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Machine learning in genomics

This Nature Reviews Genetics collection brings together Reviews by key opinion leaders that explain cutting-edge machine learning methodology and how these tools are being applied in genomics. 

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    This Nature Milestone provides a perspective of major genomic sequencing-related developments in the 21st century — from the first human reference genome, through methodological breakthroughs, to the impact of sequencing on fields as diverse as microbiology, cancer and palaeogenetics.

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    This Nature Reviews Genetics collection brings together Reviews written by key opinion leaders on single-cell omics methods and applications.

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    The editors of Nature Reviews Genetics will be posting about the latest developments in research and policy, and providing news about the journal. If you have any questions or feedback for us, get in touch by email or on X.

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    • With SNP-based genome-wide association studies (GWAS) nearing signal saturation, exploring copy number variation (CNV) can offer new insights into the genetic architecture of complex traits. The authors review recent advances that enable large-scale CNV-based GWAS and their likely impact on downstream analyses, such as polygenic risk scoring and drug target identification.

      • Laura Harris
      • Ellen M. McDonagh
      • Tomas Fitzgerald
      Review Article
    • Global genomic data sharing enhances precision medicine. In this Roadmap, the authors outline evolving data-sharing models, best practices and policy impacts, and propose 12 actions to systematically scale up genomic data sharing.

      • Zornitza Stark
      • David Glazer
      • Richard H. Scott
      Roadmap
    • Ancestral recombination graphs (ARGs) are revolutionizing population genetics by elucidating genetic processes such as demography, migration and selection. This Review introduces ARG structure, compares estimation methods and illustrates their application to understanding population dynamics.

      • Rasmus Nielsen
      • Andrew H. Vaughn
      • Yun Deng
      Review Article
    • Metabologenomics integrates multi-omics data into genome-scale metabolic models (GEMs) to analyse complex metabolic networks. Mardinoglu and Palsson review advancements in GEMs at the global, cell- and tissue-specific, microbiome and whole-body levels, with insights into their applications towards improving health care.

      • Adil Mardinoglu
      • Bernhard Ø. Palsson
      Review Article
  • In this Journal Club article, Edroaldo Lummertz da Rocha discusses two papers that provided important insights into how tumour cells communicate with distant organs to establish pre-metastatic niches.

    • Edroaldo Lummertz da Rocha
    Journal Club
  • The adoption of microfluidics was fundamental to the development of cost-effective, high-throughput DNA sequencing. As the field progresses towards multi-omics, Lambert et al. reflect on the key concepts underlying microfluidics and how resulting engineering advances at the microscale drove the evolution of genomic sequencing.

    • Camille L. G. Lambert
    • Guido van Mierlo
    • Bart Deplancke
    Comment
  • In this Journal Club, Alejo Rodriguez-Fratelli discusses a paper by Spudich and Koshland Jr that characterized non-genetic cell individuality in bacteria, a concept with emerging relevance to cancer progression.

    • Alejo E. Rodriguez-Fraticelli
    Journal Club

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