RT Journal Article
SR Electronic
T1 CINNA: Deciphering Central Informative Nodes in Network Analysis
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 168757
DO 10.1101/168757
A1 Minoo Ashtiani
A1 Mohieddin Jafari
YR 2017
UL http://biorxiv.org/content/early/2017/07/26/168757.abstract
AB Motivation With the advancement of data mining technology, created networks from various contexts become more complex and larger, which makes them more difficult to figure out. Recognizing nodes that can influence on the whole network, helps us to comprehend networks easier and faster and so facilitates the process of network analysis. Since several criteria based on the network topological features are defined for identifying influential nodes, we need to know which measure rightfully points at the central nodes in special network.Results The CINNA R package conveniently has brought together all required methods for network centrality analysis. It contains network component segregation, calculation and prioritizing centralities, along with clustering and visualization functions.Availability CINNA package is freely available from the R project at http://cran.r-proiect.org/, http://jafarilab-pasteur.com/content/software/CINNA.html.Contact m_jafari{at}pasteur.ac.ir