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Integrated visual analysis of protein structures, sequences, and feature data
BACKGROUND: To understand the molecular mechanisms that give rise to a protein's function, biologists often need to (i) find and access all related atomic-resolution 3D structures, and (ii) map sequence-based features (e.g., domains, single-nucleotide polymorphisms, post-translational modificat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547178/ https://www.ncbi.nlm.nih.gov/pubmed/26329268 http://dx.doi.org/10.1186/1471-2105-16-S11-S7 |
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author | Stolte, Christian Sabir, Kenneth S Heinrich, Julian Hammang, Christopher J Schafferhans, Andrea O'Donoghue, Seán I |
author_facet | Stolte, Christian Sabir, Kenneth S Heinrich, Julian Hammang, Christopher J Schafferhans, Andrea O'Donoghue, Seán I |
author_sort | Stolte, Christian |
collection | PubMed |
description | BACKGROUND: To understand the molecular mechanisms that give rise to a protein's function, biologists often need to (i) find and access all related atomic-resolution 3D structures, and (ii) map sequence-based features (e.g., domains, single-nucleotide polymorphisms, post-translational modifications) onto these structures. RESULTS: To streamline these processes we recently developed Aquaria, a resource offering unprecedented access to protein structure information based on an all-against-all comparison of SwissProt and PDB sequences. In this work, we provide a requirements analysis for several frequently occuring tasks in molecular biology and describe how design choices in Aquaria meet these requirements. Finally, we show how the interface can be used to explore features of a protein and gain biologically meaningful insights in two case studies conducted by domain experts. CONCLUSIONS: The user interface design of Aquaria enables biologists to gain unprecedented access to molecular structures and simplifies the generation of insight. The tasks involved in mapping sequence features onto structures can be conducted easier and faster using Aquaria. |
format | Online Article Text |
id | pubmed-4547178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45471782015-09-10 Integrated visual analysis of protein structures, sequences, and feature data Stolte, Christian Sabir, Kenneth S Heinrich, Julian Hammang, Christopher J Schafferhans, Andrea O'Donoghue, Seán I BMC Bioinformatics Research BACKGROUND: To understand the molecular mechanisms that give rise to a protein's function, biologists often need to (i) find and access all related atomic-resolution 3D structures, and (ii) map sequence-based features (e.g., domains, single-nucleotide polymorphisms, post-translational modifications) onto these structures. RESULTS: To streamline these processes we recently developed Aquaria, a resource offering unprecedented access to protein structure information based on an all-against-all comparison of SwissProt and PDB sequences. In this work, we provide a requirements analysis for several frequently occuring tasks in molecular biology and describe how design choices in Aquaria meet these requirements. Finally, we show how the interface can be used to explore features of a protein and gain biologically meaningful insights in two case studies conducted by domain experts. CONCLUSIONS: The user interface design of Aquaria enables biologists to gain unprecedented access to molecular structures and simplifies the generation of insight. The tasks involved in mapping sequence features onto structures can be conducted easier and faster using Aquaria. BioMed Central 2015-08-13 /pmc/articles/PMC4547178/ /pubmed/26329268 http://dx.doi.org/10.1186/1471-2105-16-S11-S7 Text en Copyright © 2015 Stolte et al. http://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), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Stolte, Christian Sabir, Kenneth S Heinrich, Julian Hammang, Christopher J Schafferhans, Andrea O'Donoghue, Seán I Integrated visual analysis of protein structures, sequences, and feature data |
title | Integrated visual analysis of protein structures, sequences, and feature data |
title_full | Integrated visual analysis of protein structures, sequences, and feature data |
title_fullStr | Integrated visual analysis of protein structures, sequences, and feature data |
title_full_unstemmed | Integrated visual analysis of protein structures, sequences, and feature data |
title_short | Integrated visual analysis of protein structures, sequences, and feature data |
title_sort | integrated visual analysis of protein structures, sequences, and feature data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547178/ https://www.ncbi.nlm.nih.gov/pubmed/26329268 http://dx.doi.org/10.1186/1471-2105-16-S11-S7 |
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