Artificial intelligence in genomics

Submission status
Submission deadline

Artificial intelligence (AI) has emerged as a powerful platform to streamline the analysis of complex genomic datasets and help researchers explore the genetic basis of important diseases or phenotypes. In a new Call for Papers, Communications Biology, Nature Communications and Scientific Reports are interested in submissions that highlight the possibilities offered by AI approaches to improve genomics research, regardless of the model system.

Original research Articles can report novel methods that involve AI-based algorithms or focus on specific applications of machine or deep learning to identify or prioritise genes and variants associated with a particular trait. Communications Biology and Nature Communications will also consider Reviews, Perspectives, and Comments that are relevant to these topics, though all submissions will be subject to the same peer review process and editorial standards as regular manuscripts considered at the respective journals.

To submit, see the participating journals
Glowing blue DNA molecule in the palm of a hand, representing the concept of DNA and genetic research


  • Kaoru Ito, PhD

    RIKEN Center for Integrative Medical Sciences, Japan

Communications Biology is edited by both in-house professional editors and Editorial Board Members.

Nature Communications is edited by in-house professional editors.

Scientific Reports is managed by in-house professional editors and edited by Editorial Board Members.

Our editors work closely together to ensure the quality of our published papers and consistency in author experience.


Guest Editors for Communications BIology


Melanie Bahlo, PhD, Walter and Eliza Hall Institute of Medical Research, Australia - Guest Editor from July 2023 to April 2024.

Melanie Bahlo leads a statistical genetics/bioinformatics laboratory at the Walter and Eliza Hall Institute of Medical Research, in Melbourne, Australia. Dr Bahlo’s lab is dedicated to identifying and understanding genetic risk factors of disease. Her lab also develops methods and performs bespoke analyses of large multi-omics datasets and is increasingly employing AI to extract deeper phenotyping.



Kaoru Ito, PhD, RIKEN Center for Integrative Medical Sciences, Japan

Kaoru Ito received his Ph.D from Chiba University in Japan. As a Postdoctoral Fellow at the Department of Genetics, Harvard Medical School, Dr Ito worked on genomics and bioinformatics research. From 2016 to present, Dr Ito has been engaged as a Team Leader at the RIKEN Center for Integrative Medical Sciences in Japan.