الصفحة 1
الصفحة 1
Genetic Engineering : Principles and Methods
Genetic Engineering: Principles and Methods presents state-of-the-art discussions in modern genetics and genetic engineering. Recent volumes have covered gene therapy research, genetic mapping, plant science and technology, transport protein biochemistry, and viral vectors in gene therapy, among many other topics.
Genetic Engineering
Genetic Engineering: Principles and Methods presents state-of-the-art discussions in modern genetics and genetic engineering. Recent volumes have covered gene therapy research, genetic mapping, plant science and technology, transport protein biochemistry, and viral vectors in gene therapy, among many other topics.
Association Mapping in Plants
For the past decade, there has been success in using conventional map-based strategies in identification and cloning of quantitative trait loci (QTL) in model plant species including tomato and Arabidopsis. These quantitative traits are generally the products of many loci with varying degrees of effect upon the observed phenotypes. Recently, a new approach to genetic mapping has emerged called association mapping. This new technique takes into account the thousands of genes to evaluate for QTL effect and is a more efficient approach that does not require generation of segregating populations/large numbers of progeny. As it can utilize all of the historic recombination events in a diverse population of individuals it can generate higher resolution genetic maps and, is needed to complement current map based cloning methods.
Algorithms in Bioinformatics ; Vol.4175 : 6th International Workshop, WABI 2006, Zurich, Switzerland, September 11-13, 2006, Proceedings
This book constitutes the refereed proceedings of the 6th International Workshop on Algorithms in Bioinformatics, WABI 2006, held in Zurich, Switzerland in September 2006 in the course of the ALGO 2006 conference meetings. The 36 revised full papers presented were carefully reviewed and selected from 100 submissions. All current issues of algorithms in bioinformatics are addressed, ranging from mathematical tools to experimental studies of approximation algorithms and reports on significant computational analyses. Numerous biological problems are dealt with, including genetic mapping, sequence alignment and sequence analysis, phylogeny, comparative genomics, and protein structure. For the first time also machine-learning approaches along with combinatorial optimization are covered.
Algorithms in Bioinformatics ; Vol. 3692 ; 5th international workshop, WABI 2005, Mallorca, Spain, October 3-6, 2005, Proceedings
this book present the proceedings of the 5th Workshop on Algorithmsin Bioinformatics (WABI 2005) which took place in Spain, 2005. The Workshop on Algorithms in Bioinformatics highlights research workspecifically developed to address algorithmic problems in biosequence analysis. The emphasis is therefore on statistical and probabilistic algorithms that addressimportant problems in the field of molecular and structural biology. the workshop aims to present recent research results, includingsignificant work in progress, and to identify and explore directions of futureresearch.Original research papers (including significant work in progress) or state-of-the-art surveys were solicited on all aspects of algorithms in bioinformatics,including, but not limited to: exact and approximate algorithms for genomics,genetics, sequence analysis, gene and signal recognition, alignment, molecularevolution, phylogenetics, structure determination or prediction, gene expressionand gene networks, proteomics, functional genomics, and drug design.
Algorithms in Bioinformatics ; 7th International Workshop, WABI 2007, Philadelphia, PA, USA, September 8-9, 2007, Proceedings
All current issues of algorithms in bioinformatics are addressed, ranging from mathematical tools to experimental studies of approximation algorithms and reports on significant computational analyses. Numerous biological problems are dealt with, including genetic mapping, sequence alignment and sequence analysis, phylogeny, comparative genomics, and protein structure. Furthermore the papers feature high-performance computing approaches to computationally hard learning and optimization problems in bioinformatics and cover methods, software and dataset repositories for development and testing of such algorithms and their underlying models.
