Novel Statistical Methods in Gene Expression Analysis, Functional Genomics, Genetics, and Biochemistry
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: 20 September 2025 | Viewed by 726
Special Issue Editor
Interests: genomics; biostatistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to invite you to contribute to a Special Issue of the International Journal of Molecular Sciences focusing on "Novel Statistical Methods in Gene Expression Analysis, Functional Genomics, Genetics, and Biochemistry".
The rapid advancements in high-throughput technologies have generated vast amounts of data, presenting both opportunities and challenges in various fields of molecular sciences. Innovative statistical methods are crucial for extracting meaningful insights from these complex datasets, thereby enhancing our understanding of gene expression, genetic variation, functional genomics, and biochemistry.
This Special Issue aims to highlight the cutting-edge statistical approaches that address these challenges and enhance our ability to interpret genomic data. We welcome original research articles, reviews, and methodological papers that cover, but are not limited to, the following topics:
- Advanced statistical models for gene expression analysis;
- Novel algorithms for detecting genetic associations;
- Methods for integrating multi-omics data;
- Techniques for identifying non-linear and complex relationships in genomic data;
- Applications of machine learning and artificial intelligence in genomics;
- Statistical approaches for functional annotation of genetic variants;
- Innovations in single-cell RNA sequencing data analysis;
- Tools for network-based analysis of gene interactions.
We encourage submissions that demonstrate the application of these methods to real-world datasets, providing insights into biological processes and disease mechanisms.
Submission Guidelines:
- Manuscripts should be prepared according to the Journal guidelines.
- All submissions will undergo a rigorous peer-review process.
Please submit your manuscript through the submission portal and select the Special Issue “Novel Statistical Methods in Gene Expression Analysis, Functional Genomics, Genetics, and Biochemistry”.
We look forward to your contributions and to advancing the field of genomics through innovative statistical methodologies.
Dr. Łukasz Huminiecki
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- multi-omics
- statistics
- gene expression analysis
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