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Sökning: WFRF:(Kivioja Teemu)

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1.
  • Genereux, Diane P., et al. (författare)
  • A comparative genomics multitool for scientific discovery and conservation
  • 2020
  • Ingår i: Nature. - : NATURE RESEARCH. - 0028-0836 .- 1476-4687. ; 587:7833, s. 240-245
  • Tidskriftsartikel (refereegranskat)abstract
    • A whole-genome alignment of 240 phylogenetically diverse species of eutherian mammal-including 131 previously uncharacterized species-from the Zoonomia Project provides data that support biological discovery, medical research and conservation. The Zoonomia Project is investigating the genomics of shared and specialized traits in eutherian mammals. Here we provide genome assemblies for 131 species, of which all but 9 are previously uncharacterized, and describe a whole-genome alignment of 240 species of considerable phylogenetic diversity, comprising representatives from more than 80% of mammalian families. We find that regions of reduced genetic diversity are more abundant in species at a high risk of extinction, discern signals of evolutionary selection at high resolution and provide insights from individual reference genomes. By prioritizing phylogenetic diversity and making data available quickly and without restriction, the Zoonomia Project aims to support biological discovery, medical research and the conservation of biodiversity.
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2.
  • Gopalacharyulu, Peddinti V., et al. (författare)
  • Data integration and visualization system for enabling conceptual biology
  • 2005
  • Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 21 Suppl 1, s. i177-i185
  • Tidskriftsartikel (refereegranskat)abstract
    • MOTIVATION: Integration of heterogeneous data in life sciences is a growing and recognized challenge. The problem is not only to enable the study of such data within the context of a biological question but also more fundamentally, how to represent the available knowledge and make it accessible for mining.RESULTS: Our integration approach is based on the premise that relationships between biological entities can be represented as a complex network. The context dependency is achieved by a judicious use of distance measures on these networks. The biological entities and the distances between them are mapped for the purpose of visualization into the lower dimensional space using the Sammon's mapping. The system implementation is based on a multi-tier architecture using a native XML database and a software tool for querying and visualizing complex biological networks. The functionality of our system is demonstrated with two examples: (1) A multiple pathway retrieval, in which, given a pathway name, the system finds all the relationships related to the query by checking available metabolic pathway, transcriptional, signaling, protein-protein interaction and ontology annotation resources and (2) A protein neighborhood search, in which given a protein name, the system finds all its connected entities within a specified depth. These two examples show that our system is able to conceptually traverse different databases to produce testable hypotheses and lead towards answers to complex biological questions.
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