Angielski
Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics.§This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques.§This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics.§This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques.§Features of Data Mining for Biomarker Discovery:§- Presents the most challenging problems in biomarker discovery together with the most prominent methodological approaches for developing their effective solution.§- Offers the collaborative perspectives of distinguished researchers in the fields of biomedicine, biochemistry, data mining and machine learning.§- Introduces new spectral clustering, and hierarchical clustering algorithms specifically crafted for use in a large bioinformatics database.§This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well others interested in the interdisciplinary application of data mining techniques.
