160 research outputs found

    Constructing a biodiversity terminological inventory.

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    The increasing growth of literature in biodiversity presents challenges to users who need to discover pertinent information in an efficient and timely manner. In response, text mining techniques offer solutions by facilitating the automated discovery of knowledge from large textual data. An important step in text mining is the recognition of concepts via their linguistic realisation, i.e., terms. However, a given concept may be referred to in text using various synonyms or term variants, making search systems likely to overlook documents mentioning less known variants, which are albeit relevant to a query term. Domain-specific terminological resources, which include term variants, synonyms and related terms, are thus important in supporting semantic search over large textual archives. This article describes the use of text mining methods for the automatic construction of a large-scale biodiversity term inventory. The inventory consists of names of species, amongst which naming variations are prevalent. We apply a number of distributional semantic techniques on all of the titles in the Biodiversity Heritage Library, to compute semantic similarity between species names and support the automated construction of the resource. With the construction of our biodiversity term inventory, we demonstrate that distributional semantic models are able to identify semantically similar names that are not yet recorded in existing taxonomies. Such methods can thus be used to update existing taxonomies semi-automatically by deriving semantically related taxonomic names from a text corpus and allowing expert curators to validate them. We also evaluate our inventory as a means to improve search by facilitating automatic query expansion. Specifically, we developed a visual search interface that suggests semantically related species names, which are available in our inventory but not always in other repositories, to incorporate into the search query. An assessment of the interface by domain experts reveals that our query expansion based on related names is useful for increasing the number of relevant documents retrieved. Its exploitation can benefit both users and developers of search engines and text mining applications

    DYX1C1 is required for axonemal dynein assembly and ciliary motility

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    DYX1C1 has been associated with dyslexia and neuronal migration in the developing neocortex. Unexpectedly, we found that deleting exons 2–4 of Dyx1c1 in mice caused a phenotype resembling primary ciliary dyskinesia (PCD), a disorder characterized by chronic airway disease, laterality defects and male infertility. This phenotype was confirmed independently in mice with a Dyx1c1 c.T2A start-codon mutation recovered from an N-ethyl-N-nitrosourea (ENU) mutagenesis screen. Morpholinos targeting dyx1c1 in zebrafish also caused laterality and ciliary motility defects. In humans, we identified recessive loss-of-function DYX1C1 mutations in 12 individuals with PCD. Ultrastructural and immunofluorescence analyses of DYX1C1-mutant motile cilia in mice and humans showed disruptions of outer and inner dynein arms (ODAs and IDAs, respectively). DYX1C1 localizes to the cytoplasm of respiratory epithelial cells, its interactome is enriched for molecular chaperones, and it interacts with the cytoplasmic ODA and IDA assembly factor DNAAF2 (KTU). Thus, we propose that DYX1C1 is a newly identified dynein axonemal assembly factor (DNAAF4)
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