# Augmenting Circadian Biology Research With Data Science

## TL;DR

This paper explores how data science can enhance circadian biology research by integrating big data and computational tools.

## Contribution

The paper introduces new ways to apply data science in circadian biology, emphasizing interdisciplinary collaboration.

## Key findings

- Big data and computational models are transforming traditional biological research methods.
- Collaboration between biologists and data scientists can uncover new insights into circadian rhythms.
- Data science tools can provide real-world insights into biological rhythms when applied with biological understanding.

## Abstract

The nature of biological research is changing, driven by the emergence of big data, and new computational models to parse out the information therein. Traditional methods remain the core of biological research but are increasingly either augmented or sometimes replaced by emerging data science tools. This presents a profound opportunity for those circadian researchers interested in incorporating big data and related analyses into their plans. Here, we discuss the emergence of novel sources of big data that could be used to gain real-world insights into circadian biology. We further discuss technical considerations for the biologist interested in including data science approaches in their research. We conversely discuss the biological considerations for data scientists so that they can more easily identify the nuggets of biological rhythms insight that might too easily be lost through application of standard data science approaches done without an appreciation of the way biological rhythms shape the variance of complex data objects. Our hope is that this review will make bridging disciplines in both directions (biology to computational and vice versa) easier. There has never been such rapid growth of cheap, accessible, real-world research opportunities in biology as now; collaborations between biological experts and skilled data scientists have the potential to mine out new insights with transformative impact.