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Evolutionary Genomics

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Evolutionary Genomics
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18 894,00 JPY
Typical price3 273,00 PLN
Lowest (90 days)139,00 PLN
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Last updated1 สัปดาห์ที่แล้ว
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2026-08-08 2026-08-15
ประวัติราคา
อัปเดตเมื่อราคา
2026-08-08139,00
2026-08-15156,00
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SP SpringerNatureLink Shop INT 18 875,00 JPY 19,00 JPY 18 894,00 JPY มีจำหน่าย 5 วันที่แล้ว View offer
SP Springer Nature Author 18 875,00 JPY 15,00 JPY 18 890,00 JPY มีจำหน่าย 1 สัปดาห์ที่แล้ว View offer
SP SpringerNatureLink Shop INT 156,00 EUR free 156,00 EUR มีจำหน่าย 5 วันที่แล้ว View offer

ราคาและความพร้อมจำหน่ายอาจมีการเปลี่ยนแปลง อัปเดตล่าสุด: 08.08.2026 23:32.

EAN 9781617795855
Springer Nature
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Together with early theoretical work in population genetics, the debate on sources of genetic makeup initiated by proponents of the neutral theory made a solid contribution to the spectacular growth in statistical methodologies for molecular evolution. Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies.  Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of articles encompassing theoretical works and hands-on tutorials, as well as many reviews with key biological insight.  Volume 2 begins with phylogenomics and continues with in-depth coverage of natural selection, recombination, and genomic innovation. The remaining chapters treat topics of more recent interest, including population genomics, -omics studies, and computational issues related to the handling of large-scale genomic data.  Written in the highly successful Methods in Molecular Biology™ series format, this work provides the kind of advice on methodology and implementation that is crucial for getting ahead in genomic data analyses.   Comprehensive and cutting-edge, Evolutionary Genomics: Statistical and Computational Methods is a treasure chest of state-of the-art methods to study genomic and omics data, certain to inspire both young and experienced readers to join the interdisciplinary field of evolutionary genomics.

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