Intelligent Computing Theories and Application

This three-volume set LNCS 10361, LNCS 10362, and LNAI 10363 constitutes the refereed proceedings of the 13th International Conference on Intelligent Computing, ICIC 2017, held in Liverpool, UK, in August 2017.

The 221 full papers and 15 short papers of the three proceedings volumes were carefully reviewed and selected from 639 submissions. This second volume of the set comprises 74 papers. The papers are organized in topical sections such as Pattern Recognition; Image Processing; Virtual Reality and Human-Computer Interaction; Healthcare Informatics Theory and Methods; Genetic Algorithms; Blind Source Separation; Intelligent Fault Diagnosis; Machine Learning; Knowledge Discovery and Data Mining; Gene Expression Array Analysis; Systems Biology; Modeling, Simulation, and Optimization of Biological Systems; Intelligent Computing in Computational Biology; Computational Genomics; Computational Proteomics; Gene Regulation Modeling and Analysis; SNPs and Haplotype Analysis; Protein-Protein Interaction Prediction; Protein Structure and Function Prediction; Next-Gen Sequencing and Metagenomics; Structure Prediction and Folding; Biomarker Discovery; Applications of Machine Learning Techniques to Computational Proteomics, Genomics, and Biological Sequence Analysis; Biomedical Image Analysis; Human-Machine Interaction: Shaping Tools Which Will Shape Us; Protein and Gene Bioinformatics: Analysis, Algorithms and Applications; Special Session on Computer Vision based Navigation; Neural Networks: Theory and Application.

Contenu

Pattern Recognition.- Image Processing.- Virtual Reality and Human-Computer Interaction.- Healthcare Informatics Theory and Methods.- Genetic Algorithms.- Blind Source Separation.- Intelligent Fault Diagnosis.- Machine Learning; Knowledge Discovery and Data Mining.- Gene Expression Array Analysis.- Systems Biology.- Modeling, Simulation, and Optimization of Biological Systems.- Intelligent Computing in Computational Biology.- Computational Genomics.- Computational Proteomics.- Gene Regulation Modeling and Analysis.- SNPs and Haplotype Analysis.- Protein-Protein Interaction Prediction.- Protein Structure and Function Prediction.- Next-Gen Sequencing and Metagenomics.- Structure Prediction and Folding.- Biomarker Discovery.- Applications of Machine Learning Techniques to Computational Proteomics, Genomics, and Biological Sequence Analysis; Biomedical Image Analysis.- Human-Machine Interaction: Shaping Tools Which Will Shape Us.- Protein and Gene Bioinformatics: Analysis, Algorithms and Applications.- Special Session on Computer Vision based Navigation.- Neural Networks: Theory and Application.