Prettycloud: Visualizing weighted and grouped genomic context with mathematical curves

Miao, P; Sablok, G; Zhang, Q; Tao, M; Zhu, B; Feng, G; Sun, X

Prettycloud: Visualizing weighted and grouped genomic context with mathematical curves

Miao, P Sablok, G

Zhang, Q Tao, M Zhu, B Feng, G Sun, X

Permalink

Publication Type:: Conference Proceeding
Citation:: 2017 2nd IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2017, 2017, pp. 400 - 403
Issue Date:: 2017-06-16

Closed Access

	Filename	Description	Size
	07951946.pdf	Published version	582.13 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Miao, P	en_US
dc.contributor.author	Sablok, G https://orcid.org/0000-0002-4157-9405	en_US
dc.contributor.author	Zhang, Q	en_US
dc.contributor.author	Tao, M	en_US
dc.contributor.author	Zhu, B	en_US
dc.contributor.author	Feng, G	en_US
dc.contributor.author	Sun, X	en_US
dc.date.issued	2017-06-16	en_US
dc.identifier.citation	2017 2nd IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2017, 2017, pp. 400 - 403	en_US
dc.identifier.isbn	9781509044986	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126422
dc.description.abstract	© 2017 IEEE. Biological networks and visualization of the frequent terms in networks offers a key scenario to visualize and link the biological terms, which are representative of the physiological experiment. Plethora of the publications recently using the RNA-Seq has widely elucidated the organismal biology. However, the embedded annotations are dispersed across representative publications and present end-user a cumbersome task of visually looking at annotations files for the over-represented categories. In the present paper, we present an R package for the visualization of the most frequent annotation terms using math curve functions. The developed pack-age allows for the visualization of the abundant terms in clustered way using weighted indices and present the visualization of the abundance of the terms in relation to word size, font and coloring as per the frequency of the observed word, prettycloud is implementegd in R, and is supported on Windows, Linux and MAC OSX, and freely available at https://sourceforge.net/ projects/prettycloud/or http://genome.sdau.edu.cn/research/software/prettycloud.html (Figure 1).	en_US
dc.relation.ispartof	2017 2nd IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2017	en_US
dc.relation.isbasedon	10.1109/ICCCBDA.2017.7951946	en_US
dc.title	Prettycloud: Visualizing weighted and grouped genomic context with mathematical curves	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - C3 - Climate Change Cluster
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. Biological networks and visualization of the frequent terms in networks offers a key scenario to visualize and link the biological terms, which are representative of the physiological experiment. Plethora of the publications recently using the RNA-Seq has widely elucidated the organismal biology. However, the embedded annotations are dispersed across representative publications and present end-user a cumbersome task of visually looking at annotations files for the over-represented categories. In the present paper, we present an R package for the visualization of the most frequent annotation terms using math curve functions. The developed pack-age allows for the visualization of the abundant terms in clustered way using weighted indices and present the visualization of the abundance of the terms in relation to word size, font and coloring as per the frequency of the observed word, prettycloud is implementegd in R, and is supported on Windows, Linux and MAC OSX, and freely available at https://sourceforge.net/ projects/prettycloud/or http://genome.sdau.edu.cn/research/software/prettycloud.html (Figure 1).

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/126422