Emili Collaboratory for Network Systems Biology

The ‘Collaboratory for Network Systems Biology’ at the Knight Cancer Institute at Oregon Health & Science University (OHSU), led by Professor Andrew Emili, supports ambitious research initiatives aimed at mapping macromolecular interactions crucial to human health and disease, most notably cancer.

Dynamic physical and functional interactions occur among the diverse array of cellular biomolecules, and their systematic discovery is key to advancing fundamental mechanistic understanding of complex biological processes and their relationship to human pathobiology.

What we do

The CNSB serves as a central hub from which to chart dynamic molecular networks – an important emerging focus area at the OHSU Knight Cancer Institute. CNSB provides essential interdisciplinary knowledge, access to advanced instrumentation, as well as the technical prowess to get to the heart of network biology.
As a leader in the field, the Emili lab has established burgeoning research collaborations across the Knight and the Depts of Chemical Physiology & Biochemistry, Bioengineering, Medicine, and other programs at OHSU, and we strive for lasting connections and productive partnerships.

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Our Research

Human health and development stem from precise, spatiotemporally regulated protein-protein interactions and protein-ligand binding. However, many details of these interaction networks – where they are formed, how they are controlled, and when they become dysregulated in disease – are often poorly understood, particularly for complex heterogeneous pathologies such as infection, neurodegeneration, cardiovascular disease, and cancer.

Our Team

We are assembling a bold and highly talented team of researchers at the CNSB who are focused on developing and deploying innovative ‘functional proteomics’, ‘spatial proteomics’, and integrative bioinformatics technologies to address especially challenging research questions.
Our multi-disciplinary platform combines advances in precision mass spectrometry, molecular genetics, structural modelling and data sciences/machine learning to systematically characterize the networks protein interactions that occur on or inside cells and tissues and to determine which of these are most relevant to human pathology and disease progression.