11 research outputs found

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Fly Cell Atlas: a single-nucleus transcriptomic atlas of the adult fruit fly

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    The fruit fly Drosophila melanogaster has served as a premier model organism for discovering fundamental and evolutionarily conserved biological mechanisms. Combining recent advances in single-cell sequencing with powerful fly genetic tools holds great promise for making further discoveries. Li et al. present a single-cell atlas of the entire adult fly that includes 580,000 cells and more than 250 annotated cell types. Cells from the head and body recapitulated cell types from 15 dissected tissues. In-depth analyses revealed rare cell types, cell-type-specific gene signatures, and sexual dimorphism. This atlas provides a resource for the Drosophila community to study genetic perturbations and diseases at single-cell resolution. —BA

    Fly Cell Atlas: a single-nucleus transcriptomic atlas of the adult fruit fly

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    The fruit fly Drosophila melanogaster has served as a premier model organism for discovering fundamental and evolutionarily conserved biological mechanisms. Combining recent advances in single-cell sequencing with powerful fly genetic tools holds great promise for making further discoveries. Li et al. present a single-cell atlas of the entire adult fly that includes 580,000 cells and more than 250 annotated cell types. Cells from the head and body recapitulated cell types from 15 dissected tissues. In-depth analyses revealed rare cell types, cell-type-specific gene signatures, and sexual dimorphism. This atlas provides a resource for the Drosophila community to study genetic perturbations and diseases at single-cell resolution. —BA

    Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly

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    For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae , that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type–related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution
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