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Name: Erick Lu
Type: User
Bio: Immunologist | Bioinformaticist | Gaining insights from biological data | UCSF PhD
Location: San Francisco
Name: Erick Lu
Type: User
Bio: Immunologist | Bioinformaticist | Gaining insights from biological data | UCSF PhD
Location: San Francisco
Takes a collection of PubMed abstracts and creates an equidistant time series of the number of papers published over time, using python/pandas.
A complete guide for analyzing bulk RNA-seq data. Go from raw FASTQ files to mapping reads using STAR and differential gene expression analysis using DESeq2, using example data from Guo et al. 2019.
Model the number of cancer papers published over time and visualize the data using the TSA package in R.
Use R to clean and analyze RNA-seq data from 64 cell lines from The Human Protein Atlas and identify differentially expressed genes.
Analyze bulk RNA-seq data from Li et al. 2016 to identify upregulated genes in activated dendritic cells.
Modified the square.github.io website to turn it into a data analysis portfolio.
A compilation of public databases for determining gene expression patterns and survival associations. No coding required!
Use Matlab to break an image into blocks and export properties for each block. Then use R to analyze the output.
Notes from my walkthrough of the SQL tutorial by Mode, including solutions to their exercises
Python script that downloads all pubmed abstracts corresponding to user-specified keyword searches, by performing automated NCBI E-utility queries
A guide on how to find and download raw RNA-seq data from GEO. Batch download FASTQ files using a Python script and the NCBI SRA tools prefetch and fastq-dump.
A walkthrough of Hadley Wickham and Garrett Grolemund's book, R for data science (r4ds), with my solutions to their exercises and some of my own notes and data explorations.
A guide for analyzing single-cell RNA-seq data using the R package Seurat. Go from raw data to cell clustering, identifying cell types, custom visualizations, and group-wise analysis of tumor infiltrating immune cells using data from Ishizuka et al. Nature 2019.
Use Python to scrape ESPN for stats on all players in the NBA. Obtain and organize data, calculate statistics, and model using urllib, re, pandas, and scikit-learn.
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.