Gut microbiome dysbiosis has been reported to have a role in many chronic and metabolic diseases like inflammatory bowel disease (IBD), and diabetes. Several reports show lung and skin microbiome play a significant role in health. Prebiotics and post-biotics have been reported to have therapeutic roles in inflammatory and metabolic diseases. Bioinformatics analysis is the key to metagenomics, meta-transcriptomics, and microbial metabolites analysis. Bioinformatics pipelines allow the identification of specific microbe signatures, the role of microbial communities, or their metabolites' prognostic biomarkers that can be targeted for therapy. The 24th edition of the flagship International Conference on Bioinformatics (InCoB2025) is focused on the theme "Bioinformatics-Driven Therapeutics Innovations: Microbiome and Beyond." This theme emphasizes the pivotal role of bioinformatics in advancing therapeutic innovations, particularly exploring how the microbiome, host-microbe interactions, and their dynamics help us to understand life in a holistic manner. This may help us to develop novel therapeutics for effective treatments of a variety of diseases.
Human microbiome varies in body parts in the same individual and also from geographical location, food habits, and ethnicity among different populations. The goal of this research topic is to generate and report novel statistical tools and machine learning algorithms to analyze the microbiome datasets and integrate these microbiome datasets with other OMICS and Clinical datasets for therapeutic innovations against non-communicable diseases like cancer, diabetes, inflammatory bowel disease (IBD), and chronic obstructive pulmonary disease (COPD). In addition, this topic also aims to explore various challenges such as data complexity, computational limitations, ethical concerns, validation bottlenecks, and regulatory hurdles that impact Bioinformatics-driven therapeutics discovery, especially while dealing with big as well as diverse microbiome data. This research topic will act as a platform to highlight various strategies to tackle the above-mentioned challenges by virtue of collaboration between researchers, AI specialists, and regulators.
Bioinformatics has been applied in developing new microbiome databases, identifying the role of microbe signatures or specific microbial communities in different disease conditions, and predicting the microbial metabolites' host interactions. There is still a substantial computational scope in integrating metagenomics datasets with other multi-omics data for identifying the cause and effect of a disease. This theme explores how bioinformatics, AI, and significant microbiome and other OMICS data drive advancements in drug discovery, precision medicine, and gene therapy by targeting the following key focus areas:
1) Computational Drug Discovery – AI-driven drug design, in-silico screening, and drug repurposing.
2) Precision Medicine – Genomics-based treatments, pharmacogenomics, and microbiome influences.
3) AI & Big Data in Therapeutics – Predictive modeling for drug safety, AI-generated molecules, and blockchain for secure data sharing.
5) Challenges & Ethics – Regulatory hurdles, data privacy, and bridging in-silico models with clinical trials.
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:
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.