Carlos D. Wang's Projects
Machine Learning: An Algorithmic Perspective, second edition
Machine Learning Interpretability Resources
mTCTScan Help page
A needle plot for mutation data
Optional static typing for Python 2 and 3 (PEP 484)
Network Clustering in python
Ontology visualisation widget for EBI's Ontology Lookup Service (OLS)
PDV: an integrative proteomics data viewer
PGA: a tool for ProteoGenomics Analysis
PHESANT - PHEnome Scan ANalysis Tool (pheWAS, Mendelian randomisation (MR)-pheWAS etc.) in UK Biobank
Interactive in-browser track viewer
P-NET, Biologically informed deep neural network for prostate cancer classification and discovery
Python code for "Machine learning: a probabilistic perspective"
A Python library for reading and manipulating genetic data.
All Algorithms implemented in Python
This repository contains the code associated with the "Working With Algorithms In Python" Safari Video. http://shop.oreilly.com/product/110000667.do
This repository contains the code associated with the "Designing Data Structures in Python: Principles & Practice" Safari Video. https://www.safaribooksonline.com/library/view/designing-data-structures/9781491928622/
The "Python Machine Learning" book code repository and info resource
The "Python Machine Learning (2nd edition)" book code repository and info resource
IQSS RTC workshop materials
Data Sets of Youtube Channel Rahul_CODIFY
Code and tutorials to visualise your data that is both beautiful *and* statistically valid
Integrate DNA-seq and RNA-seq data to identify mutations that are associated with regulatory effects on gene expression.
materials for the RNA-Seq workshop on Trinity and Tuxedo, covering de novo and genome-guided transcript assembly and downstream analysis.
Informatics for RNA-seq: A web resource for analysis on the cloud. Educational tutorials and working pipelines for RNA-seq analysis including an introduction to: cloud computing, critical file formats, reference genomes, gene annotation, expression, differential expression, alternative splicing, data visualization, and interpretation.
Tutorial: Bayesian Statistical Analysis in Python
Scikit-Learn tutorial material for Scipy 2015