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StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit
Target prioritization is essential for drug discovery and repositioning. Applying computational methods to analyze and process multi-omics data to find new drug targets is a practical approach for achieving this. Despite an increasing number of methods for generating datasets such as genomics, pheno...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197487/ https://www.ncbi.nlm.nih.gov/pubmed/35711912 http://dx.doi.org/10.3389/fgene.2022.868015 |
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author | Lee, Chiyun Lin, Junxia Prokop, Andrzej Gopalakrishnan, Vancheswaran Hanna, Richard N. Papa, Eliseo Freeman, Adrian Patel, Saleha Yu, Wen Huhn, Monika Sheikh, Abdul-Saboor Tan, Keith Sellman, Bret R. Cohen, Taylor Mangion, Jonathan Khan, Faisal M. Gusev, Yuriy Shameer, Khader |
author_facet | Lee, Chiyun Lin, Junxia Prokop, Andrzej Gopalakrishnan, Vancheswaran Hanna, Richard N. Papa, Eliseo Freeman, Adrian Patel, Saleha Yu, Wen Huhn, Monika Sheikh, Abdul-Saboor Tan, Keith Sellman, Bret R. Cohen, Taylor Mangion, Jonathan Khan, Faisal M. Gusev, Yuriy Shameer, Khader |
author_sort | Lee, Chiyun |
collection | PubMed |
description | Target prioritization is essential for drug discovery and repositioning. Applying computational methods to analyze and process multi-omics data to find new drug targets is a practical approach for achieving this. Despite an increasing number of methods for generating datasets such as genomics, phenomics, and proteomics, attempts to integrate and mine such datasets remain limited in scope. Developing hybrid intelligence solutions that combine human intelligence in the scientific domain and disease biology with the ability to mine multiple databases simultaneously may help augment drug target discovery and identify novel drug-indication associations. We believe that integrating different data sources using a singular numerical scoring system in a hybrid intelligent framework could help to bridge these different omics layers and facilitate rapid drug target prioritization for studies in drug discovery, development or repositioning. Herein, we describe our prototype of the StarGazer pipeline which combines multi-source, multi-omics data with a novel target prioritization scoring system in an interactive Python-based Streamlit dashboard. StarGazer displays target prioritization scores for genes associated with 1844 phenotypic traits, and is available via https://github.com/AstraZeneca/StarGazer. |
format | Online Article Text |
id | pubmed-9197487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91974872022-06-15 StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit Lee, Chiyun Lin, Junxia Prokop, Andrzej Gopalakrishnan, Vancheswaran Hanna, Richard N. Papa, Eliseo Freeman, Adrian Patel, Saleha Yu, Wen Huhn, Monika Sheikh, Abdul-Saboor Tan, Keith Sellman, Bret R. Cohen, Taylor Mangion, Jonathan Khan, Faisal M. Gusev, Yuriy Shameer, Khader Front Genet Genetics Target prioritization is essential for drug discovery and repositioning. Applying computational methods to analyze and process multi-omics data to find new drug targets is a practical approach for achieving this. Despite an increasing number of methods for generating datasets such as genomics, phenomics, and proteomics, attempts to integrate and mine such datasets remain limited in scope. Developing hybrid intelligence solutions that combine human intelligence in the scientific domain and disease biology with the ability to mine multiple databases simultaneously may help augment drug target discovery and identify novel drug-indication associations. We believe that integrating different data sources using a singular numerical scoring system in a hybrid intelligent framework could help to bridge these different omics layers and facilitate rapid drug target prioritization for studies in drug discovery, development or repositioning. Herein, we describe our prototype of the StarGazer pipeline which combines multi-source, multi-omics data with a novel target prioritization scoring system in an interactive Python-based Streamlit dashboard. StarGazer displays target prioritization scores for genes associated with 1844 phenotypic traits, and is available via https://github.com/AstraZeneca/StarGazer. Frontiers Media S.A. 2022-05-31 /pmc/articles/PMC9197487/ /pubmed/35711912 http://dx.doi.org/10.3389/fgene.2022.868015 Text en Copyright © 2022 Lee, Lin, Prokop, Gopalakrishnan, Hanna, Papa, Freeman, Patel, Yu, Huhn, Sheikh, Tan, Sellman, Cohen, Mangion, Khan, Gusev and Shameer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Lee, Chiyun Lin, Junxia Prokop, Andrzej Gopalakrishnan, Vancheswaran Hanna, Richard N. Papa, Eliseo Freeman, Adrian Patel, Saleha Yu, Wen Huhn, Monika Sheikh, Abdul-Saboor Tan, Keith Sellman, Bret R. Cohen, Taylor Mangion, Jonathan Khan, Faisal M. Gusev, Yuriy Shameer, Khader StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit |
title | StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit |
title_full | StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit |
title_fullStr | StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit |
title_full_unstemmed | StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit |
title_short | StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit |
title_sort | stargazer: a hybrid intelligence platform for drug target prioritization and digital drug repositioning using streamlit |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197487/ https://www.ncbi.nlm.nih.gov/pubmed/35711912 http://dx.doi.org/10.3389/fgene.2022.868015 |
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