The following data & models have been highlighted here for ease of access: Interaction Networks, Hierarchical Cell Models, and Aging Models. Additionally, specific data sets are listed with their corresponding paper on the Publications Page

Interaction Networks

The Ideker Laboratory has assembled and published many gene and protein interaction networks, which are available on the Network Data Exchange (NDEx) website. The NDEx Project provides an open-source framework where scientists and organizations can share, store, manipulate, and publish biological network knowledge.

The Network Data Exchange (NDEx)

Hierarchical Cell Models

Our computational analysis pipelines translate molecular networks and other data from genomics into hierarchical models of the cell. Web portals for each of these models are linked below:

MuSIC 1.0 - Multi-Scale Integrated Cel
DDRAm - DNA Damage Response Assemblies Map
Autophagy Ontology (AtgO)
Network Extracted Ontology (NeXO)

Aging Models

Epigenetic aging. In 2013 we showed that large parts of the methylome are remodeled with age, a process that is accelerated by disease and slowed in certain genotypes and in women versus men. These findings led to the first “epigenetic clock” model for predicting rate of biological aging (Hannum et al. Cell. 2013). We have since reported that these changes are accelerated by viral infection (Gross et al. Mol. Cell. 2016) and slowed by anti-aging treatments such as caloric restriction and rapamycin (Wang et al. Genome Biology 2017). Most recently, we used epigenetic profiles to translate age between humans and dogs (Wang et al., Cell Systems 2020). Comparison of Labrador retriever and human methylomes revealed a nonlinear relationship between dog and human aging which did not follow the conventional wisdom that 1 dog year = 7 human years, leading to a story that was popularized by many news outlets.

Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, Klotzle B, Bibikova M, Fan JB, Gao Y, Deconde R, Chen M, Rajapakse I, Friend S, Ideker T*, Zhang K*., Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates. Mol Cell. 2013 Jan 24;49(2):359-367. doi: 10.1016/j.molcel.2012.10.016. Epub 2012 Nov 21. [PDF] [PubMed] *Corresponding authors

"People Who Are HIV-Positive May Be Aging Faster Than Their Peers" (NPR)

Gross AM, et al. Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA. Mol Cell. 2016 Apr 21. [PDF] [PubMed]

Wang T, et al. Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment. Genome Biology. 2017 Mar 28. [PDF[PubMed]