CIBB 2024 - 19th Computational Intelligence Methods for Bioinformatics and Biostatistics conference

CIBB is a multidisciplinary forum for researchers interested in the broad application of computational intelligence to open problems in bioinformatics, biostatistics, systems and synthetic biology, and medical informatics. The 2024 edition aims to bring together prominent researchers from the international scientific community interested in advances and future perspectives in bioinformatics, biostatistics, and medical informatics. CIBB is also looking for contributions on current trends and future opportunities at the interface between computer and life sciences, as well as applications of computational intelligence to system and synthetic biology. Theoretical and experimental biologists are encouraged to participate and present their experiences facing novel challenges to foster multidisciplinary collaboration.

Authors are invited to submit a short paper (4-6 pages) describing their original contributions in the fields of bioinformatics, biostatistics, systems and synthetic biology, and medical informatics. Submitted contributions will undergo peer review, and all accepted contributions will be orally presented in plenary and special sessions. The authors of all the accepted short papers presented at the conference will be invited to submit an extended version of their manuscripts to the conference proceedings book in Springer Lecture Notes in Bioinformatics (LNBI) or to a supplement in a journal such as BMC Bioinformatics or Journal of Translational Medicine (details to be defined). In addition to the main track, the conference will provide a few special sessions focused on specific topics of interest for the CIBB audience. The list of special sessions will be available soon on the conference website.

TOPICS
- Applications of machine learning to bioinformatics or health datasets
- Data mining methods in biomedical contexts
- Artificial intelligence in biomedicine
- Next-generation sequencing bioalgorithms
- Multi-omics data analysis
- Statistical analysis of high dimensional omics data
- Algorithms for alternative splicing analysis
- Methods for visualisation of high-dimensional biomedical data
- Software tools for bioinformatics
- Methods for comparative genomics
- Computational tools for proteomics
- Simulation of biological systems and clinical populations
- Methods for the functional classification of genes
- Algorithms for molecular evolution and phylogenetic analysis
- Methods for unsupervised analysis, validation, and visualisation of structures discovered in bio-molecular data
- Health informatics and medical informatics
- Biomedical and microscopy imaging
- Methods for the integration of clinical, genetic, or environmental data
- Heterogeneous data integration and data fusion
- Algorithms for pharmacogenomics
- Biomedical text mining and natural language processing
- Bayesian methods for medical and biological data
- Health big data analytics
- Data-driven approaches for patient stratification, and prognosis or onset prediction
- Process mining in healthcare
- Information retrieval, and temporal and spatial representation and reasoning in biomedicine
- Simulation models, software, and tools (clinical decision support systems, patient engagement support, visual analytics, solutions for assisted living, and telemedicine)
- Biomedical signal processing
- Explainable AI and clinical model interpretation
- Personalised medicine for diagnosis and prognosis
- Statistical methods for the analysis of clinical data
- Prediction of secondary and tertiary protein structures
- Advanced pathway enrichment analysis methods
- Mass spectrometry data analysis in proteomics
- Bio-molecular databases and data mining
- Mathematical modeling and automated reasoning on biological and synthetic systems
- Computational simulation of biological systems
- Methods and advances in systems biology
- Spatio-temporal analysis of synthetic and biological systems
- Network systems biology
- Models for cell populations and tissues
- Methods for the engineering of synthetic components
- Modelling and engineering of interacting synthetic and biological systems
- Software tools for bioinformatics, biostatistics, systems and synthetic biology
- Computational drug discovery
- Operational research in healthcare and bioinformatics