Comparing citation numbers between articles at two stages of a Model Organism Database curation workflow

Model organism databases (MODs) facilitate the connections between published research papers with genes and other biological information. MODs aim to make research data easier to access to the research community, especially for researchers relying on genetic data and other information about a specific species. This paper follows previous research (Beradini, et al. 2016) that attempted to use quantitative data to determine if and how literature curated by a MOD makes a difference to the access and reuse of the curated data. The research addresses whether articles that have been through the detailed curation process of a MOD are more likely to be cited when compared to 'similar' articles that are not curated. For this research, citations for articles curated by FlyBase, a MOD for genetic and molecular data for the Drosophilidae insect family, were compared with articles identified as having similar genetic and molecular data, but not yet given a detailed curation by FlyBase. In addition, citation counts from a larger set of articles retrieved through a title and keyword search for Drosophilidae are also compared.GM is supported by the FlyBase NIH/NHGRI grant U41HG000739 (N. Perrimon, Harvard University, PI; N.H. Brown, University of Cambridge, coPI)

Expansion of the Gene Ontology knowledgebase and resources

The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our continued focus is on improving the quality and utility of the GO resources, and we welcome and encourage input from researchers in all areas of biology. In this update, we summarize the current contents of the GO knowledgebase, and present several new features and improvements that have been made to the ontology, the annotations and the tools. Among the highlights are 1) developments that facilitate access to, and application of, the GO knowledgebase, and 2) extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. To learn more, visit http://geneontology.org/.National Institutes of Health/National Human Genome Research Institute [HG002273] awarded to the PI group formed by (alphabetically) Judith A. Blake, J. Michael Cherry, Suzanna E. Lewis, Paul W. Sternberg and Paul D. Thomas, as well as additional funding awarded to each participating institution. For more details please visit: http://geneontology.org/page/go-consortium-contributors-list. Funding for open access charge: National Institutes of Health/National Human Genome Research Institute [HG002273]

tagtog: interactive and text-mining-assisted annotation of gene mentions in PLOS full-text articles

The breadth and depth of biomedical literature are increasing year upon year. To keep abreast of these increases, FlyBase, a database for Drosophila genomic and genetic information, is constantly exploring new ways to mine the published literature to increase the efficiency and accuracy of manual curation and to automate some aspects, such as triaging and entity extraction. Toward this end, we present the 'tagtog' system, a web-based annotation framework that can be used to mark up biological entities (such as genes) and concepts (such as Gene Ontology terms) in full-text articles. tagtog leverages manual user annotation in combination with automatic machine-learned annotation to provide accurate identification of gene symbols and gene names. As part of the BioCreative IV Interactive Annotation Task, FlyBase has used tagtog to identify and extract mentions of Drosophila melanogaster gene symbols and names in full-text biomedical articles from the PLOS stable of journals. We show here the results of three experiments with different sized corpora and assess gene recognition performance and curation speed. We conclude that tagtog-named entity recognition improves with a larger corpus and that tagtog-assisted curation is quicker than manual curation. DATABASE URL: www.tagtog.net, www.flybase.org

Analysis of the Drosophila Compound Eye with Light and Electron Microscopy.

The Drosophila compound eye is composed of about 750 units, called ommatidia, which are arranged in a highly regular pattern. Eye development proceeds in a stereotypical fashion, where epithelial cells of the eye imaginal discs are specified, recruited, and differentiated in a sequential order that leads to the highly precise structure of an adult eye. Even small perturbations, for example in signaling pathways that control proliferation, cell death, or differentiation, can impair the regular structure of the eye, which can be easily detected and analyzed. In addition, the Drosophila eye has proven to be an ideal model for studying the genetic control of neurodegeneration, since the eye is not essential for viability. Several human neurodegeneration diseases have been modeled in the fly, leading to a better understanding of the function/misfunction of the respective gene. In many cases, the genes involved and their functions are conserved between flies and human. More strikingly, when ectopically expressed in the fly eye some human genes, even those without a Drosophila counterpart, can induce neurodegeneration, detectable by aberrant phototaxis, impaired electrophysiology, or defects in eye morphology and retinal histology. These defects are often rather subtle alteration in shape, size, or arrangement of the cells, and can be easily scored at the ultrastructural level. This chapter aims to provide an overview regarding the analysis of the retina by light and electron microscopy

Drosophila melanogaster: A Valuable Genetic Model Organism to Elucidate the Biology of Retinitis Pigmentosa.

Retinitis pigmentosa (RP) is a complex inherited disease. It is associated with mutations in a wide variety of genes with many different functions. These mutations impact the integrity of rod photoreceptors and ultimately result in the progressive degeneration of rods and cone photoreceptors in the retina, leading to complete blindness. A hallmark of this disease is the variable degree to which symptoms are manifest in patients. This is indicative of the influence of the environment, and/or of the distinct genetic makeup of the individual.The fruit fly, Drosophila melanogaster, has effectively proven to be a great model system to better understand interconnected genetic networks. Unraveling genetic interactions and thereby different cellular processes is relatively easy because more than a century of research on flies has enabled the creation of sophisticated genetic tools to perturb gene function. A remarkable conservation of disease genes across evolution and the similarity of the general organization of the fly and vertebrate photoreceptor cell had prompted research on fly retinal degeneration. To date six fly models for RP, including RP4, RP11, RP12, RP14, RP25, and RP26, have been established, and have provided useful information on RP disease biology. In this chapter, an outline of approaches and experimental specifications are described to enable utilizing or developing new fly models of RP

Model organism data evolving in support of translational medicine

Model organism databases (MODs) have been collecting and integrating biomedical research data for 30 years and were designed to meet specific needs of each model organism research community. The contributions of model organism research to understanding biological systems would be hard to overstate. Modern molecular biology methods and cost reductions in nucleotide sequencing have opened avenues for direct application of model organism research to elucidating mechanisms of human diseases. Thus, the mandate for model organism research and databases has now grown to include facilitating use of these data in translational applications. Challenges in meeting this opportunity include the distribution of research data across many databases and websites, a lack of data format standards for some data types, and sustainability of scale and cost for genomic database resources like MODs. The issues of widely distributed data and application of data standards are some of the challenges addressed by FAIR (Findable, Accessible, Interoperable, and Re-usable) data principles. The Alliance of Genome Resources is now moving to address these challenges by bringing together expertly curated research data from fly, mouse, rat, worm, yeast, zebrafish, and the Gene Ontology consortium. Centralized multi-species data access, integration, and format standardization will lower the data utilization barrier in comparative genomics and translational applications and will provide a framework in which sustainable scale and cost can be addressed. This article presents a brief historical perspective on how the Alliance model organisms are complementary and how they have already contributed to understanding the etiology of human diseases. In addition, we discuss four challenges for using data from MODs in translational applications and how the Alliance is working to address them, in part by applying FAIR data principles. Ultimately, combined data from these animal models are more powerful than the sum of the parts