title: Bioinformatics tools and databases for the study of human growth hormone.
abstract: Advances in novel molecular biological diagnostic methods are changing the way of diagnosis and study of metabolic disorders like growth hormone deficiency. Faster sequencing and genotyping methods require strong bioinformatics tools to make sense of the vast amount of data generated by modern laboratories. Advances in genome sequencing and computational power to analyze the whole genome sequences will guide the diagnostics of future. In this chapter, an overview of some basic bioinformatics resources that are needed to study metabolic disorders are reviewed and some examples of bioinformatics analysis of human growth hormone gene, protein and structure are provided.
authors.affiliation: Pediatric Endocrinology, Diabetology and Metabolism, Department of Clinical Research, University of Bern, and University Children's Hospital Bern, Bern, Switzerland. amit@pandeylab.org
authors.forename: Amit V
authors.initials: AV
authors.lastname: Pandey
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D023281:Genomics / Q000379:methods*; D019382:Human Growth Hormone / Q000737:chemistry* / Q000235:genetics* / Q000378:metabolism / Q000502:physiology; D006801:Humans; D008954:Models, Biological; D008958:Models, Molecular; D008969:Molecular Sequence Data; D017433:Protein Structure, Secondary; D012984:Software
chemical_list: D019382:Human Growth Hormone