Integrating Biological Heuristics and Gene Expression Data for Gene Regulatory Network Inference

What is it about?

This article proposes a new metric to measure co-regulation between genes rather than measuring correlation. It employs definitions of up-regulation, down-regulation and dual actions to measure various relationships and to detect subtle relationships between genes. The proposed function also visualizes the relationship in a meaningful way. In addition, it embeds heuristics ( known facts about biological networks) to guide the search process when constructing a GRN. It uses a concept called hub networks to build the core structure of the network first. It also uses small-world properties to grow the network.

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Photo by Alina Grubnyak on Unsplash

Photo by Alina Grubnyak on Unsplash

Why is it important?

The first article to embed known facts about biological networks into statistics and machine learning algorithms. This is the first time that hub networks are used to construct a GRN.