Nardus Mollentze's Projects
Code and data used in Mollentze et al. (2022) "Variation in the ACE2 receptor has limited utility for SARS-CoV-2 host prediction".
A python library for generating and manipulating BEAST 1 XML files
Borrelia mapping and variant calling snakemake pipeline
A fork of LSHTM's COVID-19 model to adapt to our data
A python library for calculating geographical summary statistics
Code used in Sugrue et al. (2021), "The interferon resistance of transmitted HIV-1 is a consequence of enhanced replicative fitness".
Code for the machine learning component of Shaw, Rihn, Mollentze, et al. (2021) "The ‘antiviral state’ has shaped the CpG composition of the vertebrate interferome".
Package for hdf5 processing in R
Packaged version of Delasalles et al.'s spatio-temporal neural network model
Code and data used in Mollentze et al. (2021) "Identifying and prioritizing potential human-infecting viruses from their genome sequences".