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| − | ''This project arose from a [http://www.nescent.org/science/workinggroup.php NESCent Working Group] led by Paula Mabee and Monte Westerfield, "towards an Intregrated Database for Fish Evolution". [[Fish Evolution Working Group|Goals and summaries of the group]] are archived on this wiki.''
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| | + | * Try the [http://kb.phenoscape.org Phenoscape Knowledgebase]. Your feedback is welcome! |
| | + | * Check out the latest news on the [http://blog.phenoscape.org/ Phenoscape blog] |
| | + | * Learn more in one of our upcoming [[Training_and_Workshops | training workshops]] |
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| − | ==Linking Evolution to Genomics Using Phenotype Ontologies== | + | == Enabling Machine-actionable Semantics for Comparative Analysis of Trait Evolution == |
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| − | ===About this project===
| + | The current project of the Phenoscape team is Enabling Machine-actionable '''S'''emantics for '''C'''omparative '''A'''nalysis of '''T'''rait '''E'''volution (SCATE). |
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| − | What are the developmental and genetic bases of evolutionary differences in morphology across species? Currently it is difficult to approach this question due to a lack of computational tools that allow researchers to integrate developmental genetic and comparative morphological/anatomical data.
| + | The objective 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. |
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| − | We are addressing this by developing a database of evolutionarily variable morphological characters for a large clade of fishes (the Ostariophysi) and connecting this database to the large collection of mutant phenotypes in the [http://zfin.org ZFIN zebrafish database], with an initial emphasis on skeletal phenotypes. The evolutionary and mutant phenotypes are being described using common [[#The_Role_of_Ontologies|ontologies]]. The database with its web-interface, called EQSYTE (Entity-Quality System for Trait Evolution), together with the extended ontologies and data curation tools, will allow researchers to ask novel questions about the genetic and developmental regulation of evolutionary morphological transitions. Tool and database development are being guided by [http://en.wikipedia.org/wiki/Use_case use cases], or driving research questions, defined by the devo-evo community. These tools are being developed under an open-source, open-development model, and in such a way that they can be used for additional biological systems in the future.
| + | 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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| − | ===The Role of Ontologies===
| + | SCATE is 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. |
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| − | ====Background====
| + | 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''. |
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| − | Ontologies are constrained, structured vocabularies with well defined relationships among terms. Ontologies represent the knowledge-base of a particular discipline, and provide not only a mechanism for consistent annotation of data, but also greater interoperability among people and machines. The most widely used biological ontology is the [http://www.geneontology.org Gene Ontology], which is utilized to annotate molecular function, biological processes and subcellular localization to gene products from different organisms.
| + | See the [http://scate.phenoscape.org project website] for more information. For a little more background on the how and why of incorporating ontologies into comparative analysis, see [[ComparativeAnalysis]]. |
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| − | ====Phenotype ontologies==== | + | == Previous Phenoscape projects and Acknowledgements == |
| | + | * Phenoscape II ("[[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 [[:File:Phenoscape_Project_description_refs.pdf| here]]. |
| | + | * Phenoscape I ("[[Linking Evolution to Genomics Using Phenotype Ontologies]]") was funded by NSF grant BDI-0641025 from June 1, 2007, to Jun 30, 2011, and was supported by NESCent, NSF #EF-0423641. |
| | + | * The original ideas for Phenoscape arose from a NESCent <span class="plainlinks">[http://www.nescent.org/science/workinggroup.php Working Group]</span> led by Paula Mabee and Monte Westerfield, "[[Fish Evolution Working Group|Towards an Integrated Database for Fish Evolution]]." |
| | + | * These projects have bene made possible possible by the hard work of [[Acknowledgments#Contributors| numerous contributors]]. |
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| − | ; For model organisms : Approximately 500 mutant zebrafish lines (alleles) with over 660 annotated phenotypic characters from the jaw or gill arches (n=250), fins (n=210), axial skeleton (n=190) and other features (n=10) of the skeleton have been described. Researchers in the [http://www.zfin.org Zebrafish Information Network] (ZFIN) are annotating mutant phenotypes using the zebrafish anatomy ontology and the [http://www.bioontology.org/wiki/index.php/PATO:Main_Page Phenotype And Trait Ontology] (PATO). PATO is a “universal” ontology of terms describing qualities (e.g. shape, color, size) that may be applied to any organism.
| + | https://www.nescent.org/about/images/nsf_logo.jpg |
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| − | ; For multiple species (for evolutionary biology) : Representing anatomical character (and character state) data in an ontology-based framework is a new, forward-looking, and integrative move for phylogenetic systematic studies.
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| − | ====Anatomical ontologies====
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| − | A multi-species ontology for ostariophysan fishes, The Anatomy of Ostariophysi <!-- or: The Anatomical Ontology --> (TAO), will be developed by expanding on the terms in the zebrafish anatomical ontology. To begin with, development of the TAO will concentrate on the skeletal system because it varies significantly across the Ostariophysi, is well-preserved in fossil specimens, and it is often the focus of morphologically-based evolutionary studies in ichthyology. The [http://zfin.org/zf_info/anatomy/dict/sum.html zebrafish anatomical ontology] currently contains 236 skeletal system entities.
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| − | The multi-species anatomy ontology for ostariophysan fishes will be used in combination with the PATO ontology (see EQ format) to describe the naturally occurring phenotypes in non-model species (i.e. various ostariophysan fish species).
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| − | ====Taxonomic ontology====
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| − | We will develop a taxonomic ontology based on the Catalog of Fishes and taxonomic experts in order to relate species with particular characters and states. The taxonomic ontology will include nodes ancestral to the Ostariophysi as far back as the Vertebrata in order to associate certain anatomical terms with more inclusive clades than the Ostariophysi. The taxonomic ontology will be edited using OBO-Edit, similar to the taxonomic ontologies based on NCBI.
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| − | As part of this process, we will store statements of homology between entities, so that individual investigators may select particular relationships based on evidence. Thus, for the first time, research questions can be addressed (for example, using the web-interface and query tools that we will build) that require simultaneous data-mining of phylogenetic and genetic data. This approach will also promote integration across morphological systematic studies. Our study, which matches zebrafish model organism genetic data with phylogenetic data from the lineage to which zebrafish belongs (Cypriniformes and ostariophysan relatives), can be generalized to other model organisms and their respective clades. We bring to this study a unique collaboration between evolutionary and model organism biologists that builds upon the strengths of two national centers, a model organism database, a Tree of Life study, a Research Coordination Network, and several community image databases.
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| − | ====Fish Morphology====
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| − | Although the comparative anatomy of fishes has been documented in the literature for several hundred years, it is not available in a computable format. A Data Curator will input morphological character data that is gleaned from the literature, culled by experts (see table below) and the [http://www.deepfin.org/ ichthyological community]. The model of a “curated” database is one that has proven effective for model organism databases such as [http://zfin.org zebrafish], [http://www.FlyBase.org Drosophila], and [http://www.informatics.jax.org mouse]. EQSYTE (Entity-Quality System for Trait Evolution) will consist of a database and user interface in which the ontologies and data for evolutionary phenotypes are integrated with the zebrafish mutant phenotypes and associated genetic data from ZFIN.
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| − | Our goal is to input approximately 4,000 morphological features in an “EQ” format ([[Media:TREE Mabee.pdf|Mabee et al. 2007a]]<!--; Mabee et al. 2007 in process-->) using a combination of ontologies.
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| − | {| border="1" cellspacing="0" cellpadding="3"
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| − | ! Year !! Taxon !! PI !! # Papers !! # Characters !! # Taxa !! # Species, Genera, Families
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| − | |1 || Cypriniformes || Mayden || 72 || 1125* || 1000 || 3268, 321, 5
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| − | |1 || Siluriformes || Lundberg || 150 || 1200** || 1000 || 2867, 446, 35
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| − | |2 || Characiformes || Coburn || 81 || 800 || 550 || 1674, 270, 18
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| − | |2 || Gymnotiformes || Arratia || 20 || 200 || 50 || 134, 30, 5
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| − | |3 || Gonorhynchiformes || Arratia || 40 || 75 || 20 || 37, 7, 4
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| − | |3 || Clupeiformes || Hilton || 60 || 380 || 125 || 364, 84, 5
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| − | | || TOTAL || || 423 || 37802 || 2745 || 8344, 1158, 72
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| − | |}
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| − | <nowiki>*</nowiki> includes original characters from CToL<br/>
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| − | <nowiki>**</nowiki> All Catfish project (J. Lundberg)
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| − | <!-- LATER: “VIEW THE CHARACTERS IN THE DATABASE THUS FAR” -->
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| − | ===Help needed===
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| − | We are hiring two research programmers. See the [http://www.nescent.org/about/employment.php NESCent employment page] for more details.
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| − | ===Contact===
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| − | Paula Mabee (University of South Dakota) is the Principal Investigator. Co-principal investigators are Todd Vision (University of North Carolina, Chapel Hill), Monte Westerfield (University of Oregon, ZFIN), and Hilmar Lapp (NESCent) ([[Contact|see their contact addresses]]).
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| − | ==Pages of public interest==
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| − | * [[Ontology_Data_Service_API|Ontology Data Service API Description]]
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Enabling Machine-actionable Semantics for Comparative Analysis of Trait Evolution
The current project of the Phenoscape team is Enabling Machine-actionable Semantics for Comparative Analysis of Trait Evolution (SCATE).
The objective 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.
SCATE is 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.
See the project website for more information. For a little more background on the how and why of incorporating ontologies into comparative analysis, see ComparativeAnalysis.
Previous Phenoscape projects and Acknowledgements
- Phenoscape II ("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.
- Phenoscape I ("Linking Evolution to Genomics Using Phenotype Ontologies") was funded by NSF grant BDI-0641025 from June 1, 2007, to Jun 30, 2011, and was supported by NESCent, NSF #EF-0423641.
- The original ideas for Phenoscape arose from a NESCent Working Group led by Paula Mabee and Monte Westerfield, "Towards an Integrated Database for Fish Evolution."
- These projects have bene made possible possible by the hard work of numerous contributors.
