Graphs are an excellent way of showing high-dimensional data in an intuitive way. But when it comes to representing graphs as matrices, it can be a little less intuitive. Earlier, we looked at how to represent an undirected graph as an adjacency matrix. In this tutorial, we'll be looking at ... READ *the* POST

## When to use LASSO regression

LASSO regression is a great tool to have in your data science arsenal if you're working with big data. It's computationally efficient and performs variable selection and regression simultaneously. How powerful is that?! In this article, we'll talk about when you want to use this powerful tool for ... READ *the* POST

## Node customization for stunning networks

As we saw earlier, network visualization in R is a breeze with the visNetwork package. The graphs are gorgeous, interactive, and fun to play with. In this article, we'll look at how we can customize the nodes of our network to convey additional information. First, we'll learn how to color a network ... READ *the* POST

## How to delete your saved workspace in R

When you exit RStudio, you'll see a pop-up asking, “Save workspace image to ~/.RData?” If you’re unsure, you’ll probably select Save. After all, it is the default. Plus, saving is good. Right?
Well…it depends. The next time you load RStudio, everything in your workspace (global environment) ... READ *the* POST

## Giving your networks a user-friendly makeover

When it comes to network analysis, igraph is a beast of a package with extensive documentation. If you do network analysis in R, chances are you've at least heard of it. With igraph, you can create and compare deterministic or stochastic networks, calculate centrality measures, and find communities ... READ *the* POST

## 5 books about Bayesian networks for biologists

From gene regulatory networks to agricultural pest control, there are numerous applications of Bayesian networks in biology. If you’re a biologist, or even a computer scientist, this list will help you begin your journey towards understanding Bayesian networks and their use in biology.
1. ... READ *the* POST