Gordon Luikart mostly deals with Genetics, Conservation genetics, Population genetics, Ecology and Allele frequency. His Genetics study typically links adjacent topics like Sample size determination. His Conservation genetics research is multidisciplinary, relying on both Genomics, Sampling, Genetic structure, Gene flow and Data science.
The concepts of his Population genetics study are interwoven with issues in Population size, Selection and Small population size. His Ecology research is multidisciplinary, incorporating elements of Statistic, Biological dispersal, Panmixia and Genetic diversity. Gordon Luikart interconnects Population bottleneck and Loss of heterozygosity in the investigation of issues within Allele frequency.
Genetics, Ecology, Evolutionary biology, Microsatellite and Conservation genetics are his primary areas of study. He has researched Ecology in several fields, including Gene flow, Genetic diversity, Biological dispersal and Population genetics. The study incorporates disciplines such as Landscape ecology, Ecology, Selection and Population bottleneck in addition to Population genetics.
His Evolutionary biology study combines topics in areas such as Biodiversity and Allele frequency. Gordon Luikart has included themes like Zoology, Capra ibex, Loss of heterozygosity and Candidate gene in his Microsatellite study. His research in Conservation genetics tackles topics such as Genomics which are related to areas like Data science and Molecular ecology.
Gordon Luikart spends much of his time researching Ecology, Evolutionary biology, Population genomics, Genomics and Conservation genetics. His studies in Ecology integrate themes in fields like Fishery and Genetic diversity. Gordon Luikart combines subjects such as Genetic linkage, Allele, Allele frequency and Genetic architecture with his study of Evolutionary biology.
Population genomics is a primary field of his research addressed under Genetics. His research integrates issues of Genetic divergence and Black-tailed deer in his study of Genetics. His Conservation genetics research incorporates elements of Synteny, Locus, Genetic structure and Inbreeding depression.
His scientific interests lie mostly in Ecology, Genomics, Conservation genetics, Population genomics and Genetics. His research in Genomics intersects with topics in Natural selection, Environmental resource management, Allele, Conservation biology and Data science. His Conservation genetics research is multidisciplinary, incorporating perspectives in Sample size determination, Population genetics, Genetic diversity, Ecology and Genetic variation.
His Population genetics research includes themes of Genetic isolate, Nucleotide diversity and Computational biology. His study in Ecology is interdisciplinary in nature, drawing from both Genotyping and DNA sequencing. His Genetics study combines topics from a wide range of disciplines, such as Selection, Resistance and Mating system.
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Description and Power Analysis of Two Tests for Detecting Recent Population Bottlenecks from Allele Frequency Data
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Genetics (1996)
Computer note. BOTTLENECK: a computer program for detecting recent reductions in the effective size using allele frequency data
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Journal of Heredity (1999)
Conservation and the genetics of populations
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(2006)
Landscape genetics: combining landscape ecology and population genetics
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Trends in Ecology and Evolution (2003)
Distortion of allele frequency distributions provides a test for recent population bottlenecks
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Journal of Heredity (1998)
New Methods Employing Multilocus Genotypes to Select or Exclude Populations as Origins of Individuals
Jean-Marie Cornuet;Sylvain Piry;Gordon Luikart;Arnaud Estoup.
Genetics (1999)
The power and promise of population genomics: from genotyping to genome typing
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Nature Reviews Genetics (2003)
Estimating the probability of identity among genotypes in natural populations: cautions and guidelines
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Molecular Ecology (2001)
Genomics and the future of conservation genetics
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Nature Reviews Genetics (2010)
LOSITAN: A workbench to detect molecular adaptation based on a Fst-outlier method
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BMC Bioinformatics (2008)
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