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"Various plant metabolites are useful for human life, and the induction and reduction of these metabolites using modern biotechnical technique is of enormous potential important especially in the fields of agriculture and health. Plant Metabolism and Biotechnology describes the biosynthetic pathways of plant metabolites, their function in plants, and some applications for biotechnology. Topics covered include: Photosynthetic carbon metabolism Starch and sugar biosynthesis Cellulose (cell wall) biosynthesis Lipid biosynthesis Nitrogen fixation and assimilation Sulfur metabolism Amino acid metabolism Nucleotide metabolism Purine alkaloids Nicotine Benzylisoquinoline alkaloids (morphine, codeine) Flavonoid metabolism Pigment metabolism Use of the metabolome for biotechnology Application to biomass improvement and biodiesel Plant Metabolism and Biotechnology is an essential guide to this important field for researchers and students of biochemistry, plant biology, metabolic engineering, biotechnology, food science, agriculture, and medicine."-- "This book will describe the biosynthetic pathways of plant metabolites, their function in plants, and some applications for biotechnology such as genetic engineering to produce transgenic plants for agriculture and drug production"--

Plants --- Plant biotechnology. --- SCIENCE / Life Sciences / Biochemistry. --- Metabolism. --- Biotechnologie --- Planten : biologie --- Metabolisme --- 66.098 --- Basic Sciences. Biotechnology --- Science --- Plant Biotechnology --- Life Sciences --- Biochemistry --- Plant Biotechnology. --- Biochemistry. --- Plant biotechnology --- Plant metabolism --- Metabolism --- Plant physiology --- Crop biotechnology --- Crops --- Agricultural biotechnology --- Effect of anaerobiosis on --- Biotechnology

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Gene function annotation has been a central question in molecular biology. The importance of computational function prediction is increasing because more and more large scale biological data, including genome sequences, protein structures, protein-protein interaction data, microarray expression data, and mass spectrometry data, are awaiting biological interpretation. Traditionally when a genome is sequenced, function annotation of genes is done by homology search methods, such as BLAST or FASTA. However, since these methods are developed before the genomics era, conventional use of them is not necessarily most suitable for analyzing a large scale data. Therefore we observe emerging development of computational gene function prediction methods, which are targeted to analyze large scale data, and also those which use such omics data as additional source of function prediction. In this book, we overview this emerging exciting field. The authors have been selected from 1) those who develop novel purely computational methods 2) those who develop function prediction methods which use omics data 3) those who maintain and update data base of function annotation of particular model organisms (E. coli), which are frequently referred.

Proteomics. --- Recombinant proteins. --- SCIENCE -- Life Sciences -- Biochemistry. --- Biochemistry --- Amino Acids, Peptides, and Proteins --- Genetics --- Biology --- Biological Science Disciplines --- Chemicals and Drugs --- Chemistry --- Natural Science Disciplines --- Disciplines and Occupations --- Genomics --- Proteomics --- Proteins --- Computational Biology --- Health & Biological Sciences --- Molecular biology. --- Structures. --- Molecular biochemistry --- Molecular biophysics --- Proteids --- Medicine. --- Biotechnology. --- Biochemistry. --- Bioinformatics. --- Biomedicine. --- Biomedicine general. --- Biochemistry, general. --- Biophysics --- Biomolecules --- Systems biology --- Polypeptides --- Chemical engineering --- Genetic engineering --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Molecular biology --- Biological chemistry --- Chemical composition of organisms --- Organisms --- Physiological chemistry --- Medical sciences --- Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Pathology --- Physicians --- Data processing --- Composition --- Health Workforce --- Biomedicine, general.