PT  - JOURNAL ARTICLE
AU  - Mohith Manjunath
AU  - Yi Zhang
AU  - Steve H. Yeo
AU  - Omar Sobh
AU  - Nathan Russell
AU  - Christian Followell
AU  - Colleen Bushell
AU  - Umberto Ravaioli
AU  - Jun S. Song
TI  - ClusterEnG: An interactive educational web resource for clustering big data
AID  - 10.1101/120915
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 120915
4099  - http://biorxiv.org/content/early/2017/03/27/120915.short
4100  - http://biorxiv.org/content/early/2017/03/27/120915.full
AB  - Summary Clustering is one of the most common techniques used in data analysis to discover hidden structures by grouping together data points that are similar in some measure into clusters. Although there are many programs available for performing clustering, a single web resource that provides both state-of-the-art clustering methods and interactive visualizations is lacking. ClusterEnG (acronym for Clustering Engine for Genomics) provides an interface for clustering big data and interactive visualizations including 3D views, cluster selection and zoom features. ClusterEnG also aims at educating the user about the similarities and differences between various clustering algorithms and provides clustering tutorials that demonstrate potential pitfalls of each algorithm. The web resource will be particularly useful to scientists who are not conversant with computing but want to understand the structure of their data in an intuitive manner.Availability ClusterEnG is part of a bigger project called KnowEnG (Knowledge Engine for Genomics) and is available at http://education.knoweng.org/clustereng.Contact songi{at}illinois.edu