The University of Toronto's Mikko Taipale is working on developing new technologies to pave the way for gaining new biological insights.
Technion's Reut Shalgi is building up her lab to study how chaperones affect protein synthesis and protein folding.
EMBL-EBI's Oliver Stegle is taking a statistical approach to understanding genotype-phenotype associations.
Harvard Medical School's Kaitlin Samocha is studying de novo mutations linked to complex diseases like autism and schizophrenia.
Pacific Northwest National Laboratory's Sangtae Kim is taking on the challenges of analyzing top-down proteomic data.
At Brigham and Women's Hospital, Kimberly Glass is integrating different types of omics data to develop useful gene models.
Duke University's Slavé Petrovski is working to elucidate which genetic variations are likely benign versus ones that may be linked to disease.
By modeling organisms with systems biology data, Mount Sinai School of Medicine's Jonathan Karr plans to eventually engineer bacteria.
The Genome Institute of Singapore's Yue Wan is interested in why RNA folds as it does.
Sick Kids' Mohammed Uddin is analyzing various types of gene expression and mutational data to better understand autism.
A phylogenetic analysis indicates two venomous Australian spiders are more closely related than thought, the International Business Times reports.
Technology Review reports that 2017 was the year of consumer genetic testing and that it could spur new analysis companies.
In Science this week: CRISPR-based approach for recording cellular events, and more.
A new company says it will analyze customers' genes to find them a suitable date, though Smithsonian magazine says the science behind it might be shaky.