Statistical Analysis of Molecular and Genomic Evolution by Xun Gu (2025, Hardcover)
Great Book Prices Store (340873)
96,7% positive Bewertungen
Preis:
US $125,97
(inkl. MwSt.)
Ca.CHF 102,34
+ $20,51 Versand
Rücknahme:
14 Tage Rückgabe. Käufer zahlt Rückversand. Wenn Sie ein eBay-Versandetikett verwenden, werden die Kosten dafür von Ihrer Rückerstattung abgezogen.
Artikelzustand:
- Sofort-KaufenStatistische Analyse der molekularen und genomischen Evolution, Hardcover von Gu, Xun...
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
Über dieses Produkt
Product Identifiers
PublisherOxford University Press, Incorporated
ISBN-100198816510
ISBN-139780198816515
eBay Product ID (ePID)21063304213
Product Key Features
Number of Pages176 Pages
LanguageEnglish
Publication NameStatistical Analysis of Molecular and Genomic Evolution
SubjectGenetics, Life Sciences / Biology
Publication Year2025
TypeTextbook
Subject AreaScience, Medical
AuthorXun Gu
FormatHardcover
Dimensions
Item Height0.6 in
Item Weight17.7 Oz
Item Length10 in
Item Width6.9 in
Additional Product Features
Intended AudienceScholarly & Professional
Dewey Edition23
ReviewsSo how successful is this book as a unification of evolutionary genomics? Restricting to the four aforementioned fields Gu considered under this subject, he makes impressive strides., "So how successful is this book as a unification of evolutionary genomics? Restricting to the four aforementioned fields Gu considered under this subject, he makes impressive strides." -- Nick Bailey, Evolution: International Journal of Organic Evolution, "So how successful is this book as a unification of evolutionary genomics? Restricting to the four aforementioned fields Gu considered under this subject, he makes impressive strides." -- Nicholas Bailey, Journal of Evolutionary Biology
Dewey Decimal572.838015195
Table Of ContentPreface1. Evolutionary Distance Analysis in Molecular Evolution2. Phylogeny-Dependent Analysis3. Neutrality Testing When Some Amino Acid Sites Are Strongly Constrained4. Functional Divergence after Gene Duplication: DIVERGE Analysis5. Rank of Genotype-Phenotype Map and Effective Gene Pleiotropy Estimation6. Evolution of Genetic Robustness after Gene Duplication7. Statistical Models of Transcriptome Evolution8. Ancestral Transcriptome Inference9. Strength of Expression Conservation in Transcriptome Evolution
SynopsisThe field of molecular and genomic evolution has been catalysed by the ever increasing availability of high throughput data such as transcriptome evolution, genotype-phenotype evolution, and genetic robustness. However, there is also an urgent requirement for the emergence of new paradigms (universally accepted scientific frameworks) supported by conceptual breakthroughs, since there is now widespread agreement that genome evolution research should be far more than a static pattern characterized by some well-known arguments and yet more big data for testing or extension. Furthermore, while the internet has made a vast body of literature and data widely accessible, researchers are increasingly facing significant challenges in how to select from this huge reserve appropriately and systematically. Statistical Analysis of Molecular and Genomic Evolution sets out to provide a solution to the most frequently asked question by next-generation young researchers in the area of evolutionary genomics: What is the knowledge that is essential for moving the research forward and where can it be found? Although the book incorporates the latest research foci, it is written at the simplest mathematical level whilst sophisticated enough to provide a deep understanding of current principles and methods. Technical issues are described only briefly, mathematical derivations are kept to a minimum, and it is structured and presented in a way that encourages its use as a graduate textbook. Mindful of the steep learning curve that some biologist readers may face, online appendices review basic mathematical and statistical concepts used in the book, and provide further examples and practical exercises.This is an advanced textbook suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, bioinformatics, mathematics, and statistics., Proposes a new framework of knowledge for the field of evolutionary genomics. Written at the simplest mathematical level whilst offering a clear explanation of complex statistical models and principles., The field of molecular and genomic evolution has been catalysed by the ever increasing availability of high throughput data such as transcriptome evolution, genotype-phenotype evolution, and genetic robustness. However, there is also an urgent requirement for the emergence of new paradigms (universally accepted scientific frameworks) supported by conceptual breakthroughs, since there is now widespread agreement that genome evolution research should be far more than a static pattern characterized by some well-known arguments and yet more big data for testing or extension. Furthermore, while the internet has made a vast body of literature and data widely accessible, researchers are increasingly facing significant challenges in how to select from this huge reserve appropriately and systematically. Statistical Analysis of Molecular and Genomic Evolution sets out to provide a solution to the most frequently asked question by next-generation young researchers in the area of evolutionary genomics: What is the knowledge that is essential for moving the research forward and where can it be found? Although the book incorporates the latest research foci, it is written at the simplest mathematical level whilst sophisticated enough to provide a deep understanding of current principles and methods. Technical issues are described only briefly, mathematical derivations are kept to a minimum, and it is structured and presented in a way that encourages its use as a graduate textbook. Mindful of the steep learning curve that some biologist readers may face, online appendices review basic mathematical and statistical concepts used in the book, and provide further examples and practical exercises. This is an advanced textbook suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, bioinformatics, mathematics, and statistics.
LC Classification NumberQH390.G8 2024
