Dear R package developers and users,

I am pleased to announce the official release of our newly developed
package 'dnet', which intends to analyse omics data in terms of network,
evolution and ontology.

It has features:
1. Identification of gene-active networks from high-throughput omics data;
2. Network-based sample classifications and visualisations on 2D sample
landscape;
3. Random Walk with Restart for network affinity calculation;
4. Semantic similarity between ontology terms (and between their annotated
genes);
5. Enrichment analysis using a variety of built-in databases;
6. A wide variety of built-in RData (
http://dnet.r-forge.r-project.org/rdata.html): ontologies (including Gene
Ontology, Disease Ontology, Human Phenotype and Mammalian Phenotype), gene
evolutionary age information and gene association networks in well-studied
organisms, including human, mouse, rat, chicken, c.elegans, fruitfly,
zebrafish and arabidopsis;
7. Support for high-performance parallel computing.

For it to be used widely, we have analysed several realcases with
step-by-step protocols (http://dnet.r-forge.r-project.org/demos.html).
Since it supports many functionalities, we also introduce them individual
topics in the form of FAQs (http://dnet.r-forge.r-project.org/faqs.html).

Enjoy it!

Hai Fang, Ph.D.
>From Prof. Gough's Group (http://bioinformatics.bris.ac.uk)
Department of Computer Science
Univeristy of Bristol
Bristol, United Kingdom
hfang@cs.bris.ac.uk
http://www.cs.bris.ac.uk/~hfang

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