Utility to generate codon mutations of a given coding DNA sequence
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Updated
Jun 7, 2020 - Python
Utility to generate codon mutations of a given coding DNA sequence
Generating random mutations
Snakemake Pipeline for the Analyses of ChIP-seq data in Cancer samples
The Cancer Genome Atlas (TCGA), a cancer genomics reference program, has molecularly characterized more than 20,000 primary cancer samples and paired normal samples covering 33 types of cancer. This joint effort between the NCI and the National Human Genome Research Institute began in 2006.
Automated analysis tool for mutations in promoters, transcription factor binding sites, coding regions and protein domains in the context of gene regulatory networks.
MSc Bioinformatics with Systems Biology Dissertation
A re-implementation in Python3 of the open source project MutationFinder for gene mutation detection in free text.
Creation of a simple genetic algorithm in order to find the phrase "methinks it is like a weasel", with and without the use of crossover
Deep learning neural network to analyse variant-call data, with a Bayesian network to rank functionally important genes
Official repository for the paper "Few-shot Prediction of the experimental functional measurements for proteins with single point mutations".
During the progression of cancer cells, the degree of genome instability increases leading to genome chaos in populations of malignant cells. While normally chaos is associated with ergodicity, i.e., the state when the time average of relevant parameters is equal to the phase space average, the situation with cancer propagation is more complex.
Using gnomad-browser's GraphQL updated API to retrieve total joint allele frequencies, exome/genome allele frequencies and homozygote counts as well as population specific numbers for a batch of variants.
Chromosomal mutations associated with nitrofurantoin resistance in Escherichia coli
A genetic algorithm that attempts to get a swarm of dots from the start point to the end goal in the least number of steps
Assignments from Professor Roman Yampolskiy's Artificial Intelligence class.
Homework 2 for MCS 5603 Intro to Bioinformatics. Written in Python.
A bioinformatics pipeline to identify the best available PDB structures for all available variants for specified genes of interest
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