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Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex
BACKGROUND: Yeast one-hybrid (Y1H) is a common technique for identifying DNA-protein interactions, and robotic platforms have been developed for high-throughput analyses to unravel the gene regulatory networks in many organisms. Use of these high-throughput techniques has led to the generation of in...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461970/ https://www.ncbi.nlm.nih.gov/pubmed/34560855 http://dx.doi.org/10.1186/s12915-021-01140-y |
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author | Tsai, Ni-Chiao Hsu, Tzu-Shu Kuo, Shang-Che Kao, Chung-Ting Hung, Tzu-Huan Lin, Da-Gin Yeh, Chung-Shu Chu, Chia-Chen Lin, Jeng-Shane Lin, Hsin-Hung Ko, Chia-Ying Chang, Tien-Hsien Su, Jung-Chen Lin, Ying-Chung Jimmy |
author_facet | Tsai, Ni-Chiao Hsu, Tzu-Shu Kuo, Shang-Che Kao, Chung-Ting Hung, Tzu-Huan Lin, Da-Gin Yeh, Chung-Shu Chu, Chia-Chen Lin, Jeng-Shane Lin, Hsin-Hung Ko, Chia-Ying Chang, Tien-Hsien Su, Jung-Chen Lin, Ying-Chung Jimmy |
author_sort | Tsai, Ni-Chiao |
collection | PubMed |
description | BACKGROUND: Yeast one-hybrid (Y1H) is a common technique for identifying DNA-protein interactions, and robotic platforms have been developed for high-throughput analyses to unravel the gene regulatory networks in many organisms. Use of these high-throughput techniques has led to the generation of increasingly large datasets, and several software packages have been developed to analyze such data. We previously established the currently most efficient Y1H system, meiosis-directed Y1H; however, the available software tools were not designed for processing the additional parameters suggested by meiosis-directed Y1H to avoid false positives and required programming skills for operation. RESULTS: We developed a new tool named GateMultiplex with high computing performance using C++. GateMultiplex incorporated a graphical user interface (GUI), which allows the operation without any programming skills. Flexible parameter options were designed for multiple experimental purposes to enable the application of GateMultiplex even beyond Y1H platforms. We further demonstrated the data analysis from other three fields using GateMultiplex, the identification of lead compounds in preclinical cancer drug discovery, the crop line selection in precision agriculture, and the ocean pollution detection from deep-sea fishery. CONCLUSIONS: The user-friendly GUI, fast C++ computing speed, flexible parameter setting, and applicability of GateMultiplex facilitate the feasibility of large-scale data analysis in life science fields. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01140-y. |
format | Online Article Text |
id | pubmed-8461970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84619702021-09-24 Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex Tsai, Ni-Chiao Hsu, Tzu-Shu Kuo, Shang-Che Kao, Chung-Ting Hung, Tzu-Huan Lin, Da-Gin Yeh, Chung-Shu Chu, Chia-Chen Lin, Jeng-Shane Lin, Hsin-Hung Ko, Chia-Ying Chang, Tien-Hsien Su, Jung-Chen Lin, Ying-Chung Jimmy BMC Biol Software BACKGROUND: Yeast one-hybrid (Y1H) is a common technique for identifying DNA-protein interactions, and robotic platforms have been developed for high-throughput analyses to unravel the gene regulatory networks in many organisms. Use of these high-throughput techniques has led to the generation of increasingly large datasets, and several software packages have been developed to analyze such data. We previously established the currently most efficient Y1H system, meiosis-directed Y1H; however, the available software tools were not designed for processing the additional parameters suggested by meiosis-directed Y1H to avoid false positives and required programming skills for operation. RESULTS: We developed a new tool named GateMultiplex with high computing performance using C++. GateMultiplex incorporated a graphical user interface (GUI), which allows the operation without any programming skills. Flexible parameter options were designed for multiple experimental purposes to enable the application of GateMultiplex even beyond Y1H platforms. We further demonstrated the data analysis from other three fields using GateMultiplex, the identification of lead compounds in preclinical cancer drug discovery, the crop line selection in precision agriculture, and the ocean pollution detection from deep-sea fishery. CONCLUSIONS: The user-friendly GUI, fast C++ computing speed, flexible parameter setting, and applicability of GateMultiplex facilitate the feasibility of large-scale data analysis in life science fields. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01140-y. BioMed Central 2021-09-24 /pmc/articles/PMC8461970/ /pubmed/34560855 http://dx.doi.org/10.1186/s12915-021-01140-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Tsai, Ni-Chiao Hsu, Tzu-Shu Kuo, Shang-Che Kao, Chung-Ting Hung, Tzu-Huan Lin, Da-Gin Yeh, Chung-Shu Chu, Chia-Chen Lin, Jeng-Shane Lin, Hsin-Hung Ko, Chia-Ying Chang, Tien-Hsien Su, Jung-Chen Lin, Ying-Chung Jimmy Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex |
title | Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex |
title_full | Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex |
title_fullStr | Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex |
title_full_unstemmed | Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex |
title_short | Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex |
title_sort | large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using gatemultiplex |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461970/ https://www.ncbi.nlm.nih.gov/pubmed/34560855 http://dx.doi.org/10.1186/s12915-021-01140-y |
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