Bioinformatics for Biomedical Science and Clinical ApplicationsContemporary biomedical and clinical research is undergoing constant development thanks to the rapid advancement of various high throughput technologies at the DNA, RNA and protein levels. These technologies can generate vast amounts of raw data, making bioinformatics methodologies essential in their use for basic biomedical and clinical applications.Bioinformatics for biomedical science and clinical applications demonstrates what these cutting-edge technologies can do and examines how to design an appropriate study, including how to deal with data and address specific clinical questions. The first two chapters consider Bioinformatics and analysis of the human genome. The subsequent three chapters cover the introduction of Transcriptomics, Proteomics and Systems biomedical science. The remaining chapters move on to critical developments, clinical information and conclude with domain knowledge and adaptivity. - A coherent presentation of concepts, methodologies and practical tools that systematically lead to significant discoveries in the biomedical and clinical area - Real examples of cutting edge discoveries - The introduction of study types and technologies for all the DNA, RNA and protein levels |
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Affymetrix algorithm allele allograft amino acid annotation antibodies arrays assay association studies base calling Bioinformatics biological biomarkers biomedical science cancer cell cycles cellular chromosomal clinical clustering codon complex computational conceptual framework contrast level analysis database designed detection disease domain drug effect enrichment analysis example exploration expression levels expression profiles filters functions gene expression gene level gene ontology genetic genome browser Genome-wide association genomic variants genotype global groups GWAS hallmarks haplotype HapMap human genome integrated investigations ions layer matrix metastasis methods microarray module level molecular MS/MS multiple nodes novo nucleotide offers omics P-values paired patients peptide phenotype platforms plot prediction probe protein sequences protein structures proteomics Published by Woodhead quantitative regions represent samples sequence alignment signal similar simulation SNPs somatic mutations spectrum subjects tagging targeted tissue transcriptomics treatment tumor types variables viral visualization Warfarin Woodhead Publishing Limited