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A curated list of awesome machine learning interpretability resources.
Awesome R packages that offer extended UI or server components for the R web framework Shiny
A public list of computational methods for cell type inference from genome-scale DNA methylation data
Code to accompany publication on cell free chromatin immunoprecipitation (cfChIP)
R code to analyze ChIP data
my notes on DNA methylation analysis (arrays and sequencing data)
Integrative analysis for epigenomic sequencing data
'ggplot2' Based Publication Ready Plots
Hepatitis C and CVD meta-analysis
From IDAT to beta.
Python pipeline for analysis of SafeSeqS DNA sequencing data.
A frictionless, pipeable approach to dealing with summary statistics
📊 My contributions to the #TidyTuesday challenge
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.