Computational life sciences

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This comprehensive text covers various aspects of systems biology, structural biology, genomics, computational proteomics, molecular informatics, and distributed data mining. It explores structural protein interactions and their implications for kinase-inhibitor interactions in upregulated pancreas tumor gene expression. The book delves into biochemical pathway analysis through signature mining and presents recurrent neuro-fuzzy network models for gene regulatory interactions. Additionally, it discusses applications of dummy point scatterers in macromolecular X-ray crystallography and introduces BioRegistry, a structured metadata repository for bioinformatics databases. The text also highlights robust Perron cluster analysis for computational life sciences and methods for multiple alignment of protein structures in three dimensions. It features protein annotation techniques and tools like MAPPIS for aligning protein-protein interfaces. In genomics, it covers frequent itemsets for genomic profiling and gene selection using support vector machines. Computational proteomics is addressed with ProSpect, an R package for analyzing SELDI measurements, and algorithms for quantifying diagnostic markers in complex samples. Molecular informatics topics include molecular similarity searching, increasing diversity in in-silico screening, and structural RNA alignment. Finally, it discusses distributed data mining techniques like distrib