Pervasive Biomedical Informatics (PBI) represents a transformative approach to the collection, integration, analysis, and translation of biomedical data across diverse environments. The convergence of bioinformatics, systems biology, and pervasive computing is reshaping this field, emphasizing seamless integration and real-time analytics. As healthcare and life sciences embrace advancements in mobile health (mHealth), wearable sensors, ambient intelligence, the Internet of Things (IoT), and cloud computing, biomedical informatics continues to evolve from isolated systems to comprehensive, omnipresent solutions that monitor, support, and enhance health and well-being.
Building on this vision, PBI seeks to make bioinformatics research, development, and applications accessible and deployable for everyone, regardless of setting. We aim to explore how bioinformatics and systems biology can harness technological advancements like Edge Computing, Large Language Models (LLMs), next-generation communication technologies (including LPWANs, 5G, and 6G) to enable comprehensive, real-time biomedical data analysis and decision-making at the edge of networks, while ensuring efficiency and privacy. Specifically, this research topic targets the integration of biological data with systemic insights to facilitate holistic health outcomes.
This Research Topic aims to showcase interdisciplinary research and innovative solutions at the nexus of pervasive computing, bioinformatics, and systems biology. To gather further insights in this expansive realm and its limitations, we welcome articles addressing, but not limited to, the following themes:
o Integration of bioinformatics with heterogeneous biosensors and smart devices
o Real-time data processing algorithms utilizing Edge computing for bioinformatics applications
o Interoperability across distributed biomedical systems, including resource-limited environments
o User-centered design in pervasive bioinformatics and systems biology platforms
o Standards for pervasive, edge-aware biomedical data management
o Predictive modeling in systems biology using ubiquitous computing environments
o Contextual analysis of biological pathways enabled by pervasive monitoring technologies
o Translational applications of bioinformatics in chronic disease management, preventive care, and diagnostics
o Multi-omics data integration for personalized healthcare through pervasive informatics
We invite original research articles, methods papers, reviews, and case studies that address the multifaceted challenges within pervasive biomedical informatics. By bringing together voices from computer science, bioinformatics, systems biology, and healthcare, this topic aims to advance the field and foster integrative solutions for the next generation of health informatics.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy Brief
Review
Systematic Review
Technology and Code
Keywords: Pervasive Computing, Biomedical Informatics, Bioinformatics, Systems Biology, Real-time Analytics, Edge Computing, mHealth, Wearable Sensors, Data Integration, Personalized Healthcare
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
