TIPS Proposal Draft - Revision history

Rwalls: Replaced content with 'This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010) Back to TIPS_Fall_2010 The co…'

2010-11-18T19:28:55Z

Replaced content with 'This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010) Back to TIPS_Fall_2010 The co…'

Rwalls at 18:56, 18 November 2010

2010-11-18T18:56:59Z

Rwalls at 20:13, 17 November 2010

2010-11-17T20:13:44Z

Rwalls at 20:12, 17 November 2010

2010-11-17T20:12:58Z

Rwalls: Created page with 'This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010)'

2010-11-17T20:02:14Z

Created page with 'This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010)'

New page

This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010)

← Older revision		Revision as of 19:28, 18 November 2010
Line 3:		Line 3:
	Back to [[TIPS_Fall_2010]]		Back to [[TIPS_Fall_2010]]

−	~~'''Review/Opinion article pre-submission enquiries:'''~~	+	The content of this page was moved to a file on google docs
−
−	~~-Provide a 500-600 word summary outlining:~~
−	* what will be discussed in the article,
−	* why the suggested topic would be timely,
−	* co-author information
−	* up to 20 key references that indicate the intended breadth of the proposed article (most references should be to work published in the past 2-3 years).
−
−	~~'''Focus will be on the benefits and usefulness of the PO and GO, global perspective, links between PO and GO '''~~
−
−
−	In the age of OMICs, onotolgies are quickly becoming an indespensible tool for data curation, access and analysis. Over the past ten years, the Gene Ontology (GO) has developed the ontologies (structured, controlled vocabularies) to describe molecular functions, biological processes and cellular localizations associated with specific genes and gene products, developed a standard protocol for annotating genes with GO terms, and amassed over xxx association between GO terms and genes, laying the foundation for computationally driven functional annotation and comparative analysis. The plant community adopted the GO approach for annotation of the Arabidopsis thaliana and Oryza sativa genomes, but soon realized that in order to utilize the full potential of the large-scale analysis of OMICs datasets, it would be necessary to annotate gene expression and phenotypic datasets using ontologies for plant anatomy and growth and developmental stages. Early efforts by separate research groups were merged to create the Plant Ontology (PO) in 200x. The PO, like other taxon-specific ontologies, allows functional annotation data to be associated with the spatial and temporal expression of genes and with observed phenotypes, something that is not possible with GO.
−
−	~~Examples~~ of ~~analysis that you can do with PO or similar, but can’t do with GO.~~
−
−	~~Changes in PO and how it is now more applicable~~ to ~~cross-species comparisons:~~
−	~~-Incorporation of non-angiosperm models and angiosperm non-models~~
−	~~-flower development. Analysis example (maybe for box): Compare gene expression data sets from Arabidopsis and rice: find common datasets- one each for~~ a ~~tissue and and growth stage. Sources: from Genevestigator~~
−	~~-Researchers in model organism have benefited from structured vocabularies and other bioniformatics tools. Time for non-model organism researchers to take advantage of the same tools~~
−	~~-leaf development across taxa,~~
−
−	~~Other uses of biological ontologies:~~
−	~~Hot topics in plant genomics and how the PO can help research in those areas~~
−	~~rice data sets described above, new genomes being sequenced~~
−	~~others~~
−	~~Use of ontologies in systematics (character descriptions) and biodiversity exploration, see Teleost Anatomy Ontology paper.~~
−	~~Crop improvement for non-model species~~
−	~~(trait descriptions and gene expression as in SGN or Generation Challenge Program, gene exploration for non-model species based~~ on ~~model organism database in PO)~~
−	~~PO as teaching tool~~
−	~~Conclusion~~
−	~~Engage community, encourage folks to provide more annotations~~
−	~~Future directions~~

← Older revision		Revision as of 18:56, 18 November 2010
Line 2:		Line 2:

	Back to [[TIPS_Fall_2010]]		Back to [[TIPS_Fall_2010]]
		+
		+	'''Review/Opinion article pre-submission enquiries:'''
		+
		+	-Provide a 500-600 word summary outlining:
		+	* what will be discussed in the article,
		+	* why the suggested topic would be timely,
		+	* co-author information
		+	* up to 20 key references that indicate the intended breadth of the proposed article (most references should be to work published in the past 2-3 years).
		+
		+	'''Focus will be on the benefits and usefulness of the PO and GO, global perspective, links between PO and GO '''
		+

	In the age of OMICs, onotolgies are quickly becoming an indespensible tool for data curation, access and analysis. Over the past ten years, the Gene Ontology (GO) has developed the ontologies (structured, controlled vocabularies) to describe molecular functions, biological processes and cellular localizations associated with specific genes and gene products, developed a standard protocol for annotating genes with GO terms, and amassed over xxx association between GO terms and genes, laying the foundation for computationally driven functional annotation and comparative analysis. The plant community adopted the GO approach for annotation of the Arabidopsis thaliana and Oryza sativa genomes, but soon realized that in order to utilize the full potential of the large-scale analysis of OMICs datasets, it would be necessary to annotate gene expression and phenotypic datasets using ontologies for plant anatomy and growth and developmental stages. Early efforts by separate research groups were merged to create the Plant Ontology (PO) in 200x. The PO, like other taxon-specific ontologies, allows functional annotation data to be associated with the spatial and temporal expression of genes and with observed phenotypes, something that is not possible with GO.		In the age of OMICs, onotolgies are quickly becoming an indespensible tool for data curation, access and analysis. Over the past ten years, the Gene Ontology (GO) has developed the ontologies (structured, controlled vocabularies) to describe molecular functions, biological processes and cellular localizations associated with specific genes and gene products, developed a standard protocol for annotating genes with GO terms, and amassed over xxx association between GO terms and genes, laying the foundation for computationally driven functional annotation and comparative analysis. The plant community adopted the GO approach for annotation of the Arabidopsis thaliana and Oryza sativa genomes, but soon realized that in order to utilize the full potential of the large-scale analysis of OMICs datasets, it would be necessary to annotate gene expression and phenotypic datasets using ontologies for plant anatomy and growth and developmental stages. Early efforts by separate research groups were merged to create the Plant Ontology (PO) in 200x. The PO, like other taxon-specific ontologies, allows functional annotation data to be associated with the spatial and temporal expression of genes and with observed phenotypes, something that is not possible with GO.

← Older revision		Revision as of 20:13, 17 November 2010
Line 1:		Line 1:
	This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010)		This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010)
		+
		+	Back to [[TIPS_Fall_2010]]

	In the age of OMICs, onotolgies are quickly becoming an indespensible tool for data curation, access and analysis. Over the past ten years, the Gene Ontology (GO) has developed the ontologies (structured, controlled vocabularies) to describe molecular functions, biological processes and cellular localizations associated with specific genes and gene products, developed a standard protocol for annotating genes with GO terms, and amassed over xxx association between GO terms and genes, laying the foundation for computationally driven functional annotation and comparative analysis. The plant community adopted the GO approach for annotation of the Arabidopsis thaliana and Oryza sativa genomes, but soon realized that in order to utilize the full potential of the large-scale analysis of OMICs datasets, it would be necessary to annotate gene expression and phenotypic datasets using ontologies for plant anatomy and growth and developmental stages. Early efforts by separate research groups were merged to create the Plant Ontology (PO) in 200x. The PO, like other taxon-specific ontologies, allows functional annotation data to be associated with the spatial and temporal expression of genes and with observed phenotypes, something that is not possible with GO.		In the age of OMICs, onotolgies are quickly becoming an indespensible tool for data curation, access and analysis. Over the past ten years, the Gene Ontology (GO) has developed the ontologies (structured, controlled vocabularies) to describe molecular functions, biological processes and cellular localizations associated with specific genes and gene products, developed a standard protocol for annotating genes with GO terms, and amassed over xxx association between GO terms and genes, laying the foundation for computationally driven functional annotation and comparative analysis. The plant community adopted the GO approach for annotation of the Arabidopsis thaliana and Oryza sativa genomes, but soon realized that in order to utilize the full potential of the large-scale analysis of OMICs datasets, it would be necessary to annotate gene expression and phenotypic datasets using ontologies for plant anatomy and growth and developmental stages. Early efforts by separate research groups were merged to create the Plant Ontology (PO) in 200x. The PO, like other taxon-specific ontologies, allows functional annotation data to be associated with the spatial and temporal expression of genes and with observed phenotypes, something that is not possible with GO.

← Older revision		Revision as of 20:12, 17 November 2010
Line 1:		Line 1:
	This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010)		This page was created so multiple authors can work on this draft without using email, and older versions will be archived. (RW 11-17-2010)
		+
		+	In the age of OMICs, onotolgies are quickly becoming an indespensible tool for data curation, access and analysis. Over the past ten years, the Gene Ontology (GO) has developed the ontologies (structured, controlled vocabularies) to describe molecular functions, biological processes and cellular localizations associated with specific genes and gene products, developed a standard protocol for annotating genes with GO terms, and amassed over xxx association between GO terms and genes, laying the foundation for computationally driven functional annotation and comparative analysis. The plant community adopted the GO approach for annotation of the Arabidopsis thaliana and Oryza sativa genomes, but soon realized that in order to utilize the full potential of the large-scale analysis of OMICs datasets, it would be necessary to annotate gene expression and phenotypic datasets using ontologies for plant anatomy and growth and developmental stages. Early efforts by separate research groups were merged to create the Plant Ontology (PO) in 200x. The PO, like other taxon-specific ontologies, allows functional annotation data to be associated with the spatial and temporal expression of genes and with observed phenotypes, something that is not possible with GO.
		+
		+	Examples of analysis that you can do with PO or similar, but can’t do with GO.
		+
		+	Changes in PO and how it is now more applicable to cross-species comparisons:
		+	-Incorporation of non-angiosperm models and angiosperm non-models
		+	-flower development. Analysis example (maybe for box): Compare gene expression data sets from Arabidopsis and rice: find common datasets- one each for a tissue and and growth stage. Sources: from Genevestigator
		+	-Researchers in model organism have benefited from structured vocabularies and other bioniformatics tools. Time for non-model organism researchers to take advantage of the same tools
		+	-leaf development across taxa,
		+
		+	Other uses of biological ontologies:
		+	Hot topics in plant genomics and how the PO can help research in those areas
		+	rice data sets described above, new genomes being sequenced
		+	others
		+	Use of ontologies in systematics (character descriptions) and biodiversity exploration, see Teleost Anatomy Ontology paper.
		+	Crop improvement for non-model species
		+	(trait descriptions and gene expression as in SGN or Generation Challenge Program, gene exploration for non-model species based on model organism database in PO)
		+	PO as teaching tool
		+	Conclusion
		+	Engage community, encourage folks to provide more annotations
		+	Future directions