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Thematische Bibliographien / Genetic variation

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Auswahl der wissenschaftlichen Literatur zum Thema „Genetic variation“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 28. Juli 2024

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Zeitschriftenartikel zum Thema "Genetic variation"

1

Ansari, K. I., N. Palacios, C. Araya, T. Langin, D. Egan und F. M. Doohan. „Genetic variation between Colletotrichum lindemuthianum isolates“. Plant Protection Science 38, SI 2 - 6th Conf EFPP 2002 (31.12.2017): 378–80. http://dx.doi.org/10.17221/10496-pps.

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We characterized the genetic diversity of seventy-three C. lindemuthianum isolates collected from 10 different countries by Amplified Fragment Length Polymorphism (AFLP) analysis. The results of this research highlighted the fact that there is huge variation in the genetic diversity between isolates from different countries. The molecular profile of the isolates showed correlation with geographic origin of the isolates.

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Paaby, Annalise, und Greg Gibson. „Cryptic Genetic Variation in Evolutionary Developmental Genetics“. Biology 5, Nr. 2 (13.06.2016): 28. http://dx.doi.org/10.3390/biology5020028.

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Bedge, Kiran, und Pratima Salunkhe. „Population Genetics : A Review“. International Journal of Scientific Research in Science and Technology 11, Nr. 2 (20.04.2024): 746–48. http://dx.doi.org/10.32628/ijsrst24112109.

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Genetics is the study of genes and genetic variations alongwith the hereditary characteristics of an organism. Genetics is a central pillar of biology. It overlaps with other areas, such as: Agriculture, Medicine, Biotechnology. Genetics involves studying: Gene structure and function Gene variation and changes How genes affect health, appearance, and personality. Population genetics studies genetic variation within and among populations, based on the Hardy-Weinberg law, which remains constant in large populations with random mating and minimal mutation, selection, and migration.

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Ellsworth, Katarzyna A., Irene Moon, Bruce W. Eckloff, Brooke L. Fridley, Gregory D. Jenkins, Anthony Batzler, Joanna M. Biernacka et al. „FKBP5 genetic variation“. Pharmacogenetics and Genomics 23, Nr. 3 (März 2013): 156–66. http://dx.doi.org/10.1097/fpc.0b013e32835dc133.

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Ryan, Stephen G. „Human Genetic Variation“. Pharmacogenomics 3, Nr. 1 (Januar 2002): 9–11. http://dx.doi.org/10.1517/14622416.3.1.9.

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Gibson, Greg, und Laura K. Reed. „Cryptic genetic variation“. Current Biology 18, Nr. 21 (November 2008): R989—R990. http://dx.doi.org/10.1016/j.cub.2008.08.011.

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Vihinen, Mauno. „Individual Genetic Heterogeneity“. Genes 13, Nr. 9 (10.09.2022): 1626. http://dx.doi.org/10.3390/genes13091626.

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Genetic variation has been widely covered in literature, however, not from the perspective of an individual in any species. Here, a synthesis of genetic concepts and variations relevant for individual genetic constitution is provided. All the different levels of genetic information and variation are covered, ranging from whether an organism is unmixed or hybrid, has variations in genome, chromosomes, and more locally in DNA regions, to epigenetic variants or alterations in selfish genetic elements. Genetic constitution and heterogeneity of microbiota are highly relevant for health and wellbeing of an individual. Mutation rates vary widely for variation types, e.g., due to the sequence context. Genetic information guides numerous aspects in organisms. Types of inheritance, whether Mendelian or non-Mendelian, zygosity, sexual reproduction, and sex determination are covered. Functions of DNA and functional effects of variations are introduced, along with mechanism that reduce and modulate functional effects, including TARAR countermeasures and intraindividual genetic conflict. TARAR countermeasures for tolerance, avoidance, repair, attenuation, and resistance are essential for life, integrity of genetic information, and gene expression. The genetic composition, effects of variations, and their expression are considered also in diseases and personalized medicine. The text synthesizes knowledge and insight on individual genetic heterogeneity and organizes and systematizes the central concepts.

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Varvio, Sirkka-Liisa, Ranajit Chakraborty und Masatoshi Nei. „Genetic variation in subdivided populations and conservation genetics“. Heredity 57, Nr. 2 (Oktober 1986): 189–98. http://dx.doi.org/10.1038/hdy.1986.109.

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Korpelainen, Helena, und Noris Salazar Allen. „Genetic variation in three species of epiphytic Octoblepharum (Leucobryaceae)“. Nova Hedwigia 68, Nr. 3-4 (02.06.1999): 281–90. http://dx.doi.org/10.1127/nova.hedwigia/68/1999/281.

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Biros, Erik, Mirko Karan und Jonathan Golledge. „Genetic Variation and Atherosclerosis“. Current Genomics 9, Nr. 1 (01.03.2008): 29–42. http://dx.doi.org/10.2174/138920208783884856.

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Dissertationen zum Thema "Genetic variation"

1

Walker, Tina Kay. „Genetic variation in schistosomes“. Thesis, Brunel University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.278245.

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Gresham, David J. „Genetic variation and disease in the Roma (Gypsies)“. Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2001. https://ro.ecu.edu.au/theses/1516.

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The Roma (Gypsies) are a European people composed of a mosaic of culturally heterogeneous populations. Linguistic analyses point to their origins in the Indian subcontinent. Cultural diversity in extant Romani populations suggests that they are descended from a mixture of Indian populations. Previous population genetic studies of the Roma have supported this claim by demonstrating the genetic heterogeneity of Romani populations. More recently, medical genetic research has detected identical founder mutations in separated Romani populations, which provides evidence of their relatedness. In this thesis, the genetic heritage of the Roma and its significance for genetic disease and research is investigated. Male and female lineages were analysed in eight traditionally endogamous Romani populations. Asian specific Y chromosome haplogroup VI-68 and mitochondrial DNA (mtDNA) haplogroup M were detected in all populations and accounted for 39% and 25% of all lineages respectively. Diversity within haplogroups was assessed by genotyping Y chromosome short tandem repeats (YSTRs) and sequencing the mtDNA hypervariable segment 1 (HVSl). Lineages within haplogroups VI-68 and M were found to be closely related suggesting that Romani populations are predominantly descended from a single Indian ethnic population. The differing historical legacies of Romani populations and adherence to endogamous practices have resulted in genetic substructure and limited diversity within populations. Thus, the Roma are shown to comprise a conglomerate of related admixed population isolates. The unique genetic heritage of the Roma provides a powerful tool for the positional cloning of monogenic disease genes. This is demonstrated through the reduction of the critical chromosomal region for a novel genetic disorder, hereditary motor and sensory neuropathy type Lom (HMSNL). In the initial report, the HMSNL disease locus was defined as a 3cM region on chromosome 8q24. In this study, refined genetic mapping utilising historical and parental recombinations observed in Romani individuals from different populations reduced the HMSNL critical interval to 202kb. Sequence analysis of two genes contained within this genomic interval found all affected individuals to be homozygous for a CT mutation in codon 148 of N-myc downstream regulated gene 1 (NDRGJ), resulting in a truncating Rl48X mutation. Investigation of the population distribution of the R148X disease allele shows that it occurs in six of eight separated Romani populations. Another founder mutation, C283Y in the y-sarcoglycan gene (SGCG), which causes limb girdle muscular dystrophy type 2C (LGMD2C), was found in two of eight Romani populations. Profound founder effects are apparent within Romani populations with a carrier frequency of 19.5% determined for the R148X mutation in the Lom population, and 6.25% for the C283Y allele in the Turgovzi population. High carrier frequencies for autosomal recessive diseases can be expected to pose a significant health risk for these communities. Thus, community-wide carrier testing represents a potential means of addressing this health problem. A pilot community based carrier-testing program was implemented in a Romani community of north eastern Bulgaria and relevant attitudes assessed by means of a questionnaire. Community-based carrier screening was demonstrated to be an appropriate approach to improving health amongst the Roma.

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Vetayasuporn, Sopit. „Genetic variation in Pinus kesiya“. Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301651.

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Wright, Dominic. „Genetic variation in zebrafish behaviour“. Thesis, University of Leeds, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414510.

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Keightley, Peter D. „Studies of quantitative genetic variation“. Thesis, University of Edinburgh, 1988. http://hdl.handle.net/1842/12340.

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Yang, Ian Anthony. „Genetic variation in COPD pathogenesis /“. [St. Lucia, Qld.], 2001. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16860.pdf.

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De, Bustos Cecilia. „Genetic and Epigenetic Variation in the Human Genome : Analysis of Phenotypically Normal Individuals and Patients Affected with Brain Tumors“. Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6629.

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Zhou, Huitong. „Genetic variation in Dichelobacter nodosus Fimbriae“. Lincoln University, 2001. http://hdl.handle.net/10182/2244.

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Footrot is a contagious hoof disease of ruminants. It is endemic in New Zealand and throughout sheep and goat farming regions of the world. The disease results from a mixed bacterial infection, but the essential agent is Dichelobacter nodosus, a Gram-negative, anaerobic bacterium that possesses type-IV fimbriae on its surface. Genetic variation in the fimbriae of D. nodosus was investigated in this study. Using the polymerase chain reaction (PCR), the variable region of the gene encoding the fimbrial subunit (fimA) was amplified from bacterial DNA extracted from footrot lesions. Different fimA amplimers were differentiated by single-strand conformation polymorphism (SSCP) analysis. In conjunction with DNA sequencing, 15 unique sequences of D. nodosus fimA were obtained from 14 footrot samples taken from 6 farming regions throughout New Zealand. When these sequences were compared to fimA of known serogroups, it revealed that there were at least 15 D. nodosus strains, representing 8 serogroups, present on New Zealand farms. The predominant serogroup was B which contained 6 strains, followed by serogroups F, H and G. No strains from serogroups D and I were detected in this investigation. Twelve out of the 15 New Zealand D. nodosus strains had fimbriae different to those previously reported and the presence of multiple strains on a single hoof was common (86% of samples). The fimA sequences from the 12 D. nodosus strains incorporated into the footrot vaccine currently available in New Zealand were determined. A primer set targeting the relatively conserved fimA regions and based on the published sequence of serogroup M Nepalese isolates (designated M-Nep), failed to amplify fimA from the vaccine serotype M strain (designated as M-SPAHL). When the downstream primer was substituted with a primer that was specific for other serogroups of D. nodosus, the fimA gene was successfully amplified. Cloning followed by DNA sequencing, revealed that M-SPAHL fimA was different to M-Nep fimA. The predicted amino acid sequence of M-SPAHL fimA did not show homology to any known serogroups or serotypes. The most similar sequence was from serotype F1, and not M-Nep. The sequence difference between M-SPAHL and M-Nep was larger than that expected within a serogroup. The consequences of serological relatedness and sequence dissimilarity are discussed. Only eight of the 15 New Zealand field strains had fimbriae identical to those of the vaccine strains, while the remaining seven strains possessed different fimbriae. In addition, the vaccine contained two more D. nodosus strains, representing two sera groups, that were not found on the New Zealand farms investigated in this study. This may, to some extent, explain why the current footrot vaccine is at times less efficient in New Zealand. Another 17 footrot samples were screened for new or additional D. nodosus strains. Two PCR amplimers (designated X and Y) derived from footrot samples generated SSCP patterns different to those of previously identified strains. DNA sequencing revealed that these two fragments possessed novel sequences. The upstream of X (nt 1-183) was identical to serotype M1 while its downstream (nt 223-414) was identical to serotype F1; the upstream of Y (nt 1-116) was identical to serotype E1 whereas its downstream (nt 148-423) was identical to serotype F1. A 14-mer sequence consisting of two partially overlapping Chi-like sequences, 5'-GCTGGTGCTGGTGA-3', was also found in these fragments. Two primer sets with the downstream primer specific for serotype Fl and the upstream primer specific for serotype M1 or E1, produced PCR products of the expected sizes from the footrot samples from which fragments X and Y were isolated, respectively. These primer sets did not appear to amplify artificially mixed genomic DNA from serotypes M1 and F1 or E1 and F1. However, when the reactions were re-amplified, PCR recombination artefacts were observed, suggesting that PCR recombination does occur, but at a low frequency. It therefore seems more likely that fragments X and Y reflect genuine fimA sequences of D. nodosus which have resulted from in vivo DNA recombination, than from a PCR recombination artifact. The genetic capability for recombination at the fimbrial subunit locus may therefore endow D. nodosus with the ability to alter its antigenic appearance. D. nodosus strains present in footrot lesions can be genotyped using a PCR-SSCP/sequencing technique. However, this typing technique requires cloning and screening of D. nodosus fimA sequences, which is both laborious and costly. A rapid molecular typing system for D. nodosus was therefore developed in this study. A close examination of available D. nodosus fimA sequences revealed regions that appear to be specific for serogroups and serotypes. These regions were used to design a panel of sequence-specific oligonucleotide probes (SSOPs), and a rapid and accurate D. nodosus typing system using PCR and reverse dot-blot hybridisation (PCR/oligotyping) was subsequently developed. The variable region of D. nodosus fimA, amplified and labelled with digoxigenin (DIG) in a single multiplex PCR amplification, was hybridised to a panel of group- and type-specific, poly-dT tailed oligonucleotides that were immobilised on a nylon membrane strip. A mixture of positive control poly-dT tailed oligonucleotides was also included on the membrane. After hybridisation the membrane was washed to a defined specificity, and DIG-labelled fragments that had hybridised were detected. The specificity of the oligonucleotides was verified by the lack of cross-reactivity with D. nodosus fimA sequences that had a single base difference. DNA from 14 footrot samples previously genotyped by PCR-SSCP/sequencing, was assayed using the PCR/oligotyping technique. All types of D. nodosus which had been detected previously with a PCR-SSCP/sequencing method were detected by this procedure. However, for three of the 14 footrot samples, PCR/oligotyping detected additional types of D. nodosus. Further PCR amplification using type-specific primers, confirmed that these types were present in the original footrot samples. These results indicate that PCR/oligotyping is a specific, accurate, and useful tool for typing footrot samples. In combination with a rapid DNA extraction protocol, D. nodosus present in a footrot sample can be accurately genotyped in less than two days. Individual animals from the same farm, or the same paddock, were often infected by different strains of D. nodosus. This suggests a host role in mediating footrot infection, or that the interaction between the pathogen and the host is important. In order to better understand the interaction between the bacterium and the host, two polymorphic ovine class II MHC genes DQA1 and DQA2, which have been previously shown to be important in footrot infection, were also investigated in this study. PCR-SSCP/sequencing analysis of the DQA1 locus revealed ten unique ovine DQA1 sequences, with five of them being newly identified. This increases the number of known ovine DQA1 alleles from 8 to 13 (including a null allele), implying a high level of polymorphism at the ovine DQA1 locus. D. nodosus present on 20 footrot infected sheep from the same flock were genotyped, together with the ovine DQA1 and DQA2 genotypes of their hosts. Preliminary results showed that sheep with the same DQA1 and DQA2 genotypes tended to be infected by similar types of D. nodosus. Different types of D. nodosus were generally found on sheep with different genotypes at either the DQA1 or the DQA2 locus. This suggests the diversity in D. nodosus infection may be associated with the heterogeneity in the host MHC. However, as only a small number of animals from the same sire were analysed, further investigation is needed to gain a better understanding of the interaction between D. nodosus and the host MHC.

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Gannett, Lisa Anne. „Genetic variation, difference, deviation, or deviance?“ Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0023/NQ31121.pdf.

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Lindroos, Katarina. „Accessing Genetic Variation by Microarray Technology“. Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2002. http://publications.uu.se/theses/91-554-5251-5/.

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Bücher zum Thema "Genetic variation"

1

Barnes, Michael R., und Gerome Breen, Hrsg. Genetic Variation. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60327-367-1.

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Walker, Tina Kay. Genetic variation in schistosomes. Uxbridge: Brunel University, 1987.

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ll, Torbjo rn Sa. Genetic variation for recombination in barley. Svalo v: Swedish University of Agricultural Sciences, Dept. of Crop Genetics and Breeding, 1989.

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L, Mahoney Conner, und Springer Douglas A, Hrsg. Genetic diversity. Hauppauge, NY: Nova Science Publishers, 2009.

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Amaya, Julian A. Cervantes, und Miguel M. Franco Jimenez. Genetic diversity: New research. Hauppauge, N.Y: Nova Science Publisher's, Inc., 2011.

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1933-, Simopoulos Artemis P., Nestel P. J und International Conference on Genetic Variation and Nutrition (1989 : Washington, D.C.), Hrsg. Genetic variation and dietary response. Basel: Karger, 1997.

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1954-, Prescott John, und Tepper Beverly J, Hrsg. Genetic variation in taste sensitivity. New York: Marcel Dekker, Inc., 2004.

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1958-, Weiner Michael P., Gabriel Stacey und Stephens J. Claiborne, Hrsg. Genetic variation: A laboratory manual. Cold Spring Harbor, N.Y: Cold Spring Harbor Laboratory Press, 2007.

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W, Konigsberg Lyle, und Relethford John, Hrsg. Human biological variation. New York: Oxford University Press, 2006.

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W, Konigsberg Lyle, und Relethford John, Hrsg. Human biological variation. 2. Aufl. New York: Oxford University Press, 2011.

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Buchteile zum Thema "Genetic variation"

1

Andrews, John H. „Genetic Variation“. In Brock/Springer Series in Contemporary Bioscience, 18–62. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3074-8_2.

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Ritu und Bhagyalaxmi Mohapatra. „Genetic Variation“. In Encyclopedia of Animal Cognition and Behavior, 1–6. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-47829-6_20-1.

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Ritu und Bhagyalaxmi Mohapatra. „Genetic Variation“. In Encyclopedia of Animal Cognition and Behavior, 2913–18. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_20.

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Andrews, John H. „Genetic Variation“. In Comparative Ecology of Microorganisms and Macroorganisms, 25–68. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6897-8_2.

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Twfieg, Mohammed-Elfatih, und M. Dawn Teare. „Molecular Genetics and Genetic Variation“. In Methods in Molecular Biology, 3–12. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60327-416-6_1.

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Neale, David B., und Nicholas C. Wheeler. „Adaptive Genetic Variation“. In The Conifers: Genomes, Variation and Evolution, 225–54. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-46807-5_10.

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Neale, David B., und Nicholas C. Wheeler. „Neutral Genetic Variation“. In The Conifers: Genomes, Variation and Evolution, 181–224. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-46807-5_9.

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Schanfield, Moses S., Dragan Primorac und Damir Marjanović. „Basic Genetics and Human Genetic Variation“. In Forensic DNA Applications, 3–44. 2. Aufl. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.4324/9780429019944-2.

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Simm, Geoff, Geoff Pollott, Raphael Mrode, Ross Houston und Karen Marshall. „Genes, genetic codes and genetic variation.“ In Genetic improvement of farmed animals, 11–58. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789241723.0011.

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Princée, F. P. G. „Genetic Variation and Generations“. In Topics in Biodiversity and Conservation, 171–78. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50032-4_12.

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Konferenzberichte zum Thema "Genetic variation"

1

„Genetic linkage to explain genetic variation“. In 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.a4.mijangos.

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Vafaee, Fatemeh, Gyorgy Turan, Peter C. Nelson und Tanya Y. Berger-Wolf. „Among-site rate variation“. In GECCO '14: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2576768.2598216.

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Wei, Pan, Yan Mingming, Tan Yuejun und Xie Huixiang. „Micro Variation Chaos Genetic Algorithm“. In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407913.

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Cox, David R. „The human genetic variation (abstract)“. In the second annual international conference. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/279069.279088.

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La Cava, William, und Jason H. Moore. „Semantic variation operators for multidimensional genetic programming“. In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3321707.3321776.

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Hudson, Tom. „“Genetic variation and cancer”“. In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4649062.

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Cervantes, Jorge, und Christopher Rhodes Stephens. „Rank based variation operators for genetic algorithms“. In the 10th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1389095.1389271.

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Alqallaf, Abdullah K., Ahmed H. Tewfik und Scott B. Selleck. „Genetic variation detection using maximum likelihood estimator“. In 2009 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS). IEEE, 2009. http://dx.doi.org/10.1109/gensips.2009.5174365.

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Kidd, Kenneth K. „Abstract ED04-03: Genetic variation among populations“. In Abstracts: AACR International Conference on the Science of Cancer Health Disparities‐‐ Sep 18-Sep 21, 2011; Washington, DC. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/1055-9965.disp-11-ed04-03.

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Bujny, Mariusz, Nikola Aulig, Markus Olhofer und Fabian Duddeck. „Learning-based topology variation in evolutionary level set topology optimization“. In GECCO '18: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3205455.3205528.

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Berichte der Organisationen zum Thema "Genetic variation"

1

Van Haverbeke, David F., und Rudy M. King. Genetic variation in Great Plains Juniperus. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, 1990. http://dx.doi.org/10.2737/rm-rp-292.

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2

Kammenga, J. E. Hidden genetic variation : From recognition to acknowledgement of genetic individuality. Wageningen: Wageningen University & Research, 2016. http://dx.doi.org/10.18174/409705.

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3

Phipps, Troy J. SRD5A1 Genetic Variation and Prostate Cancer Epidemiology. Fort Belvoir, VA: Defense Technical Information Center, Mai 2005. http://dx.doi.org/10.21236/ada441326.

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4

Ayala, F. J. Genetic variation in resistance to ionizing radiation. Office of Scientific and Technical Information (OSTI), Januar 1989. http://dx.doi.org/10.2172/6331129.

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5

Phipps, Troy J. SRD5A1 Genetic Variation and Prostate Cancer Epidemiology. Fort Belvoir, VA: Defense Technical Information Center, Mai 2004. http://dx.doi.org/10.21236/ada428280.

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6

Ayala, F. Genetic variation in resistance to ionizing radiation. Office of Scientific and Technical Information (OSTI), Juni 1991. http://dx.doi.org/10.2172/5696596.

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7

Ayala, F. Genetic variation in resistance to ionizing radiation. Office of Scientific and Technical Information (OSTI), Januar 1990. http://dx.doi.org/10.2172/5597533.

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8

Ayala, F. Genetic variation in resistance to ionizing radiation. Office of Scientific and Technical Information (OSTI), Januar 1992. http://dx.doi.org/10.2172/7368758.

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9

Zephyr, Yvelande, und Susan Walsh. Exploring Genetic Variation in a Caffeine Amplification Gene. Genetics Society of America Peer-Reviewed Education Portal (GSA PREP), März 2015. http://dx.doi.org/10.1534/gsaprep.2015.001.

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10

Zhang, Shu, Travis Knight, Jennifer Minick, Richard G. Tait, Allen H. Trenkle, Doyle E. Wilson, Gene H. Rouse, Daryl R. Strohbehn, James M. Reecy und Donald C. Beitz. Association of Genetic Variation to Healthfulness of Beef. Ames (Iowa): Iowa State University, Januar 2005. http://dx.doi.org/10.31274/ans_air-180814-1370.

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