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Computational curation and analysis of publicly available protein sequence data from a single protein family
The wealth of sequence data available on public databases is increasing at an exponential rate, and while tremendous efforts are being made to make access to these resources easier, these data can be challenging for researchers to reuse because submissions are made from numerous laboratories with di...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508561/ https://www.ncbi.nlm.nih.gov/pubmed/36164433 http://dx.doi.org/10.1016/j.mex.2022.101846 |
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author | Dougherty, Kyra Hudak, Katalin A. |
author_facet | Dougherty, Kyra Hudak, Katalin A. |
author_sort | Dougherty, Kyra |
collection | PubMed |
description | The wealth of sequence data available on public databases is increasing at an exponential rate, and while tremendous efforts are being made to make access to these resources easier, these data can be challenging for researchers to reuse because submissions are made from numerous laboratories with different biological objectives, resulting in inconsistent naming conventions and sequence content. Researchers can manually inspect each sequence and curate a dataset by hand but automating some of these steps will reduce this burden. This paper is a step-by-step guide describing how to identify all proteins containing a specific domain with the Conserved Protein Domain Architecture Retrieval Tool, download all associated amino acid sequences from NCBI Entrez, tabulate, and clean the data. I will also describe how to extract the full taxonomic information and computationally predict some physicochemical properties of the proteins based on amino acid sequence. The resulting data are applicable to a wide range of bioinformatic analyses where publicly available data are utilized. • Step-by-step guide to gathering, cleaning, and parsing data from publicly available databases for computational analysis, plus supplementation of taxonomic data and physicochemical characteristics from sequence data. • This strategy allows for reuse of existing large-scale publicly available data for different downstream applications to answer novel biological questions. |
format | Online Article Text |
id | pubmed-9508561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-95085612022-09-25 Computational curation and analysis of publicly available protein sequence data from a single protein family Dougherty, Kyra Hudak, Katalin A. MethodsX Method Article The wealth of sequence data available on public databases is increasing at an exponential rate, and while tremendous efforts are being made to make access to these resources easier, these data can be challenging for researchers to reuse because submissions are made from numerous laboratories with different biological objectives, resulting in inconsistent naming conventions and sequence content. Researchers can manually inspect each sequence and curate a dataset by hand but automating some of these steps will reduce this burden. This paper is a step-by-step guide describing how to identify all proteins containing a specific domain with the Conserved Protein Domain Architecture Retrieval Tool, download all associated amino acid sequences from NCBI Entrez, tabulate, and clean the data. I will also describe how to extract the full taxonomic information and computationally predict some physicochemical properties of the proteins based on amino acid sequence. The resulting data are applicable to a wide range of bioinformatic analyses where publicly available data are utilized. • Step-by-step guide to gathering, cleaning, and parsing data from publicly available databases for computational analysis, plus supplementation of taxonomic data and physicochemical characteristics from sequence data. • This strategy allows for reuse of existing large-scale publicly available data for different downstream applications to answer novel biological questions. Elsevier 2022-09-10 /pmc/articles/PMC9508561/ /pubmed/36164433 http://dx.doi.org/10.1016/j.mex.2022.101846 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Method Article Dougherty, Kyra Hudak, Katalin A. Computational curation and analysis of publicly available protein sequence data from a single protein family |
title | Computational curation and analysis of publicly available protein sequence data from a single protein family |
title_full | Computational curation and analysis of publicly available protein sequence data from a single protein family |
title_fullStr | Computational curation and analysis of publicly available protein sequence data from a single protein family |
title_full_unstemmed | Computational curation and analysis of publicly available protein sequence data from a single protein family |
title_short | Computational curation and analysis of publicly available protein sequence data from a single protein family |
title_sort | computational curation and analysis of publicly available protein sequence data from a single protein family |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508561/ https://www.ncbi.nlm.nih.gov/pubmed/36164433 http://dx.doi.org/10.1016/j.mex.2022.101846 |
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