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CIBB 2023 : Computational Intelligence Methods for Bioinformatics and Biostatistics | |||||||||||||||
Link: https://cibb2023.dei.unipd.it/ | |||||||||||||||
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Call For Papers | |||||||||||||||
SHORT PAPER SUBMISSION
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 before acceptance. All accepted contributions will be presented in plenary oral sessions and special sessions. Authors of accepted short papers are encouraged to post their short papers on preprint servers such as arXiv, bioRxiv, or medRxiv. The conference proceedings will be shared among the participants during the conference. The proceedings will not be indexed on Scopus, but, after the conference, 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 BMC Medical Informatics and Decision Making. Topics of interest include: - 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 the 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 modelling 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 |
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