國立虎尾科技大學 |

Phenotypes and genotypes = the search for influential genes /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Phenotypes and genotypes/ by Florian Frommlet, Malgorzata Bogdan, David Ramsey.
其他題名:	the search for influential genes /
作者:	Frommlet, Florian.
其他作者:	Bogdan, Malgorzata.
出版者:	London :Springer London : : 2016.,
面頁冊數:	xii, 222 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Genetics. -
電子資源:	http://dx.doi.org/10.1007/978-1-4471-5310-8
ISBN:	9781447153108

Phenotypes and genotypes = the search for influential genes /
Frommlet, Florian.

Phenotypes and genotypesthe search for influential genes /[electronic resource] :by Florian Frommlet, Malgorzata Bogdan, David Ramsey. - London :Springer London :2016. - xii, 222 p. :ill., digital ;24 cm. - Computational biology,v.181568-2684 ;. - Computational biology ;v.23..

This timely text presents a comprehensive guide to genetic association, a new and rapidly expanding field that aims to elucidate how our genetic code (genotypes) influences the traits we possess (phenotypes) The book provides a detailed review of methods of gene mapping used in association with experimental crosses, as well as genome-wide association studies. Emphasis is placed on model selection procedures for analyzing data from large-scale genome scans based on specifically designed modifications of the Bayesian information criterion. Topics and features: Presents a thorough introduction to the theoretical background to studies of genetic association (both genetic and statistical) Reviews the latest advances in the field, highlighting the advantages and shortcomings of the currently most commonly used methods Illustrates the properties of methods for mapping quantitative trait loci using computer simulations and the analysis of real data Discusses open challenges that remain to be solved in the future Includes an extensive statistical appendix as a reference for those who are not totally familiar with the fundamentals of statistics This important work is essential reading for researchers and graduate students wishing to enter the field of statistical genetics and/or interested in statistical issues related to the analysis of high-dimensional data. No prior background knowledge of genetics is required, although some basic mathematical and computer science skills are assumed. Dr. Florian Frommlet is a researcher in the Center for Medical Statistics, Informatics, and Intelligent Systems at the Medical University of Vienna, Austria. Dr. Malgorzata Bogdan is an Associate Professor in the Institute of Mathematics at Wroclaw University, Poland. Dr. David Ramsey is a Senior Lecturer in the Department of Operations Research at Wroclaw University of Technology, Poland.

ISBN: 9781447153108

Standard No.: 10.1007/978-1-4471-5310-8doiSubjects--Topical Terms:

578972
Genetics.

LC Class. No.: QH430

Dewey Class. No.: 576.5

Phenotypes and genotypes = the search for influential genes /
LDR:02925nam a2200325 a 4500 001 862406
003 DE-He213
005 20160824103031.0
006 m d
007 cr nn 008maaau
008 170720s2016 enk s 0 eng d
020 $a 9781447153108 $q (electronic bk.)
020 $a 9781447153092 $q (paper)
024 7 $a 10.1007/978-1-4471-5310-8 $2 doi
035 $a 978-1-4471-5310-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QH430
072 7 $a PSA $2 bicssc
072 7 $a UB $2 bicssc
072 7 $a COM014000 $2 bisacsh
082 0 4 $a 576.5 $2 23
090 $a QH430 $b .F932 2016
100 1 $a Frommlet, Florian. $3 1105738
245 1 0 $a Phenotypes and genotypes $h [electronic resource] : $b the search for influential genes / $c by Florian Frommlet, Malgorzata Bogdan, David Ramsey.
260 $a London : $c 2016. $b Springer London : $b Imprint: Springer,
300 $a xii, 222 p. : $b ill., digital ; $c 24 cm.
490 1 $a Computational biology, $x 1568-2684 ; $v v.18
520 $a This timely text presents a comprehensive guide to genetic association, a new and rapidly expanding field that aims to elucidate how our genetic code (genotypes) influences the traits we possess (phenotypes) The book provides a detailed review of methods of gene mapping used in association with experimental crosses, as well as genome-wide association studies. Emphasis is placed on model selection procedures for analyzing data from large-scale genome scans based on specifically designed modifications of the Bayesian information criterion. Topics and features: Presents a thorough introduction to the theoretical background to studies of genetic association (both genetic and statistical) Reviews the latest advances in the field, highlighting the advantages and shortcomings of the currently most commonly used methods Illustrates the properties of methods for mapping quantitative trait loci using computer simulations and the analysis of real data Discusses open challenges that remain to be solved in the future Includes an extensive statistical appendix as a reference for those who are not totally familiar with the fundamentals of statistics This important work is essential reading for researchers and graduate students wishing to enter the field of statistical genetics and/or interested in statistical issues related to the analysis of high-dimensional data. No prior background knowledge of genetics is required, although some basic mathematical and computer science skills are assumed. Dr. Florian Frommlet is a researcher in the Center for Medical Statistics, Informatics, and Intelligent Systems at the Medical University of Vienna, Austria. Dr. Malgorzata Bogdan is an Associate Professor in the Institute of Mathematics at Wroclaw University, Poland. Dr. David Ramsey is a Senior Lecturer in the Department of Operations Research at Wroclaw University of Technology, Poland.
650 0 $a Genetics. $3 578972
650 0 $a Phenotype. $3 655348
650 1 4 $a Computer Science. $3 593922
650 2 4 $a Computational Biology/Bioinformatics. $3 677363
650 2 4 $a Bioinformatics. $3 583857
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 670172
700 1 $a Bogdan, Malgorzata. $3 1105739
700 1 $a Ramsey, David. $3 1105740
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Computational biology ; $v v.23. $3 1069228
856 4 0 $u http://dx.doi.org/10.1007/978-1-4471-5310-8
950 $a Computer Science (Springer-11645)