These are the collections of things that I beleived useful in my daily researh work.
Training
- Another Book on Data Science- Learn R and Python in Parallel
- Bioinformatics at COMAV
- HarvardX Biomedical Data Science Open Online Training - rafalab
- Next-Generation Sequencing Analysis Resources -NGS analysis, concepts
- Research Informatics Training - University of Cambbridge
- Introduction to Bioinformatics workflows with Nextflow and nf-core
- National cancer institute GDC documentation
- Bioinformatics for Biologists
- National Cancer Institute: Bioinformatics Training & Education Program
- High dimensional statistics with R Introduction to high-dimensional data
- Bioinformatics Training at the Harvard Chan Bioinformatics Core
- STATQUEST!!!
- Protocols - Beiting Lab
Biologist
Research Labs
- http://rafalab.dfci.harvard.edu/ - Development of statistical tools
- https://liulab-dfci.github.io/ - Computational methods for the design (SSC), analysis (MAGeCK), hit prioritization (NEST), and visualization (VISPR) of genome-wide CRISPR screens
- https://www.jax.org - Leading the research for tomorrow’s cures
- https://www.snijderlab.org/ - Use systems biology to discover things about cells.
- https://zlab.bio/ - Zhang Feng Biological Discovery & Engineering
- https://www.ciccialab.com/ - Genome Integrity and Genome Editing
- https://sizunjianglab.com - Investigate host-disease interaction
- https://hostmicrobe.org/ - Study the biological basis of diseases caused by microbes
- https://cheesemanlab.wi.mit.edu/ - World of cell division
- https://blainey.mit.edu/ - Pooled optical genetic screening in human cells
- https://marsonlab.org/ - Decoding and rewriting human immune cells with CRISPR
- Statistical Bioinformatics Lab