ECCB 2026 is a broad conference covering the full spectrum of computational biology and bioinformatics. We welcome submissions from all areas of the field. When submitting, please select the scientific area that best matches your work.
The conference programme will be structured around five core scientific areas, each representing a major domain of research:
We encourage submitters to select the scientific area(s) that best reflect the focus of their work. While there is no dedicated “Applications” track, application-oriented contributions are welcome and should be submitted under the area that most closely relates to the work.
Authors will be asked to select one primary and one secondary scientific area to help guide the review process and inform session planning.
This session focuses on computational advances in genome sequencing, annotation, functional genomics, epigenomics, and genome editing technologies like CRISPR. It includes research exploring disease genomics, genetic predispositions, and therapeutic targets. Submissions related to imaging applications in genomic studies (e.g., spatial genomics) are also welcome.
Keywords: genome sequencing, genome assembly, genome editing, genetic variation, population genomics, epigenetic modifications, methylation, genome annotation, pangenomics.
This session invites submissions on bioinformatics advances in transcriptomics, gene expression analysis, and regulatory network inference, including disease-focused studies, precision medicine, and other health-related studies. Topics such as single-molecule profiling, spatial transcriptomics, single-cell RNA-seq, and regulatory element analysis are encouraged.
Keywords: RNA-seq, transcript quantification, alternative splicing, non-coding RNAs, regulatory elements, enhancers, promoters, transcriptional regulation, RNA metabolism, gene expression dynamics, non-coding variants, eQTLs.
This session explores computational methods for structural biology, protein dynamics and allostery, interactions between proteins and other molecules, protein evolution, and protein design. It includes research on disease-related protein analysis, drug target identification, and drug design. Approaches based on sequence, structure, dynamics, or function are all welcome. Submissions that integrate computational and experimental approaches are also encouraged, e.g. about cryo-EM, X-ray crystallography, and proteomics. .
Keywords: protein structure, dynamics, protein-protein interactions, protein-small molecule interactions, protein evolution, protein engineering, protein design, drug design, cryo-EM, X-ray crystallography, mass spectrometry, computational proteomics.
This session highlights computational systems biology approaches that integrate multi-omics data (e.g., genomics, transcriptomics, proteomics, metabolomics) or other data types (e.g., imaging) to study biological systems. We welcome approaches modeling biological processes across spatio-temporal scales to elucidate their mechanisms, or to predict responses to perturbations such as drug treatments.
Keywords: systems biology, data integration, multi-omics and multimodal data, metabolic and signaling pathways, network inference, dynamic modeling, predictive modeling.
This session focuses on computational approaches for biodiversity conservation, environmental genomics, metagenomics, and microbiome research. It highlights the interactions between organisms and their environments, and between hosts, pathogens, and microbiomes. Topics include species monitoring, climate change adaptation, bioinformatics tools for environmental imaging, and ecosystem modeling for conservation and sustainable agriculture. The session also encompasses the use of sequencing data to reconstruct evolutionary histories, conduct comparative genomic analyses, and establish reference genomes to uncover the genetic basis of biodiversity.
Keywords: metagenomics, microbiomes, biodiversity, ecological networks, conservation genomics, environmental DNA (eDNA), climate impact studies, sustainable agriculture, ecosystem modeling, bioinformatics for environmental data, phylogenomics, pathogen genomes, host-pathogen and host-microbiome interactions, comparative genomics.