Call for papers - Long-read sequencing technologies for medical diagnostics

Guest Editor

Laia Bassaganyas, PhD, Institut de Genómique Fonctionnelle (IGF), France

Submission Status: Open | Submission Deadline: 28 March 2025

BMC Medical Genomics is calling for submissions to our Collection on Long-read sequencing technologies for medical diagnostics.

This Collection seeks to gather cutting-edge research on the application of long-read sequencing technologies in medical genomics and diagnostic sequencing. We invite submissions that explore the utility of single-molecule sequencing, nanopore sequencing, and other third-generation sequencing approaches in elucidating complex genomic features, identifying disease-associated variants, and advancing precision medicine.

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Meet the Guest Editor

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Laia Bassaganyas, PhD, Institut de Genómique Fonctionnelle (IGF), Montpellier France

Dr Laia Bassaganyas is a CNRS tenure researcher at the Signaling, Plasticity, and Cancer group at the Institut de Genómique Fonctionnelle in Montpellier. Her research interests include the analysis of genomic and transcriptomic sequencing data (bulk and single-cell) to gain new insights into fundamental aspects of cancer disease, the development of user-friendly computational tools for the analysis of sequencing data, and the adaptation of sequencing technology, especially nanopore-based sequencing from Oxford Nanopore, for clinical use.

About the Collection

BMC Medical Genomics is calling for submissions to our Collection on Long-read sequencing technologies for medical diagnostics.

Long-read sequencing technologies have revolutionized medical genomics by enabling the comprehensive analysis of complex genomic regions, especially structural variations and repetitive sequences. These technologies, including single-molecule sequencing and nanopore sequencing, have enabled a greater understanding of genetic diseases, cancer genomics, and infectious diseases, as well as advanced progress in personalized medicine and clinical diagnostics. Applications of long-read sequencing helped uncover novel disease-associated genetic variants, elucidate complex genomic rearrangements, and improve the accuracy of genetic diagnostics. It is important to continue advancing our collective understanding of long-read sequencing technologies in medical diagnostics to harness their full potential for precision medicine and clinical applications. Recent advances have demonstrated the utility of long-read sequencing in resolving complex genomic structures, identifying disease-causing genetic mutations, and improving the diagnostic yield in challenging clinical cases.

This collection seeks to gather cutting-edge research on the application of long-read sequencing technologies in medical genomics and diagnostic sequencing. We invite submissions that explore the utility of single-molecule sequencing, nanopore sequencing, and other third-generation sequencing approaches in elucidating complex genomic features, identifying disease-associated variants, and advancing precision medicine.

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Long-read sequencing technologies for medical diagnostics" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.