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Current Genomics

ISSN: 1389-2029 (Print)
eISSN: 1875-5488 (Online)

Current Genomics is a peer-reviewed journal that provides essential reading about the latest and most important developments in genome science and related fields of research. Systems biology, systems modeling, machine learning, network inference, bioinformatics, computational biology, epigenetics, single cell genomics, extracellular vesicles, quantitative biology, and synthetic biology for the study of evolution, development, maintenance, aging and that of human health, human diseases, clinical genomics and precision medicine are topics of particular interest. The journal covers plant genomics. The journal will not consider articles dealing with breeding and livestock. Current Genomics publishes three types of articles including: i) Research papers from internationally-recognized experts reporting on new and original data generated at the genome scale level. Position papers dealing with new or challenging methodological approaches, whether experimental or mathematical, are greatly welcome in this section. ii) Authoritative and comprehensive full-length or mini reviews from widely recognized experts, covering the latest developments in genome science and related fields of research such as systems biology, statistics and machine learning, quantitative biology, and precision medicine. Proposals for mini-hot topics (2-3 review papers) and full hot topics (6-8 review papers) guest edited by internationally-recognized experts are welcome in this section. Hot topic proposals should not contain original data and they should contain articles originating from at least 2 different countries. iii) Opinion papers from internationally recognized experts addressing contemporary questions and issues in the field of genome science and systems biology and basic and clinical research practices.

Special Issues With Active Call for Papers

Submission closes on: Dec 31, 2024
Genomic Insights into Oncology: Harnessing Machine Learning for Breakthroughs in Cancer Genomics.

This special issue aims to explore the cutting-edge intersection of genomics and oncology, with a strong emphasis on original data and experimental validation. While maintaining the focus on how machine learning and advanced data analysis techniques are revolutionizing our understanding and treatment of cancer, this issue will prioritize contributions that go beyond mere data-mining. We seek to include comprehensive review articles that synthesize recent advancements and research papers that present novel data, demonstrating clear experimental... see more

Submission closes on: Dec 31, 2024
Pathogen genomics & human health

Pathogens establish successful infection need to escape host immune surveillance. Alteration and mutation of genomics in pathogens confer advantages to subvert the host immune barrier. In this issue, we will collect and discuss current understanding in the field of “pathogen genomics and human disease”. see more

Submission closes on: Dec 04, 2024
Integrating Artificial Intelligence and Omics Approaches in Complex Diseases

Recent advancements in AI and omics methodologies have revolutionized the landscape of biomedical research, enabling us to extract valuable information from vast amounts of complex data. By combining AI algorithms with omics technologies such as genomics, proteomics, metabolomics, and transcriptomics, researchers can obtain a more comprehensive and multi-dimensional analysis of biological systems, ultimately leading to a better understanding of disease mechanisms. Complex diseases, characterized by their heterogeneous nature, pose unique challenges to researchers and clinicians... see more

Submission closes on: Oct 31, 2024
Advanced AI Techniques in Big Genomic Data Analysis

The thematic issue on "Advanced AI Techniques in Big Genomic Data Analysis" aims to explore the cutting-edge methodologies and applications of artificial intelligence (AI) in the realm of genomic research, where vast amounts of data pose both challenges and opportunities. This issue will cover a broad spectrum of AI-driven strategies, including machine learning and deep learning models, tailored for extracting, analyzing, and interpreting complex patterns within large-scale genomic datasets. Contributions to this issue will highlight... see more

Submission closes on: Sep 26, 2024
Deep learning in Single Cell Analysis

The field of biology is undergoing a revolution in our ability to study individual cells at the molecular level, and to integrate data from multiple sources and modalities. This has been made possible by advances in technologies for single-cell sequencing, multi-omics profiling, spatial transcriptomics, and high-throughput imaging, as well as the development of powerful machine learning and deep learning algorithms. In particular, the ability to analyze spatially resolved single-cell data has opened new avenues for... see more

Submission closes on: Aug 31, 2024
Microbial Destruction of Resistant Pollutants: Adaptive Reactions, Genetic Determinants and Characteristics of Enzyme Systems

Microbial technologies for environmental removal of persistent pollutants are effective and low-cost. Microorganisms catalyze a huge variety of metabolic pathways for the destruction of toxicants, which allows them to adapt to almost any type of organic pollutant and use it as a substrate/cosubstrate. Modern research methods, such as NGS, transcriptomic analysis, and whole-genome sequencing, make it possible to study in detail the capabilities of a particular organism. However, without studying the properties of isolated enzymes,... see more

Submission closes on: Aug 03, 2024
Applications of Single-cell Sequencing Technology in Reproductive Medicine

Single cell sequencing (SCS) technology utilizes individual cells' genetic material to sequence their genome, transcriptome, and epigenetics at the molecular level. It offers insights into cell heterogeneity and enables the study of limited biological materials. Since its recognition as a valuable technique in 2011, single cell sequencing has yielded numerous research findings. Recent advancements have rapidly expanded its applications, particularly in studying reproductive cells and embryonic stem cells with small sample sizes. These developments have... see more

Submission closes on: Jul 30, 2024
Advanced Computational Algorithms and Artificial Intelligence in Clinical Pharmacogenomics

In the era of personalized medicine, understanding the relationship between genetics and drug response is crucial. This issue delves into innovative methodologies, leveraging deep computational analysis and artificial intelligence, to enhance the field of Clinical Pharmacogenomics. The interdisciplinary approach harnesses the power of advanced high-throughput genotyping technologies, sophisticated computational analysis, and machine learning algorithms to unravel the complexities of genotype-phenotype correlations. By scrutinizing vast genomic datasets with precision and speed, researchers can now identify genetic... see more

Submission closes on: Jun 30, 2024
New insights on Pediatric Tumors and Associated Cancer Predisposition Syndromes

Because of the broad spectrum of children cancer susceptibility, the diagnosis of cancer risk syndromes in children is rarely used in direct cancer treatment. The field of pediatric cancer genetics and genomics will only continue to expand as a result of increasing use of genetic testing tools. It's possible that people who have a children cancer predisposition syndrome might not be assessed in time to diagnose and prevent cancer in themselves or their family members... see more

Submission closes on: Not Found
Current Genomics in Cardiovascular Research

Cardiovascular diseases are the main cause of death in the world, in recent years we have had important advances in the interaction between cardiovascular disease and genomics. In this Research Topic, we intend for researchers to present their results with a focus on basic, translational and clinical investigations associated with genomics and cardiovascular disease. Experimental studies, network meta-analysis, randomized controlled trials, systematic reviews and meta-analysis, umbrella reviews, meta-epidemiologic studies, cross-sectional studies, diagnosis, treatment, management, prevention... see more