Scientist Stories: Uri Alon, Geometry of Phenotype Space
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Uri Alon is a pioneer of systems biology and a professor at the Weizmann Institute of Science. Train as a physicist, his research develops quantitative tools to understand how parts of the cells all work together. Merging wet-lab experiments with mathematical theory to define general principles of biological circuits within cells.
His work to define the design principles of biology began in Tel Aviv, Israel where he studied physics & mathematics during college. Then going to Hebrew University in Jerusalem for a physics masters and earning a physics PhD at Weizmann. After a postdoc at Princeton, he went back to Israel to join the Weizmann faculty in 1999.
A key theme of his work is understanding the ‘unity of opposites’ that exists across. Modeling how biological circuits can have so much resilience with a dynamic range of fluctuations for each of their components. During his career he has written an essay and a book that is a must read for all scientists:
Systems biology provides a framework for assembling models of biological systems from systematic measurements. Since the field’s emergence over the last ~2 decades, progress in computation/modeling power and new tools to globally measuring cells (i.e single-cell RNA-seq) have led to new maps, and models, of the cell. From genetic interaction maps to systems approaches to hone in on disease genes & new biomarkers. Expanding into translation sciences, for exampling influence how the immune system is therapeutically targeted. Or helping engineer stem cell therapeutics.
However, if you ask a 100 biologists for a definition of systems biology. You’ll get >100 different answers. In theory, systems biology allows us to see life in a bigger picture. In practice, discoveries/models made at one scale (organism, tissue, cell) may not be sufficient to explain phenomena at others. Higher resolution tools like microscopes and proteomics are needed.
But systems biology offers a complementary approach to reductionist biology. Where the former tries to put the pieces together, explaining the whole. The latter taking pieces apart and explaining each other; driving most of the breakthroughs in molecule biology.
Compared to conventional views on systems biology. It is not just fancy bioinformatics. Or baroque computational models. It is a methodology for large-scale quantification of biology. For example, the immune system involves >1,500 genes/proteins in many interconnected pathways and processes. A systems approach has been critical to understand how our immune system responds to things like infections & vaccinations. Where changes in molecular pathways can be detected using high-throughput ‘omics datasets (i.e. transcriptomics, proteomics, and metabolomics). Using methods such as pathway enrichment, network analysis, and machine learning.
These methods have been pointed toward the developmental trajectory of neonates during the first week of life, mechanisms in host-pathogen interactions, disease prognosis, biomarker discovery, drug discovery, and more.
