A phylogeny-aware approach to detecting amino acid coevolution: PHACE. Instead of relying on sequence alignments only, it maps substitutions onto evolutionary trees and accounts for shared ancestry. A nice step toward more accurate models of protein evolution and structure.
All data generated in this study and all benchmark analysis scripts and source codes for PHACE are available at github.com/CompGenomeLa...
Our new algorithm PHACE: Phylogeny-Aware Detection of Molecular Coevolution, by me and Ogün Adebali (@compgenomics.bsky.social), is now published in Molecular Biology and Evolution.
Many thanks to @nehircanozdemir.bsky.social for the beautiful illustration of PHACE!
The image is a poster for the "Variant Effects Seminar Series" dated August 5th, 2025. The top section is a blue header with white, bold text indicating the seminar series name and date. Below, the time for different time zones is given: 9-10 am (PACIFIC), 12-1 pm (EASTERN), and 5-6 pm (GMT). On the left side of the poster, a vertical DNA helix graphic in black is visible. To the right, there are two circular photographs of speakers with talk titles.
Coming up on August 5 🗓️
Nurdan Kuru @nurdankuru.bsky.social shares phylogeny-aware methods for variant effect prediction.
Ferdy van Geest dives into MCT8 variants & thyroid disease. Computational meets clinical! #Genetics #RareDisease #MedicalGenetics ℹ️ www.varianteffect.org/seminar-seri...
#BoG25 at home - CSHL
A gene called NOVA1 may be part of the solution to the mystery of how our ancestors evolved language. Here's my story about mice with strange squeaks. [Gift link] nyti.ms/3XuVehN 🧪
NOVA1, a neuron-specific RNA binding protein & splicing factor, likely impacted language function in human evolution. Human NOVA1 is unique (vs mammals, Neanderthals), & it changes vocalization in CRISPR’d mice!
TY @NatureComms @RockefellerUniv team, collaborators @erichjarvis @asiepel labs
🧵👇