About this Research Topic

Background

Gene regulation is the intricate and highly dynamic process of inducing or inhibiting the expression of individual genes in an organism’s genome. It is orchestrated by a vast array of molecules, including transcription factors and cofactors, chromatin regulators, as well as other epigenetic mechanisms, which allow an organism to control cell growth and differentiation during development, as well as to respond to a variety of environmental stimuli. In turn, disruptions in gene regulation, e.g., those caused by mutations in regulatory sequences, have been shown to represent a defining feature of a plethora of diseases, including developmental and neurological disorders as well as cancer.

Given its importance in proper cell functioning and adaptability, decoding the architecture of gene regulation has become one of the most pressing tasks in modern (computational) biology. To this end, it has been a long-held ambition to enable quantitative prediction of gene regulation, i.e., inference of gene expression levels, from genomic and epigenomic features alone. The rise in computing power, recent advances in learning algorithms alongside high-throughput, next-generation sequencing that provide large-scale quantification of gene expression at single-cell resolution, as well as the identification of novel genes and noncoding RNAs at unprecedented levels, may bring us one step closer to the realization of this dream.

Early attempts in the application of modern approaches in machine learning - in particular deep learning - to predict mRNA abundance levels directly from DNA sequence have already yielded promising results. Despite this, it remains an open question how individual factors and epigenomic features involved in the gene regulatory apparatus interact within the vast genomic landscape of an organism’s non-coding regions and, in turn, contribute to mRNA expression levels. In order to advance our understanding of gene expression inference, we need scalable algorithms that: i) allow for the integration of a variety of diverse genomic and epigenomic datasets as well as structural and/or biological priors; ii) are interpretable with respect to the representations they have learned; and, iii) allow for a transfer of the learned representations to novel and different environments and contexts.

This Research Topic welcomes both original studies and review articles assessing modern machine learning approaches that integrate genomic and/or epigenomic datasets to quantitatively predict gene regulation. The topics of interest include, but are not limited to, the following:

- Quantitative inference of gene expression levels from DNA sequence and/or epigenomic features;
- Analyses of transcription factor interaction within multiple binding elements and/or effects of single nucleotide polymorphisms, copy number variations, etc., in causing loss or creation of promoter binding elements and
enhancers;
- Strategies for heterogeneous data integration of genomic sequences and epigenetic datasets, including chromatin accessibility, methylation, or chromatin conformation-related data;
- Evaluation and/or benchmarking of different (un-) supervised learning paradigms, including Bayesian (deep) learning, deep convolutional models, graph neural networks, or attention-based approaches;
- Approaches to structural learning of efficient model architectures based on biological, structural priors, or data-driven methods, such as Neural Architectural Search or Bayesian sampling;
- Analyses of model scalability versus model complexity trade-offs with respect to structural priors, inductive biases, dimensionality reduction, randomized or sampling-based techniques;
- Investigations into model interpretability e.g., visualization of individual components of trained models, such as model filters representing sequence binding motifs;
- Studies into the possibilities/limitations of the transfer of trained models to novel/different contexts and environments.

Keywords: machine learning, plant genome, plant genes, gene regulation, epigenomics, deep learning

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Frequently asked questions

• What is a Research Topic?

  Frontiers' Research Topics are collaborative hubs built around an emerging theme.Defined, managed, and led by renowned researchers, they bring communities together around a shared area of interest to stimulate collaboration and innovation.

  Unlike section journals, which serve established specialty communities, Research Topics are pioneer hubs, responding to the evolving scientific landscape and catering to new communities.

• Why does Frontiers publish Research Topics? 

  The goal of Frontiers' publishing program is to empower research communities to actively steer the course of scientific publishing. Our program was implemented as a three-part unit with fixed field journals, flexible specialty sections, and dynamically emerging Research Topics, connecting communities of different sizes and maturity.

  Research Topics originate from the scientific community. Many of our Research Topics are suggested by existing editorial board members who have identified critical challenges or areas of interest in their field.

• Why are Research Topics important for journals?

  As an editor, Research Topics will help you build your journal, as well as your community, around emerging, cutting-edge research. As research trailblazers, Research Topics attract high-quality submissions from leading experts all over the world.

  A thriving Research Topic can potentially evolve into a new specialty section if there is sustained interest and a growing community around it.

• How do we ensure the quality of articles within Research Topics?

  Each Research Topic must be approved by the specialty chief editor, and it falls under the editorial oversight of our editorial boards, supported by our in-house research integrity team. The same standards and rigorous peer review processes apply to articles published as part of a Research Topic as for any other article we publish.

  In 2023, 80% of the Research Topics we published were edited or co-edited by our editorial board members, who are already familiar with their journal's scope, ethos, and publishing model. All other topics are guest edited by leaders in their field, each vetted and formally approved by the specialty chief editor.

• What are the benefits of publishing my article in a Research Topic?

  Publishing your article within a Research Topic with other related articles increases its discoverability and visibility, which can lead to more views, downloads, and citations. Research Topics grow dynamically as more published articles are added, causing frequent revisiting, and further visibility.

  As Research Topics are multidisciplinary, they are cross-listed in several fields and section journals – increasing your reach even more and giving you the chance to expand your network and collaborate with researchers in different fields, all focusing on expanding knowledge around the same important topic.

  Our larger Research Topics are also converted into ebooks and receive social media promotion from our digital marketing team.

   
• What types of articles can be published in a Research Topic?

  Frontiers offers multiple article types, but it will depend on the field and section journals in which the Research Topic will be featured. The available article types for a Research Topic will appear in the drop-down menu during the submission process.

  Check available article types here 

• Can I suggest a new Research Topic? 

  Yes, we would love to hear your ideas for a topic. Most of our Research Topics are community-led and suggested by researchers in the field. Our in-house editorial team will contact you to talk about your idea and whether you’d like to edit the topic. If you’re an early-stage researcher, we will offer you the opportunity to coordinate your topic, with the support of a senior researcher as the topic editor. 

  Suggest your topic here 

• Who leads a Research Topic? 

  A team of guest editors (called topic editors) lead their Research Topic. This editorial team oversees the entire process, from the initial topic proposal to calls for participation, the peer review, and final publications.

  The team may also include topic coordinators, who help the topic editors send calls for participation, liaise with topic editors on abstracts, and support contributing authors. In some cases, they can also be assigned as reviewers.

• What is the role of a topic editor?

  As a topic editor (TE), you will take the lead on all editorial decisions for the Research Topic, starting with defining its scope. This allows you to curate research around a topic that interests you, bring together different perspectives from leading researchers across different fields and shape the future of your field. 

   

  You will choose your team of co-editors, curate a list of potential authors, send calls for participation and oversee the peer review process, accepting or recommending rejection for each manuscript submitted.

• What support will I receive when editing a new Research Topic? 

  As a topic editor, you're supported at every stage by our in-house team. You will be assigned a single point of contact to help you on both editorial and technical matters. Your topic is managed through our user-friendly online platform, and the peer review process is supported by our industry-first AI review assistant (AIRA).

• As a junior researcher, can I be involved in editing a Research Topic? 

  If you’re an early-stage researcher, we will offer you the opportunity to coordinate your topic, with the support of a senior researcher as the topic editor. This provides you with valuable editorial experience, improving your ability to critically evaluate research articles and enhancing your understanding of the quality standards and requirements for scientific publishing, as well as the opportunity to discover new research in your field, and expand your professional network.

• Can I get a certificate for editing a Research Topic?

  Yes, certificates can be issued on request. We are happy to provide a certificate for your contribution to editing a successful Research Topic.

• Who will I collaborate with?

  Research Topics thrive on collaboration and their multi-disciplinary approach around emerging, cutting-edge themes, attract leading researchers from all over the world.

• How long does it take to publish a Research Topic?

  As a topic editor, you can set the timeline for your Research Topic, and we will work with you at your pace. Typically, Research Topics are online and open for submissions within a few weeks and remain open for participation for 6 – 12 months. Individual articles within a Research Topic are published as soon as they are ready.

  Find out more about our Research Topics

• What fee support is available to authors publishing in a Research Topic?

  Our fee support program ensures that all articles that pass peer review, including those published in Research Topics, can benefit from open access – regardless of the author's field or funding situation.

  Authors and institutions with insufficient funding can apply for a discount on their publishing fees. A fee support application form is available on our website.

• Will there be a printed version of my Research Topic?

  In line with our mission to promote healthy lives on a healthy planet, we do not provide printed materials. All our articles and ebooks are available under a CC-BY license, so you can share and print copies.