# The next frontier for genomic prediction is computational

## TL;DR

This paper discusses the growing importance of computational methods in genomic prediction and invites new research and debate on the topic.

## Contribution

The paper highlights the need for new computational approaches to improve genomic prediction.

## Key findings

- Genomic prediction is becoming more dynamic with new technologies.
- Computational models face challenges in integrating different data types.
- The paper invites submissions to advance the field through discussion and research.

## Abstract

From the seminal paper by Meeuwissen et al. 2001 to the GSA Journals Series launch in 2015, the field of Genomic Prediction continues to gain momentum. The field is increasingly dynamic, with new technology increasing the scale and scope of the data available. Significant challenges exist in building computational models. Questions of how to appropriately account for different types of data, and which data improve predictions are interwoven. What is the best path forward? What methods will improve predictions? Authors can submit their rejoinder or start a new discussion on one of the many important topics in the field by submitting a Dialogue and Debate article for peer review at G3.