Homework 2 for MCS 5603 Intro to Bioinformatics. Written in Python.
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Updated
Oct 16, 2014 - Python
Homework 2 for MCS 5603 Intro to Bioinformatics. Written in Python.
Statistical model to detect de-novo mutations using sequencing data from trios and pairs.
Plot Protein: Visualization of Mutations with Conservation
Plot Protein: Visualization of Mutations
Route optimization web application
An Elixir Evolutive Neural Network framework à la G.Sher
Observe and react to changes in distributed nodes in web components, Shadow DOM v0.
♻️ BioJS1.0 Component for visualising human gentic variations, GSoC2014
Just a small function to freeze the entire object avoiding mutability
Discover pseudogenes in a newly assembled genome, using reference gene/protein sequences.
High order component for Lokka GraphQL client
R tools to mine & craft somatic mutations from cancer genomes
Simple example of GraphQL implementation with Ruby on Rails and ReactJS
Deep learning neural network to analyse variant-call data, with a Bayesian network to rank functionally important genes
WOLAND is a multiplatform tool to analyze point mutation patterns using resequencing data from any organism or cell. It is implemented as a Perl and R tool using as inputs filtered unannotated or annotated SNV lists, combined with its correspondent genome sequences.
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