by Ioannis Michalopoulos

Immunogenetic Studies in Patients With GAD-Positive Stiff-Person Syndrome Reveal Novel Lymphocytic Genes and KLK10-Gene Variants

Tsiortou, P., Alexopoulos, H., Kyriakidis, K., Kosmidis, M., Barba, C., Akrivou, S., Michalopoulos, I., Politis, P., and Dalakas, M.C. (2025). Immunogenetic Studies in Patients With GAD-Positive Stiff-Person Syndrome Reveal Novel Lymphocytic Genes and KLK10-Gene Variants. Neurol Neuroimmunol Neuroinflamm 12, e200373.

by Ioannis Michalopoulos

Special Issue “Advances in Computational Biology and Bioinformatics”

Guest Editors

Georgios Pavlopoulos
Research Director, Institute for Fundamental Biomedical Research
BSRC Alexander Fleming, Greece
Email: pavlopoulos@fleming.gr

Nikos Kyrpides
Microbiome Data Science Group Lead, DOE Joint Genome Institute
Lawrence Berkeley National Laboratory, United States of America
Email: nckyrpides@lbl.gov

Ιoannis Michalopoulos
Staff Research Scientist, Centre of Systems Biology
Biomedical Research Foundation of the Academy of Athens, Greece
Email: imichalop@bioacademy.gr

Fotis Baltoumas
Postdoctoral Researcher, Bioinformatics and Integrative Biology Lab
BSRC Alexander Fleming, Greece
Email: baltoumas@fleming.gr

Evangelos Karatzas
Research Fellow, ARISE
European Bioinformatics Institute, United Kingdom
Email: vangelis@ebi.ac.uk

The rapid advancements in computational biology and bioinformatics have revolutionized our understanding of biological systems, providing unprecedented insights into the complexities of life. This special issue, titled “Advances in Computational Biology and Bioinformatics,” aims to highlight the cutting-edge research and innovative methodologies propelling the field forward varying from the development of sophisticated algorithms for data analysis to the integration of multi-omics approaches, computational biology and bioinformatics. These advances not only enhance our ability to decode the vast amounts of data generated by modern experimental techniques but also pave the way for new discoveries in genomics, proteomics, systems biology, and personalized medicine. By showcasing the latest breakthroughs and emerging trends, this issue seeks to underscore the pivotal role of computational approaches in addressing some of the most pressing challenges in biology and medicine today.

Scope of the Special Issue:

The main scope of the special issue on “Advances in Computational Biology and Bioinformatics” encompasses a wide array of topics that reflect the dynamic and interdisciplinary nature of the field. This issue aims to cover (but not limited) the following key areas:

  • Algorithm Development and Data Analysis: Papers in this section will focus on novel algorithms, computational models, and analytical tools designed to process and interpret biological data. This includes advancements in machine learning, artificial intelligence, and statistical methods that enhance the accuracy and efficiency of data analysis.
  • Genomics and Transcriptomics: Contributions will explore computational techniques applied to genomic and transcriptomic data. This includes genome assembly, annotation, variant analysis, and the interpretation of gene expression patterns, as well as the integration of genomic data with other biological datasets.
  • Proteomics and Metabolomics: This area will highlight computational approaches in the study of proteins and metabolites. Topics may include protein structure prediction, protein-protein interactions, metabolite profiling, and the integration of proteomic and metabolomic data for comprehensive biological insights.
  • Systems Biology: Papers will delve into the modelling and simulation of complex biological systems. This includes network biology, dynamic systems modelling, and the use of computational tools to understand cellular pathways, interactions, and regulatory mechanisms.
  • Structural Biology and Molecular Dynamics: This section will cover computational methods in structural biology, including molecular dynamics simulations, docking studies, and the prediction of biomolecular structures and functions.
  • Bioinformatics in Personalized Medicine: Contributions will explore how computational biology is advancing personalized medicine. Topics may include the analysis of patient-specific data, biomarker discovery, drug repositioning, and the development of tailored therapeutic strategies.
  • Big Data and High-Performance Computing: Papers will focus on the challenges and solutions related to handling and analyzing large-scale biological data. This includes the use of high-performance computing, cloud-based platforms, and data storage solutions to manage the vast amounts of data generated in modern biological research.
  • Emerging Trends and Future Directions: This section will provide insights into the latest trends and future directions in computational biology and bioinformatics. Topics may include emerging technologies, interdisciplinary approaches, and the potential impact of these advancements on various fields of biology and medicine.

By addressing these diverse yet interconnected areas, this special issue aims to provide a comprehensive overview of the current state of computational biology and bioinformatics, highlighting the theoretical advancements and practical applications driving the field forward.

All manuscripts will receive expedited handling and the accepted version will appear online within one week. Please note that every accepted paper is subjected to a processing fee as per Elsevier’s open access journal policies.

If you have any further questions, please feel free to contact us at
publications.assistant@csbj-rncsb.org

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