Research Expertise and Interest

computational biology, molecular evolution, computational genomics, Systems and Synthetic Biology

Research Description

The Holmes Lab brings techniques from machine learning, statistical linguistics, phylogenetics, and web development to bear on the interpretation and analysis of genomic data. Particular areas of interest include the development of basecalling and analysis software for nanopore sequencing; phylogenetic reconstruction using Bayesian approaches; the use of deep learning to predict and design protein structures; and the development of modern JavaScript user interfaces, backed by fast indexing and in-browser AI, to maximize the impact of genome sequences and annotations.