Omics Technologies in Molecular Biology
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 181
Special Issue Editor
2. Facultad de Ciencias Agrarias, Departamento de Ciencias Forestales, Universidad Nacional de Colombia—Sede Medellín, Medellín 050034, Colombia
Interests: plant genomics; plant breeding; genetics of adaptation; population genomics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The current Special Issue entitled “Omics Technologies in Molecular Biology”, compiled by the International Journal of Molecular Sciences, focuses on the advancements and integration of omics technologies, key high-throughput tools that allow for comprehensive analysis of biological systems at various molecular and phenotypic levels. The Special Issue will cover genomics, transcriptomics, proteomics, metabolomics, lipidomics, phenomics, enviromics, and their intersection through big data analytics and machine learning. By harnessing these last-generation technologies, researchers will be able to uncover new insights into complex biological processes, systems biology, and disease mechanisms. Ultimately, the Special Issue will provide a platform for interdisciplinary collaboration, aiming to advance the frontiers of molecular biology by merging cutting-edge omics technologies with computational innovations. By merging interdisciplinary studies at the frontier of omics tools, the Special Issue’s main goal is to fill the following research gaps:
- Data Integration and Interpretation: A major current challenge in the omics field is how to effectively integrate diverse datasets (e.g., all the way from genomics to phenomics and enviromics passing by metabolomics and proteomics) to provide a more meaningful understanding of the underlying mechanisms in play.
- Scalability and Accuracy: Omics data can be vast and complex, requiring innovative and advanced algorithms for reliably processing and interpreting these "big data" resources.
- Machine Learning Applications: Although the promises of machine learning for data integration in the omics paradigm have been widely discussed, significant advancements remain in developing models that can accurately predict biological phenomena or therapeutic outcomes based on multi-omics data.
- Enviromics in Systems Biology: There is a major need to bridge the gap between molecular biology and environmental factors (enviromics), which are often overlooked despite their significant impact on molecular processes. Original research articles and reviews across a wide spectrum of study organisms are welcome, specifically within the following sub-disciplines:
- Genomics and Transcriptomics: Works that study genomic variation, gene sequences, and their expression patterns.
- Proteomics and Metabolomics: Research that analyzes protein structures, functions, and cellular metabolites to better understand physiological effects.
- Lipidomics and Phenomics: Manuscripts that investigate lipid profiles and phenotypic variations in relation to complex traits and diseases.
- Enviromics: Initiatives that explore how environmental factors interact with molecular systems, providing a comprehensive view of biological adaptation.
- Big Data and Machine Learning: Integrative proposals to design and apply advanced computational methods capable of handling and interpreting large-scale biological data and predictive models across multi-dimensional datasets from various omics technologies.
By merging multi-omics data with machine learning tools across a diverse array of biological systems, the Special Issue will enable breakthroughs in phenotype forecasting, genotype-targeted management, and disease diagnostics. Specifically, the simultaneous deployment of multiple omics datasets is likely to uncover novel biomarkers that can be used for trait prediction and early disease detection and monitoring. The collaboration of multiple omics disciplines across study systems is lacking, yet it will enable the development of more holistic biological and computational models, offering a better understanding of complex biological networks.
Dr. Andrés J. Cortés
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.
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Keywords
- omics technologies
- genomics
- transcriptomics
- proteomics
- metabolomics
- lipidomics
- phenomics
- enviromics
- big data
- machine learning
- molecular biology
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