Evolutionary and Computational Biology
Image Credit: Page Lab
Research in Evolutionary and Computational Biology leverages large-scale genomic, transcriptomic and related data across diverse species to unlock the molecular mechanisms of life.
Patrick Aoude
Matthew Leventhal
Anders Sejr Hansen
Predicting sequence from structure
Researchers have devised a faster, more efficient way to design custom peptides and perturb protein-protein interactions.
Engineering "capture compounds" to probe cell growth
Researchers develop a method to investigate how bacteria respond to starvation and to identify which proteins bind to the "magic spot" - ppGpp.
Computer model offers more control over protein design
New approach generates a wider variety of protein sequences optimized to bind to drug targets.
Designing synthetic proteins that can act as drugs for cancer or other diseases can be a tedious process: It generally involves creating a library of millions of proteins, then screening the library to find proteins that bind the correct target.
Decoding RNA-protein interactions
Thanks to continued advances in genetic sequencing, scientists have identified virtually every A, T, C, and G nucleotide in our genetic code. But to fully understand how the human genome encodes us, we need to go one step further, mapping the function of each base.
CSB Thesis Defense
Student: Amanda Kedaigle
Lab: Fraenkel
Title: Integrating Omics Data: A new Software Tool and its Use in Implicating Therapeutic Targets in Huntington's Disease
Scientists find different cell types contain the same enzyme ratios
New discovery suggest that all life may share a common design principle.
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