MuRaL is a deep learning framework for estimating single-nucleotide mutation rates across the genome.
-
Updated
Jul 1, 2024 - Python
MuRaL is a deep learning framework for estimating single-nucleotide mutation rates across the genome.
Nextflow pipeline for estimation of evolutionary rate using Bayesian statistics.
Reports frequency of all single nucleotide changes for a group of fastq files
Algorithms for the generation of substitution matrices from intra-taxa variation data. Implemented and published on human genetic variation data.
A biologically motivated mathematical formalism is used to estimate the relative risks of breast, lung and thyroid cancers in childhood cancer survivors due to concurrent therapy regimen. This model specifically includes possible organ-specific interaction between radiotherapy and chemotherapy. The model predicts relative risks for developing se…
We employed a biologically motivated mathematical model to estimate the radiation and chemotherapy-induced relative risks of thyroid malignancies in four childhood cancer study survivors (CCSS) data sets. the predictions of radiation and chemotherapy-induced relative risks of secondary thyroid malignancies using the mathematical model are compar…
Add a description, image, and links to the mutation-rate topic page so that developers can more easily learn about it.
To associate your repository with the mutation-rate topic, visit your repo's landing page and select "manage topics."