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LINPS: a database for cancer-cell-specific perturbations of biological networks
Screening for potential cancer therapies using existing large datasets of drug perturbations requires expertise and resources not available to all. This is often a barrier for lab scientists to tap into these valuable resources. To address these issues, one can take advantage of prior knowledge espe...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378515/ https://www.ncbi.nlm.nih.gov/pubmed/34415996 http://dx.doi.org/10.1093/database/baab048 |
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author | Ahmed, Mahmoud Kim, Deok Ryong |
author_facet | Ahmed, Mahmoud Kim, Deok Ryong |
author_sort | Ahmed, Mahmoud |
collection | PubMed |
description | Screening for potential cancer therapies using existing large datasets of drug perturbations requires expertise and resources not available to all. This is often a barrier for lab scientists to tap into these valuable resources. To address these issues, one can take advantage of prior knowledge especially those coded in standard formats such as causal biological networks (CBN). Large datasets can be converted into appropriate structures, analyzed once and the results made freely available in easy-to-use formats. We used the Library of Integrated Cellular Signatures to model the cell-specific effect of hundreds of drug treatments on gene expression. These signatures were then used to predict the effect of the treatments on several CBN using the network perturbation amplitudes analysis. We packaged the pre-computed scores in a database with an interactive web interface. The intuitive user-friendly interface can be used to query the database for drug perturbations and quantify their effect on multiple key biological functions in cancer cell lines. In addition to describing the process of building the database and the interface, we provide a realistic use case to explain how to use and interpret the results. To sum, we pre-computed cancer-cell-specific perturbation amplitudes of several biological networks and made the output available in a database with an interactive web interface. Database URL https://mahshaaban.shinyapps.io/LINPSAPP/ |
format | Online Article Text |
id | pubmed-8378515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-83785152021-08-23 LINPS: a database for cancer-cell-specific perturbations of biological networks Ahmed, Mahmoud Kim, Deok Ryong Database (Oxford) Database Tool Screening for potential cancer therapies using existing large datasets of drug perturbations requires expertise and resources not available to all. This is often a barrier for lab scientists to tap into these valuable resources. To address these issues, one can take advantage of prior knowledge especially those coded in standard formats such as causal biological networks (CBN). Large datasets can be converted into appropriate structures, analyzed once and the results made freely available in easy-to-use formats. We used the Library of Integrated Cellular Signatures to model the cell-specific effect of hundreds of drug treatments on gene expression. These signatures were then used to predict the effect of the treatments on several CBN using the network perturbation amplitudes analysis. We packaged the pre-computed scores in a database with an interactive web interface. The intuitive user-friendly interface can be used to query the database for drug perturbations and quantify their effect on multiple key biological functions in cancer cell lines. In addition to describing the process of building the database and the interface, we provide a realistic use case to explain how to use and interpret the results. To sum, we pre-computed cancer-cell-specific perturbation amplitudes of several biological networks and made the output available in a database with an interactive web interface. Database URL https://mahshaaban.shinyapps.io/LINPSAPP/ Oxford University Press 2021-08-20 /pmc/articles/PMC8378515/ /pubmed/34415996 http://dx.doi.org/10.1093/database/baab048 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Tool Ahmed, Mahmoud Kim, Deok Ryong LINPS: a database for cancer-cell-specific perturbations of biological networks |
title | LINPS: a database for cancer-cell-specific perturbations of biological networks |
title_full | LINPS: a database for cancer-cell-specific perturbations of biological networks |
title_fullStr | LINPS: a database for cancer-cell-specific perturbations of biological networks |
title_full_unstemmed | LINPS: a database for cancer-cell-specific perturbations of biological networks |
title_short | LINPS: a database for cancer-cell-specific perturbations of biological networks |
title_sort | linps: a database for cancer-cell-specific perturbations of biological networks |
topic | Database Tool |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378515/ https://www.ncbi.nlm.nih.gov/pubmed/34415996 http://dx.doi.org/10.1093/database/baab048 |
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