Resources

Below is a collection of software and books that have greatly influenced the way I work and think. I primarily keep this updated for myself and for any new graduate student starting their journey into the life sciences.

For the books that are freely available to the public, I have included those direct links. Many of these books are available via academic subscriptions and some of the programming books are available via membership to ACM. Manning, No Starch Press, and O’Reilly often post book bundles on Humble Bundle that are DRM-free.

Software #

• Joplin, fantastic note-taking app with inline code support; end-to-end encryption; and synchronization via a cloud provider or local server.
• Rstudio / Posit, best IDE for R with support for python.
• VScode, general all-around code editor.
• Zotero, open-source PDF and reference manager.

Books #

Data Analytics #

• Feature Engineering and Selection: A Practical Approach for Predictive Models (free)
• Introduction to Statistical Learning (free)
• Statistical Rethinking, Bayesian data analysis
• Statistics with R: Bayesian Statistics (free)
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction (free)

R Language #

• Advance R (free)
• R for Data Science (free)
• Tidy Modeling with R (free)

Neuroscience #

• Advanced Data Analysis in Neuroscience: Integrating Statistical and Computational Models

Programming #

Databases #

• Designing Data-Intensive Applications
• SQL Indexing and Tuning e-Book (free)

Devops #

• Ansible: Up and Running
• Container Security, complementary copy available from Aqua
• Docker: Up and Running
• Kubernetes: Up and Running, complementary copy available from VMware Tanzu
• Terraform: Up and Running

Python #

• Architecture Patterns with Python (free)