Advances in Bioinformatics and Computational Biology of Human Disease

Dr. Ioannis Michalopoulos and Dr. Georgios A. Pavlopoulos are editors to “Advances in Bioinformatics and Computational Biology of Human Disease” topic

Abstract submission deadline
31 October 2023

Manuscript submission deadline
31 December 2023

In today’s big-data era, the exponential growth of information due to the latest advancements in high-throughput technologies is indisputable. Therefore, efficient algorithms and tools for the extraction, analysis, exploration, and representation of biological information are necessary. In this regard, we invite investigators to contribute original bioinformatics research and review articles describing novel methods, algorithms, software applications, web services, and workflows that are able to cope with larger datasets, complexity, and new datasets or databases which integrate information from different sources. Submissions across the entire spectrum of life and biomedical sciences are welcomed.


  • genomics
  • sequence analysis
  • gene expression
  • structural bioinformatics
  • gene regulation
  • proteomics
  • metabolomics
  • biological networks
  • data visualization
  • data integration
  • AI/ML
  • personalized medicine
  • meta-analysis
  • cancer research
  • disease research

Participating Journals

Journal NameImpact FactorCiteScoreLaunched YearFirst Decision (median)APC
Biology4.24.0201218.8 Days2700 CHF
BioTech4.4201216.5 Days1400 CHF
Cells6.09.0201218.8 Days2700 CHF
Genes3.55.1201017.9 Days2600 CHF
Metabolites4.15.3201112.9 Days2700 CHF

Special Issue “Differential Gene Expression and Coexpression”

Dr Ioannis Michalopoulos and Dr Apostolos Malatras are Guest Editors of Special Issue “Differential Gene Expression and Coexpression” of Biology (Impact Factor 5.168, JCR category rank: Q1: Biology). Deadline for manuscript submissions: 31 December 2022.

The most common approach in transcriptomics (RNA-seq and microarrays) is differential gene expression analysis. Genes identified as differentially expressed may be responsible for phenotype differences between various biological conditions. An alternative approach is gene co-expression analysis, which detects groups of genes with similar expression patterns across unrelated sets of transcriptomic data of the same organism. Co-expressed genes tend to be involved in similar biological processes. This Special Issue will include reviews and research articles on the topic differential gene expression and coexpression. The reviews will provide an overview of the methods available for transcriptomic analysis, while the research articles will provide an in-depth description of each state-of-the-art tool. Please send me an abstract prior to submission to make sure that your work falls within the scope of this Special Issue.