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NeoHiC: A Web Application for the Analysis of Hi-C Data

Authors :
Ivan Merelli
Marco Aldinucci
Daniele D'Agostino
Pietro Liò
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.

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