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NeoHiC: A Web Application for the Analysis of Hi-C Data
- Source :
- Computational Intelligence Methods for Bioinformatics and Biostatistics ISBN: 9783030630607, CIBB, CIBB 2019: Computational Intelligence Methods for Bioinformatics and Biostatistics, pp. 98–107, Bergamo, Italy, 4-6/9/2019, info:cnr-pdr/source/autori:D'Agostino D.; Lio P.; Aldinucci M.; Merelli I./congresso_nome:CIBB 2019: Computational Intelligence Methods for Bioinformatics and Biostatistics/congresso_luogo:Bergamo, Italy/congresso_data:4-6%2F9%2F2019/anno:2020/pagina_da:98/pagina_a:107/intervallo_pagine:98–107, Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2019), pp. 29–32, Bergamo, Italy, 4-6/9/2019, info:cnr-pdr/source/autori:D. D'Agostino, I. Merelli, M. Aldinucci, and P. Liò/congresso_nome:Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2019)/congresso_luogo:Bergamo, Italy/congresso_data:4-6%2F9%2F2019/anno:2019/pagina_da:29/pagina_a:32/intervallo_pagine:29–32
- Publication Year :
- 2020
- Publisher :
- Springer International Publishing, 2020.
-
Abstract
- High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of chromatin interactions and 3D chromosome folding on a larger scale. A graph-based multi-level representation of Hi-C data is essential for proper visualisation of the spatial pattern they represent, in particular for comparing different experiments or for re-mapping omics-data in a space-aware context. The size of the HiC data hampers the straightforward use of currently available graph visualisation tools and libraries. In this paper, we present the first version of NeoHiC, a user-friendly web application for the progressive graph visualisation of Hi-C data based on the use of the Neo4j graph database. The user could select the richness of the environment of the query gene by choosing among a large number of proximity and distance metrics.
- Subjects :
- Computer science
0206 medical engineering
Context (language use)
web app
02 engineering and technology
computer.software_genre
Chromosome conformation capture
03 medical and health sciences
Chromosome (genetic algorithm)
Hi-C
Web application
Representation (mathematics)
030304 developmental biology
0303 health sciences
Information retrieval
Graph database
business.industry
Graph visualisation
Visualization
graph databases
Graph (abstract data type)
graph visualization
business
computer
020602 bioinformatics
Subjects
Details
- ISBN :
- 978-3-030-63060-7
- ISBNs :
- 9783030630607
- Database :
- OpenAIRE
- Journal :
- Computational Intelligence Methods for Bioinformatics and Biostatistics ISBN: 9783030630607, CIBB, CIBB 2019: Computational Intelligence Methods for Bioinformatics and Biostatistics, pp. 98–107, Bergamo, Italy, 4-6/9/2019, info:cnr-pdr/source/autori:D'Agostino D.; Lio P.; Aldinucci M.; Merelli I./congresso_nome:CIBB 2019: Computational Intelligence Methods for Bioinformatics and Biostatistics/congresso_luogo:Bergamo, Italy/congresso_data:4-6%2F9%2F2019/anno:2020/pagina_da:98/pagina_a:107/intervallo_pagine:98–107, Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2019), pp. 29–32, Bergamo, Italy, 4-6/9/2019, info:cnr-pdr/source/autori:D. D'Agostino, I. Merelli, M. Aldinucci, and P. Liò/congresso_nome:Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2019)/congresso_luogo:Bergamo, Italy/congresso_data:4-6%2F9%2F2019/anno:2019/pagina_da:29/pagina_a:32/intervallo_pagine:29–32
- Accession number :
- edsair.doi.dedup.....842c1208b202ab9021e35e7782148f59
- Full Text :
- https://doi.org/10.1007/978-3-030-63061-4_10