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ScreenTroll: a searchable database to compare genome-wide yeast screens

Systematic biological screens typically identify many genes or proteins that are implicated in a specific phenotype. However, deriving mechanistic insight from these screens typically involves focusing upon one or a few genes within the set in order to elucidate their precise role in producing the p...

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Detalles Bibliográficos
Autores principales: Thorpe, Peter H., Dittmar, John C., Rothstein, Rodney
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3330810/
https://www.ncbi.nlm.nih.gov/pubmed/22522342
http://dx.doi.org/10.1093/database/bas022
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author Thorpe, Peter H.
Dittmar, John C.
Rothstein, Rodney
author_facet Thorpe, Peter H.
Dittmar, John C.
Rothstein, Rodney
author_sort Thorpe, Peter H.
collection PubMed
description Systematic biological screens typically identify many genes or proteins that are implicated in a specific phenotype. However, deriving mechanistic insight from these screens typically involves focusing upon one or a few genes within the set in order to elucidate their precise role in producing the phenotype. To find these critical genes, researchers use a variety of tools to query the set of genes to uncover underlying common genetic or physical interactions or common functional annotations (e.g. gene ontology terms). Not only it is necessary to find previous screens containing genes in common with the new set, but also useful to easily access the individual manuscript or study that classified those genes. Unfortunately, no tool currently exists to facilitate this task. We have developed a web-based tool (ScreenTroll) that queries one or more genes against a database of systematic yeast screens. The software determines which genome-wide yeast screens also identified the queried gene(s) and the resulting screens are listed in an order based on the extent of the overlap between the queried gene(s) and the open reading frames (ORFs) characterized in each individual yeast screen. In a separate list, the corresponding ORFs that are found in both the queried set of genes and each individual genome-wide screen are displayed along with links to the relevant manuscript via NIH’s PubMed database. ScreenTroll is useful for comparing a list of ORFs with genes identified in a wide array of published genome-wide screens. This comparison informs users whether any of their queried ORFs overlaps a previous study in the ScreenTroll database. By listing the manuscript of the published screen, users can read more about the phenotype associated with that study. Together, this information provides insight into the function of the queried genes and helps the user focus on a subset of them.
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spelling pubmed-33308102012-04-20 ScreenTroll: a searchable database to compare genome-wide yeast screens Thorpe, Peter H. Dittmar, John C. Rothstein, Rodney Database (Oxford) Database Tool Systematic biological screens typically identify many genes or proteins that are implicated in a specific phenotype. However, deriving mechanistic insight from these screens typically involves focusing upon one or a few genes within the set in order to elucidate their precise role in producing the phenotype. To find these critical genes, researchers use a variety of tools to query the set of genes to uncover underlying common genetic or physical interactions or common functional annotations (e.g. gene ontology terms). Not only it is necessary to find previous screens containing genes in common with the new set, but also useful to easily access the individual manuscript or study that classified those genes. Unfortunately, no tool currently exists to facilitate this task. We have developed a web-based tool (ScreenTroll) that queries one or more genes against a database of systematic yeast screens. The software determines which genome-wide yeast screens also identified the queried gene(s) and the resulting screens are listed in an order based on the extent of the overlap between the queried gene(s) and the open reading frames (ORFs) characterized in each individual yeast screen. In a separate list, the corresponding ORFs that are found in both the queried set of genes and each individual genome-wide screen are displayed along with links to the relevant manuscript via NIH’s PubMed database. ScreenTroll is useful for comparing a list of ORFs with genes identified in a wide array of published genome-wide screens. This comparison informs users whether any of their queried ORFs overlaps a previous study in the ScreenTroll database. By listing the manuscript of the published screen, users can read more about the phenotype associated with that study. Together, this information provides insight into the function of the queried genes and helps the user focus on a subset of them. Oxford University Press 2012-04-20 /pmc/articles/PMC3330810/ /pubmed/22522342 http://dx.doi.org/10.1093/database/bas022 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Tool
Thorpe, Peter H.
Dittmar, John C.
Rothstein, Rodney
ScreenTroll: a searchable database to compare genome-wide yeast screens
title ScreenTroll: a searchable database to compare genome-wide yeast screens
title_full ScreenTroll: a searchable database to compare genome-wide yeast screens
title_fullStr ScreenTroll: a searchable database to compare genome-wide yeast screens
title_full_unstemmed ScreenTroll: a searchable database to compare genome-wide yeast screens
title_short ScreenTroll: a searchable database to compare genome-wide yeast screens
title_sort screentroll: a searchable database to compare genome-wide yeast screens
topic Database Tool
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3330810/
https://www.ncbi.nlm.nih.gov/pubmed/22522342
http://dx.doi.org/10.1093/database/bas022
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