ELI5: Explain Like I'm 5

Weighted correlation network analysis

Weighted correlation network analysis is like a game where you have a bunch of toys and you want to figure out which toys are friends with each other. Imagine you have a lot of toy cars, toy dolls, and toy animals. You know that sometimes toy cars like to play with other toy cars, dolls like to play with other dolls, and animals like to play with other animals.

So, to figure out which toys like to play with each other, you start by putting all the toys that are the same type in groups. Then, you look at each toy in each group and see if they are friends with other toys in the group. If they are friends, you give them a high score. If they are not friends, you give them a low score.

After you have looked at all the toys, you make a chart that shows which toys are friends with each other based on their scores. This chart is called a weighted correlation network. It helps you see which types of toys like to play with each other the most.

In real life, scientists can use weighted correlation network analysis to look at things like genes and proteins to see how they are connected to each other. By figuring out which genes and proteins are friends with each other, scientists can learn more about how our bodies work and how to treat diseases.