CryptoNet is

a probabilistic functional gene network for Cryptococcusn neoformans. Edge information for all data-specific networks as well as the integrated network is available from Download page.


Various network biology approaches such as guilt-by-association have been widely employed in generating novel hypotheses for gene functions and gene-phenotype associations. CryptoNet also provides such network biology tools to (i) find new members of a pathway, (ii) infer functions from network neighbors, (iii) Find context associated hub genes.


CryptoNet was constructed by Bayesian integration of many networks inferred from 14 distinct types of genomics and proteomics data listed in the following table.


Data type Code Description
CN-CC Inferred links by co-citation of two genes across 609 PubMed Central articles for C. neoformans biology
CN-CX Inferred links by co-expression pattern of two C. neoformans genes (based on high-dimensional gene expression data)
CN-DC Inferred links by co-occurrence of protein domains between two C. neoformans coding genes
CN-GN Inferred links by similar genomic context of bacterial orthologs of two C. neoformans genes
CN-PG Inferred links by similar phylogenetic profiles between two C. neoformans genes
HS-HT Associalogs by high-throughput human protein-protein interactions
HS-LC Associalogs by small/medium-scale human protein-protein interactions
(collected from protein-protein interaction data bases)
SC-CC Associalogs by co-citation of two genes across 46,111 PubMed Medline abstracts for yeast biology
SC-CX Associalogs by co-expression pattern of two yeast genes (based on high-dimensional gene expression data)
SC-DC Associalogs by co-occurrence of protein domains between two yeast coding genes
SC-GT Associalogs by similar profiles of yeast genetic interaction partners
SC-HT Associalogs by high-throughput yeast protein-protein interactions
SC-LC Associalogs by small/medium-scale yeast protein-protein interactions
(collected from protein-protein interaction data bases)
SC-TS Associalogs by protein ineteractions from yeast tertiary structures of complexes


Citation
Hanhae Kim, Kwang-Woo Jung, Shinae Maeng, Ying-Lien Chen, Junha Shin, Jung Eun Shim, Sohyun Hwang, Guilhem Janbon, Taeyup Kim, Joseph Heitman, Yong-Sun Bahn* and Insuk Lee*, Network-assisted genetic dissection of pathogenicity and drug resistance in the opportunistic human pathogenic funcgus Cryptococcus neoformans. Scientific Reports 2015 Mar 5;5:8767 (link)

Contact information
Insuk Lee (insuklee (at) yonsei.ac.kr)

Funding
This work was supported by the National Research Foundation of Korea grant (2010-0017649, 2012M3A9B4028641, 2012M3A9C7050151).