Prasad Tangirala Venkateswara, Babu Ravindra Pentela, Ahson Syed Ismail
Department of Computer Science, Jamia Millia Islamia University, New Delhi 110 025, India.
Bioinformation. 2006 Jan 26;1(3):83-5. doi: 10.6026/97320630001083.
Currently available micro-array gene expression data analysis tools lack standardization at various levels. We developed GEDAS (gene expression data analysis suite) to bring various tools and techniques in one system. It also provides a number of other features such as a large collection of distance measures and pre-processing techniques. The software is an extension of Cluster 3.0 (developed based on Eisen Lab's Cluster and Tree View software). GEDAS allows the usage of different datasets with algorithms such as k-means, HC, SVD/PCA and SVM, in addition to Kohonen's SOM and LVQ.