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MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks

Thanks to recent advances in sequencing and computational technologies, many researchers with biological and/or medical backgrounds are now producing multiple data sets with an embedded temporal dimension. Multi-modalities enable researchers to explore and investigate different biological and physic...

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Autores principales: Anžel, Aleksandar, Heider, Dominik, Hattab, Georges
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8886009/
https://www.ncbi.nlm.nih.gov/pubmed/35284047
http://dx.doi.org/10.1016/j.csbj.2022.02.012
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author Anžel, Aleksandar
Heider, Dominik
Hattab, Georges
author_facet Anžel, Aleksandar
Heider, Dominik
Hattab, Georges
author_sort Anžel, Aleksandar
collection PubMed
description Thanks to recent advances in sequencing and computational technologies, many researchers with biological and/or medical backgrounds are now producing multiple data sets with an embedded temporal dimension. Multi-modalities enable researchers to explore and investigate different biological and physico-chemical processes with various technologies. Motivated to explore multi-omics data and time-series multi-omics specifically, the exploration process has been hindered by the separation introduced by each omics-type. To effectively explore such temporal data sets, discover anomalies, find patterns, and better understand their intricacies, expertise in computer science and bioinformatics is required. Here we present MOVIS, a modular time-series multi-omics exploration tool with a user-friendly web interface that facilitates the data exploration of such data. It brings into equal participation each time-series omic-type for analysis and visualization. As of the time of writing, two time-series multi-omics data sets have been integrated and successfully reproduced. The resulting visualizations are task-specific, reproducible, and publication-ready. MOVIS is built on open-source software and is easily extendable to accommodate different analytical tasks. An online version of MOVIS is available under https://movis.mathematik.uni-marburg.de/ and on Docker Hub (https://hub.docker.com/r/aanzel/movis).
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spelling pubmed-88860092022-03-11 MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks Anžel, Aleksandar Heider, Dominik Hattab, Georges Comput Struct Biotechnol J Research Article Thanks to recent advances in sequencing and computational technologies, many researchers with biological and/or medical backgrounds are now producing multiple data sets with an embedded temporal dimension. Multi-modalities enable researchers to explore and investigate different biological and physico-chemical processes with various technologies. Motivated to explore multi-omics data and time-series multi-omics specifically, the exploration process has been hindered by the separation introduced by each omics-type. To effectively explore such temporal data sets, discover anomalies, find patterns, and better understand their intricacies, expertise in computer science and bioinformatics is required. Here we present MOVIS, a modular time-series multi-omics exploration tool with a user-friendly web interface that facilitates the data exploration of such data. It brings into equal participation each time-series omic-type for analysis and visualization. As of the time of writing, two time-series multi-omics data sets have been integrated and successfully reproduced. The resulting visualizations are task-specific, reproducible, and publication-ready. MOVIS is built on open-source software and is easily extendable to accommodate different analytical tasks. An online version of MOVIS is available under https://movis.mathematik.uni-marburg.de/ and on Docker Hub (https://hub.docker.com/r/aanzel/movis). Research Network of Computational and Structural Biotechnology 2022-02-22 /pmc/articles/PMC8886009/ /pubmed/35284047 http://dx.doi.org/10.1016/j.csbj.2022.02.012 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Anžel, Aleksandar
Heider, Dominik
Hattab, Georges
MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks
title MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks
title_full MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks
title_fullStr MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks
title_full_unstemmed MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks
title_short MOVIS: A multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks
title_sort movis: a multi-omics software solution for multi-modal time-series clustering, embedding, and visualizing tasks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8886009/
https://www.ncbi.nlm.nih.gov/pubmed/35284047
http://dx.doi.org/10.1016/j.csbj.2022.02.012
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