The Experts below are selected from a list of 280650 Experts worldwide ranked by ideXlab platform
Hannah Rempel - One of the best experts on this subject based on the ideXlab platform.
-
LibGuides: *Animal Sciences: Web Resources
2013Co-Authors: Hannah RempelAbstract:This research guide covers resources about Animal nutrition, Animal growth, Animal reproduction, Animal breeding, Animal Genetics, livestock, beef cattle, dairy cattle, goats, pigs, poultry, sheep, swine, horses.
-
LibGuides: *Animal Sciences: Find Articles
2013Co-Authors: Hannah RempelAbstract:This research guide covers resources about Animal nutrition, Animal growth, Animal reproduction, Animal breeding, Animal Genetics, livestock, beef cattle, dairy cattle, goats, pigs, poultry, sheep, swine, horses.
-
LibGuides: *Animal Sciences: Find Books
2013Co-Authors: Hannah RempelAbstract:This research guide covers resources about Animal nutrition, Animal growth, Animal reproduction, Animal breeding, Animal Genetics, livestock, beef cattle, dairy cattle, goats, pigs, poultry, sheep, swine, horses.
-
LibGuides: *Animal Sciences: Writing Help
2013Co-Authors: Hannah RempelAbstract:This research guide covers resources about Animal nutrition, Animal growth, Animal reproduction, Animal breeding, Animal Genetics, livestock, beef cattle, dairy cattle, goats, pigs, poultry, sheep, swine, horses.
-
LibGuides: *Animal and Rangeland Sciences: Web Resources
2013Co-Authors: Hannah RempelAbstract:This research guide covers resources about Animal nutrition, Animal growth, Animal reproduction, Animal breeding, Animal Genetics, livestock, beef cattle, dairy cattle, goats, pigs, poultry, sheep, swine, horses.
André Eggen - One of the best experts on this subject based on the ideXlab platform.
-
A review on SNP and other types of molecular markers and their use in Animal Genetics
Genetics selection evolution : GSE, 2002Co-Authors: Alain Vignal, Magali Sancristobal, Denis Milan, André EggenAbstract:During the last ten years, the use of molecular markers, revealing polymorphism at the DNA level, has been playing an increasing part in Animal Genetics studies. Amongst others, the microsatellite DNA marker has been the most widely used, due to its easy use by simple PCR, followed by a denaturing gel electrophoresis for allele size determination, and to the high degree of information provided by its large number of alleles per locus. Despite this, a new marker type, named SNP, for Single Nucleotide Polymorphism, is now on the scene and has gained high popularity, even though it is only a bi-allelic type of marker. In this review, we will discuss the reasons for this apparent step backwards, and the pertinence of the use of SNPs in Animal Genetics, in comparison with other marker types.
Seungwoo Hwang - One of the best experts on this subject based on the ideXlab platform.
-
whole transcriptome analyses of six thoroughbred horses before and after exercise using rna seq
BMC Genomics, 2012Co-Authors: Kyungdo Park, Jongsun Park, Junsu Ko, Kyoungtag Do, Hansol Choi, Sanghoon Song, Hongsik Kong, Young Mok Yang, Byunghak Jhun, Seungwoo HwangAbstract:Background Thoroughbred horses are the most expensive domestic Animals, and their running ability and knowledge about their muscle-related diseases are important in Animal Genetics. While the horse reference genome is available, there has been no large-scale functional annotation of the genome using expressed genes derived from transcriptomes.
Martin Larsen - One of the best experts on this subject based on the ideXlab platform.
-
a parallel solver for Animal Genetics
Parallel Computing, 1998Co-Authors: Per Madsen, Martin LarsenAbstract:The use of linear multivariate mixed models in Animal Genetics, leads to very large, sparse linear systems of equations. The sparse, symmetric coefficient matrix is too large to be constructed explicitly. We describe a parallel, iterative linear equation solver for large sparse systems, developed by DIAS and UNI-C. The solver takes advantage of the structure of the multivariate mixed model equations, and is based on Gauss-Seidel and second order Jacobi iteration. It is parallelized for distributed memory architectures.
-
PARA - A Parallel Solver for Animal Genetics
Lecture Notes in Computer Science, 1998Co-Authors: Per Madsen, Martin LarsenAbstract:The use of linear multivariate mixed models in Animal Genetics, leads to very large, sparse linear systems of equations. The sparse, symmetric coefficient matrix is too large to be constructed explicitly. We describe a parallel, iterative linear equation solver for large sparse systems, developed by DIAS and UNI-C. The solver takes advantage of the structure of the multivariate mixed model equations, and is based on Gauss-Seidel and second order Jacobi iteration. It is parallelized for distributed memory architectures.
Luca Ferretti - One of the best experts on this subject based on the ideXlab platform.
-
Massive parallel sequencing in Animal Genetics: wherefroms and wheretos
Animal genetics, 2010Co-Authors: Miguel Pérez-enciso, Luca FerrettiAbstract:Summary Next generation sequencing (NGS) has revolutionized genomics research, making it difficult to overstate its impact on studies of Biology. NGS will immediately allow researchers working in non-mainstream species to obtain complete genomes together with a comprehensive catalogue of variants. In addition, RNA-seq will be a decisive way to annotate genes that cannot be predicted purely by computational or comparative approaches. Future applications include whole genome sequence association studies, as opposed to classical SNP-based association, and implementing this new source of information into breeding programmes. For these purposes, one of the main advantages of sequencing vs. genotyping is the possibility of identifying copy number variants. Currently, experimental design is a topic of utmost interest, and here we discuss some of the options available, including pools and reduced representation libraries. Although bioinformatics is still an important bottleneck, this limitation is only transient and should not deter Animal geneticists from embracing these technologies.