Scientist Stories: M. Madan Babu, Biological Systems at Different Scales of Complexity @axialxyz

Uploaded July 2024 | Updated September 2026, 2 weeks ago

M. Madan Babu is a Member of St Jude Children’s Research Hospital and an Endowed Chair of Biological Data Science in the Department of Structural Biology.

He is also the Director of the Center for Data Driven Discovery. Madan is a Visiting Scientist at the MRC Laboratory of Molecular Biology, UK and an Adjunct Professor in the Department of Biochemistry and Molecular Biology, University of Southern Denmark, Denmark.

Madan has pioneered data science-based approaches to make biological discoveries and reveal fundamental principles in biological systems. His group has developed state-of-the-art computational and machine learning-based methods to interrogate large-scale biological data from diverse organisms. Madan’s group investigates biological systems at different scales of complexity: from systems at the atomic level (e.g., structures) to the network of interactions between molecules (e.g., protein interaction networks) to the level of an entire population (e.g., variation in the human population and cancer genomes). He envisions that his group’s research findings will help us better understand how mutations cause cancer and other diseases. This knowledge can be used in biotechnology, drug discovery, and personalized medicine.

en.wikipedia.org/wiki/M._Madan_Babu

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Scientist Stories: M. Madan Babu, Biological Systems at Different Scales of Complexity

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$Scientist Stories: Joe Marsh, Deep Mutational Scanning Most known Mendelian genetic disorders are caused by changes in protein-coding regions of DNA, yet clinically relevant variants account for only a tiny fraction of those seen in humans. We are interested in understanding the molecular mechanisms by which protein variants can cause disease. While past work has often focused on how sequence changes can cause a loss of protein function, we are especially interested in protein mutations that cause disease via gain-of-function or dominant-negative effects. We believe that through better understanding of the molecular mechanisms, we can improve our ability to predict which variants of uncertain significance are most likely to be pathogenic. Moreover, understanding molecular mechanisms can open the door to future treatment possibilities. To address this, we use three complementary strategies. Structural bioinformatics can provide great insight into the molecular mechanisms underlying disease mutations, but has historically been less useful for identifying deleterious mutations. In contrast, computational variant effect predictors are very good at identifying pathogenic mutations in certain genes, but tell us nothing about why they are damaging. Finally, deep mutational scanning (DMS) experiments, performed in collaboration with the Kudla lab, enable direct high-throughput measurement of variant effects, and are proving tremendously valuable for identifying disease mutations and explaining molecular mechanisms. We also have a strong interest in protein complexes. The emergence of new experimental and computational techniques, along with the increasing availability of diverse structural, proteomic and genomic datasets, have created huge potential for investigating protein complex structure and assembly on a large scale. Consideration of protein quaternary structure is often tremendously useful for understanding the molecular mechanisms underlying disease mutations. We are also interested in the biology of protein complex assembly, seeking to understand how assembly occurs within cells, how it is regulated, how it contributes to normal biological function, and how it has evolved. https://scholar.google.com/citations?user=jdDpvE4AAAAJ&hl=en #biotechnology #science #vc #startup #startups #startupideas #biology #biotech #chemistry #business #speech #speeches #investing #investment #lifescience #casestudy #scientist #scientists #inventors #inventor #inventions #invention #research #innovation #siliconvalley #entrepreneur #entrepreneurship #entrepreneurs #healthcare #genomics #genetics #history #biologia #technology #tech #founderstories #founder #founders #founderstory #scienceandtechnology #sciencestory #stories #bioengineering #engineering #engineer #biochemistry #discovery #discover #technical #health #education #educational #learning #learn #podcast #podcasts #podcasting #podcaster #technews Axial Newsletter: https://axial.substack.com/ Build with Axial: https://build.axialvc.com/ https://linktr.ee/axialxyz$

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