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| LEADER |
01922naaaa2200277uu 4500 |
| 001 |
23339 |
| 005 |
20200318 |
| 020 |
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|a 978-1-0716-0199-0
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| 024 |
7 |
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|a 10.1007/978-1-0716-0199-0
|c doi
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| 041 |
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|h English
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| 042 |
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|a dc
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| 100 |
1 |
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|a Dutheil, Julien Y.
|e edt
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| 856 |
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|z Get fulltext
|u http://library.oapen.org/handle/20.500.12657/23339
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| 700 |
1 |
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|a Dutheil, Julien Y.
|e oth
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| 245 |
1 |
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|a Statistical Population Genomics
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| 260 |
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|b Springer Nature
|c 2020
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| 300 |
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|a 1 electronic resource (468 p.)
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| 506 |
0 |
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|a Open Access
|2 star
|f Unrestricted online access
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| 520 |
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|a This open access volume presents state-of-the-art inference methods in population genomics, focusing on data analysis based on rigorous statistical techniques. After introducing general concepts related to the biology of genomes and their evolution, the book covers state-of-the-art methods for the analysis of genomes in populations, including demography inference, population structure analysis and detection of selection, using both model-based inference and simulation procedures. Last but not least, it offers an overview of the current knowledge acquired by applying such methods to a large variety of eukaryotic organisms. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, pointers to the relevant literature, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Statistical Population Genomics aims to promote and ensure successful applications of population genomic methods to an increasing number of model systems and biological questions.
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| 540 |
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|a Creative Commons
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| 546 |
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|a English
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| 650 |
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7 |
|a Genetics (non-medical)
|2 bicssc
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| 650 |
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7 |
|a Molecular biology
|2 bicssc
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| 653 |
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|a Life sciences
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| 653 |
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|a Bioinformatics
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| 653 |
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|a Genetics
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