The structure and behavior of many biological (and other) systems can be effectively represented as networks. We have several projects related to this topic. Below, we provide links to the various software developed in our group for declaring, visualizing, and analyzing networks. We also provide access to our databases containing network representations of several systems. Finally, links to our network-related publications are provided.

Software and Servers Papers
tynaformerly TopNet The Yale Network Analyzer is our primary networks software. It can be used to manage networks in several formats, calculate various statistical properties, perform network operations, and interact with networks visually. tYNA can be used online, downloaded, and also connects to Cytoscape.
tYNA featured in Journal of Proteome Research (html, pdf) and CBHD Newsletter.
2004, 2006
pubnet A flexible system for visualizing literature-derived networks. Input a PubMed query and PubNet outputs a network showing a variety of relationships, such as the degree to which two authors collaborate or the MeSH Term relatedness of publications with PDB id's. 2005
Defective Cliques A collection of scripts and binaries for predicting protein-protein interactions. The central idea is to find defective cliques (nearly complete complexes of pairwise interacting proteins), and predict the interactions that complete them. 2006
YeastHub A lightweight semantic web data warehouse for integrating RDF-formatted yeast data. Register datasets and then peform queries through predefined templates or compose one manually. 2004, 2005
Databases and Datasets Papers
ENCODE human regulatory network Here, we provide the human transcriptional regulatory network constructed from over 400 ChIP-Seq experiments (~120 transcription factors).
2012
Comparing Linux call graph and E. coli regulatory network The networks of E. coli transcriptional regulatory network and the call graph of the Linux operating system.
2010
Metagenomics Dynamics Here, we provide a dataset to relate the usage of particular pathways and subnetworks in recent metagenomics studies to environmental features. We have shown such changes may reflect the adaptation of microbial communities to these different conditions -i.e., how network dynamics relates to environmental features. 2009
SIN Structural Interaction Network. In contrast to the conventional nodes-and-edge view of networks, we provide an atomic resolution view, making extensive use of 3D protein structures and homology mapping. Our network reveals many hitherto unknown trends and evolutionary insight. 2006
Net Hierarchy Relationships between transcription factors (TFs) and their target genes have an extensive pyramid-shaped hierarchical structure. We provide results for E. coli and S. cerevisiae. 2006
IntInt Bayesian approach for predicting protein-protein interactions genome-wide in yeast. Our method integrates noisy, experimental interaction data sets, and, at given levels of sensitivity, we observe that our predictions are more accurate than the existing high-throughput experimental data sets. 2002, 2003, 2005
Sandy Static network analysis has been used widely in biology. Sandy extends this with an approach to analyze network dynamics. 2004
Interolog It is valuable to map large-scale network information from one organism to another using comparative genomics. We have assessed the degree to which this can be done reliably as a function of sequence similarity. Here we provide results using interaction information from C. elegans, D. melanogaster, and H. pylori. 2004
Phosphorylome Using proteome chip technology, we describe the in vitro substrates recognized by most S. cerevisiae protein kinases. Over 4,000 phosphorylation events involving 1,325 different proteins are identified. The results are assembled into a first-generation phosphorylation map. 2005
EChipChip A predicted map for the transcriptional regulatory network in yeast is presented. It is based on reconstructions from expression correlations. 2003
Papers
Click here for a complete list of network-related papers published in our group. Individual references to some of these have also been provided above under the relevant software or database.