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== Enabling Machine-actionable Semantics for Comparative Analysis of Trait Evolution (SCATE) ==
 
== Enabling Machine-actionable Semantics for Comparative Analysis of Trait Evolution (SCATE) ==
  
Our objective with the [http://scate.phenoscape.org SCATE project] to create infrastructure that will provide comparative trait analysis tools easy access to algorithms powered by machine reasoning with the semantics of trait descriptions. Similar to how Google, IBM Watson, and others have enabled developers of smartphone apps to incorporate, with only a few lines of code, complex machine-learning and artificial intelligence capabilities such as sentiment analysis, we aim to demonstrate how easy access to knowledge computing opens up new opportunities for analysis, tools, and research in comparative trait analysis. As driving biological research questions, we focus on addressing three long-standing limitations in comparative studies of trait evolution: recombining trait data, modeling trait evolution, and generating testable hypotheses for the drivers of trait adaptation.
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Our objective with the [http://scate.phenoscape.org SCATE project] is to create infrastructure that will provide comparative trait analysis tools easy access to algorithms powered by machine reasoning with the semantics of trait descriptions. Similar to how Google, IBM Watson, and others have enabled developers of smartphone apps to incorporate, with only a few lines of code, complex machine-learning and artificial intelligence capabilities such as sentiment analysis, we aim to demonstrate how easy access to knowledge computing opens up new opportunities for analysis, tools, and research in comparative trait analysis. As driving biological research questions, we focus on addressing three long-standing limitations in comparative studies of trait evolution: recombining trait data, modeling trait evolution, and generating testable hypotheses for the drivers of trait adaptation.
  
 
More information about this project, including participating PIs and funding, can be found at its [http://scate.phenoscape.org project website].
 
More information about this project, including participating PIs and funding, can be found at its [http://scate.phenoscape.org project website].

Revision as of 18:58, 13 December 2019

Enabling Machine-actionable Semantics for Comparative Analysis of Trait Evolution (SCATE)

Our objective with the SCATE project is to create infrastructure that will provide comparative trait analysis tools easy access to algorithms powered by machine reasoning with the semantics of trait descriptions. Similar to how Google, IBM Watson, and others have enabled developers of smartphone apps to incorporate, with only a few lines of code, complex machine-learning and artificial intelligence capabilities such as sentiment analysis, we aim to demonstrate how easy access to knowledge computing opens up new opportunities for analysis, tools, and research in comparative trait analysis. As driving biological research questions, we focus on addressing three long-standing limitations in comparative studies of trait evolution: recombining trait data, modeling trait evolution, and generating testable hypotheses for the drivers of trait adaptation.

More information about this project, including participating PIs and funding, can be found at its project website.

Previous Phenoscape and precursor projects

Acknowledgments

The SCATE project has been funded by NSF collaborative grants DBI-1661456 (Duke University), DBI-1661529 (Virginia Tech), DBI-1661516 (University of South Dakota), and DBI-1661356 (UNC Chapel Hill and RENCI) from Sep 1, 2017 to Aug 31, 2020. The grant proposal text with references is publicly available: W. Dahdul, J.P. Balhoff, H. Lapp, P. M. Mabee, J. Uyeda, & T.J. Vision. (2017). Enabling machine-actionable semantics for comparative analyses of trait evolution. Zenodo. http://doi.org/10.5281/zenodo.885538.

The Phenoscape II project ("Ontology-enabled reasoning across phenotypes from evolution and model organisms") was funded by NSF collaborative grants DBI-1062404 and DBI-1062542 from July 1, 2011, to June 30, 2018, and supported by the National Evolutionary Synthesis Center (NESCent), NSF #EF-0905606. The original Project Description for this grant is available here.

These projects would not have been possible without the hard work of numerous contributors and the results obtained in the Linking Evolution to Genomics Using Phenotype Ontologies project, which was funded by NSF grant BDI-0641025 from June 1, 2007, to Jun 30, 2011, and was supported by NESCent, NSF #EF-0423641. This earlier project in turn arose from a NESCent Working Group led by Paula Mabee and Monte Westerfield, "Towards an Integrated Database for Fish Evolution."

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