Name: LANL Molecular Evolution & Epidemiology Team
Type: Organization
Bio: Public health-related work done in the Theoretical Biology & Biophysics Group at Los Alamos National Laboratory
Location: United States of America
Blog: https://public.lanl.gov/tkl/
LANL Molecular Evolution & Epidemiology Team's Projects
Code from Castro et al "Recombination smooths the time-signal disrupted by latency in within-host HIV phylogenies"
Code from Lundgren et al "Combining biomarker and virus phylogenetic models improves epidemiological source identification" in PLOS Computational Biology 2022 Aug 26;18(8):e1009741
Code from Belluccini et al. "A story of viral co-infection, co-transmission and co-feeding in ticks: how to compute an invasion reproduction number"
Code from Kupperman et al_ "Predicting Impacts of Contact Tracing on Epidemiological Inference from Phylogenetic Data" (2023).
Information about this collection of work.
Practice collaborating with git
End-to-End computational pipeline for nationwide HIV outbreak monitoring.
Code from Kupperman et al "A deep learning approach to real-time HIV outbreak detection using genetic data" in PLOS Comp Biol 2022 18(10):e1010598
Code and data from Mbisa et al. "Identification of two novel subtypes of hepatitis C virus genotype 8 and a potential new genotype in the UK successfully treated with direct acting antivirals."
This could be the code for an already-published paper, now public.
SEEPS: Sequence Evolution and Epidemiological Process Simulator
Code from Lin et al., "The number and pattern of viral genomic reassortments are not necessarily identifiable from segment trees", 2024; msae078.
Time-slice Markov model for phylogenetic inference of transmission time