DATA & MODELS
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 Publication.
The NeST (Nested Systems in Tumors) map is a hierarchy of 395 protein systems that are recurrently mutated in one or more cancer types. It provides a resource of cancer mechanisms under selection for somatic mutations and captures canonical cancer pathways and protein complexes, along with novel protein assemblies on which mutations unexpectedly converge.
Publication: Zheng F*, Kelly MR*, et al. Interpretation of cancer mutations using a multiscale map of protein systems. Science (2021)
Mapping a human cell gives researchers a view of subcellular architecture and sheds light on how cancer develops. Learn more about the U2OS Cell Map here.
The Multi-Scale Integrated Cell (MuSIC) Map is a comprehensive map of eukaryotic cell architecture, constructed by systematically integrating diverse proteomic data. Using a robust computational framework, MuSIC combines data from tens of thousands of protein interactions and images to create a detailed hierarchy of cellular components and processes, accessible through NDEx.
Publications:
- Schaffer, Hu, et al. Multimodal cell maps as a foundation for structural and functional genomics. Nature (2025)
- Qin, et al. Mapping cell structure across scales by fusing protein images and interactions. Nature (2021)
Related Press:
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.
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:
DDRAm – DNA Damage Response Assemblies Map
DCell
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.
Quantitative Translation of Dog-to-Human Aging by Conserved Remodeling of the DNA Methylome. Cell Systems (2020). [PDF] [PubMed]
Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA. Mol Cell. (2016). [PDF] [PubMed]
- GitHub Source Code
- “People Who Are HIV-Positive May Be Aging Faster Than Their Peers” (NPR)