Using computational models, researchers are gaining traction toward understanding what makes a stem cell a stem cell; how gene expression drives stem cell differentiation; why studying stem cell heterogeneity is important; and, ultimately, how stem cells control their fate.
Decades of steady progress in pharmacogenetics have unearthed hundreds of associations between genes and drug response. But the field has to solve some theoretical and practical issues before it can deliver on the promise of personalized drug therapy.
Kim Branson of Vertex Pharmaceuticals uses OpenMM as the GPU accelerator for Yank, a program for quickly estimating molecular binding affinities that he’s building with collaborators from Pande’s lab.
Using Rosetta@Home, a program that runs on the personal computers of 150,000 volunteers worldwide, David Baker’s team predicted the structure of a 112-amino-acid protein from scratch.
Having developed detailed and sophisticated models of both E. Coli and human metabolism, researchers can begin to build toward a whole cell model that will be useful for the study of human health and disease.
The complexity and variability of aging itself, along with the fragmented nature of researchers’ current understanding of aging, call for tools that can help scientists dig through mounds of data to find often subtle connections.
Cultured brain cells draw pictures
Upcoming biocomputing conferences
Classifying variability of gene expression