicians to feel their training in genetics and genomics is adequate. Physicians younger than 50 were more likely than older colleagues to feel their training is adequate. CONCLUSIONS: Our exploratory study suggests a gap in physician education and understanding regarding genomic testing, which is fast becoming part of personalized medical care. Future studies with larger samples should examine ways for physicians to close this gap, with special focus on the needs of PCPs.

Structural libraries of protein models for multiple species to understand evolution of the renin-angiotensin system.

The details of protein pathways at a structural level provides a bridge between genetics/molecular biology and physiology. The renin-angiotensin system is involved in many physiological pathways with informative structural details in multiple components. Few studies have been performed assessing structural knowledge across the system. This assessment allows use of bioinformatics tools to fill in missing structural voids. In this paper we detail known structures of the renin-angiotensin system and use computational approaches to estimate and model components that do not have their protein structures defined. With the subsequent large library of protein structures, we then created a species specific protein library for human, mouse, rat, bovine, zebrafish, and chicken for the system. The rat structural system allowed for rapid screening of genetic variants from 51 commonly used rat strains, identifying amino acid variants in angiotensinogen, ACE2, and AT1b that are in contact positions with other macromolecules. We believe the structural map will be of value for other researchers to understand their experimental data in the context of an environment for multiple proteins, providing pdb files of proteins for the renin-angiotensin system in six species. With detailed structural descriptions of each protein, it is easier to assess a species for use in translating human diseases with animal models. Additionally, as whole genome sequencing continues to decrease in cost, tools such as molecular modeling will gain use as an initial step in designing efficient hypothesis driven research, addressing potential functional outcomes of genetic variants with precompiled protein libraries aiding in rapid characterizations.