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SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery

Synthetic lethal interactions (SLIs), genetic interactions in which the simultaneous inactivation of two genes leads to a lethal phenotype, are promising targets for therapeutic intervention in cancer, as exemplified by the recent success of PARP inhibitors in treating BRCA1/2-deficient tumors. We p...

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Autores principales: Tercan, Bahar, Qin, Guangrong, Kim, Taek-Kyun, Aguilar, Boris, Phan, John, Longabaugh, William, Pot, David, Kemp, Christopher J., Chambwe, Nyasha, Shmulevich, Ilya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9880341/
https://www.ncbi.nlm.nih.gov/pubmed/36761837
http://dx.doi.org/10.12688/f1000research.110903.2
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author Tercan, Bahar
Qin, Guangrong
Kim, Taek-Kyun
Aguilar, Boris
Phan, John
Longabaugh, William
Pot, David
Kemp, Christopher J.
Chambwe, Nyasha
Shmulevich, Ilya
author_facet Tercan, Bahar
Qin, Guangrong
Kim, Taek-Kyun
Aguilar, Boris
Phan, John
Longabaugh, William
Pot, David
Kemp, Christopher J.
Chambwe, Nyasha
Shmulevich, Ilya
author_sort Tercan, Bahar
collection PubMed
description Synthetic lethal interactions (SLIs), genetic interactions in which the simultaneous inactivation of two genes leads to a lethal phenotype, are promising targets for therapeutic intervention in cancer, as exemplified by the recent success of PARP inhibitors in treating BRCA1/2-deficient tumors. We present SL-Cloud, a new component of the Institute for Systems Biology Cancer Gateway in the Cloud (ISB-CGC), that provides an integrated framework of cloud-hosted data resources and curated workflows to enable facile prediction of SLIs. This resource addresses two main challenges related to SLI inference: the need to wrangle and preprocess large multi-omic datasets and the availability of multiple comparable prediction approaches. SL-Cloud enables customizable computational inference of SLIs and testing of prediction approaches across multiple datasets. We anticipate that cancer researchers will find utility in this tool for discovery of SLIs to support further investigation into potential drug targets for anticancer therapies.
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spelling pubmed-98803412023-02-08 SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery Tercan, Bahar Qin, Guangrong Kim, Taek-Kyun Aguilar, Boris Phan, John Longabaugh, William Pot, David Kemp, Christopher J. Chambwe, Nyasha Shmulevich, Ilya F1000Res Software Tool Article Synthetic lethal interactions (SLIs), genetic interactions in which the simultaneous inactivation of two genes leads to a lethal phenotype, are promising targets for therapeutic intervention in cancer, as exemplified by the recent success of PARP inhibitors in treating BRCA1/2-deficient tumors. We present SL-Cloud, a new component of the Institute for Systems Biology Cancer Gateway in the Cloud (ISB-CGC), that provides an integrated framework of cloud-hosted data resources and curated workflows to enable facile prediction of SLIs. This resource addresses two main challenges related to SLI inference: the need to wrangle and preprocess large multi-omic datasets and the availability of multiple comparable prediction approaches. SL-Cloud enables customizable computational inference of SLIs and testing of prediction approaches across multiple datasets. We anticipate that cancer researchers will find utility in this tool for discovery of SLIs to support further investigation into potential drug targets for anticancer therapies. F1000 Research Limited 2022-12-22 /pmc/articles/PMC9880341/ /pubmed/36761837 http://dx.doi.org/10.12688/f1000research.110903.2 Text en Copyright: © 2022 Tercan B et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Tercan, Bahar
Qin, Guangrong
Kim, Taek-Kyun
Aguilar, Boris
Phan, John
Longabaugh, William
Pot, David
Kemp, Christopher J.
Chambwe, Nyasha
Shmulevich, Ilya
SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery
title SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery
title_full SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery
title_fullStr SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery
title_full_unstemmed SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery
title_short SL-Cloud: A Cloud-based resource to support synthetic lethal interaction discovery
title_sort sl-cloud: a cloud-based resource to support synthetic lethal interaction discovery
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9880341/
https://www.ncbi.nlm.nih.gov/pubmed/36761837
http://dx.doi.org/10.12688/f1000research.110903.2
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