Academic literature on the topic 'Ancestry prediction'
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Journal articles on the topic "Ancestry prediction"
Oldoni, Fabio, Rebecca Hart, Kelly Long, Kathrina Maddela, Selena Cisana, Moses Schanfield, Sharon Wootton, et al. "Microhaplotypes for ancestry prediction." Forensic Science International: Genetics Supplement Series 6 (December 2017): e513-e515. http://dx.doi.org/10.1016/j.fsigss.2017.09.209.
Full textC, Omuruka T., Osunwoke Osunwoke, E. A, Edibamode Edibamode, and E. I. "Palmar Creases and Ancestry Prediction." Scholars International Journal of Anatomy and Physiology 5, no. 2 (February 16, 2022): 41–49. http://dx.doi.org/10.36348/sijap.2022.v05i02.003.
Full textMoshkov, Nikita, Aleksandr Smetanin, and Tatiana V. Tatarinova. "Local ancestry prediction with PyLAE." PeerJ 9 (December 14, 2021): e12502. http://dx.doi.org/10.7717/peerj.12502.
Full textLippert, Christoph, Riccardo Sabatini, M. Cyrus Maher, Eun Yong Kang, Seunghak Lee, Okan Arikan, Alena Harley, et al. "Identification of individuals by trait prediction using whole-genome sequencing data." Proceedings of the National Academy of Sciences 114, no. 38 (September 5, 2017): 10166–71. http://dx.doi.org/10.1073/pnas.1711125114.
Full textBitarello, Bárbara D., and Iain Mathieson. "Polygenic Scores for Height in Admixed Populations." G3: Genes|Genomes|Genetics 10, no. 11 (September 2, 2020): 4027–36. http://dx.doi.org/10.1534/g3.120.401658.
Full textCheung, Elaine Y. Y., Michelle Elizabeth Gahan, and Dennis McNevin. "Prediction of biogeographical ancestry in admixed individuals." Forensic Science International: Genetics 36 (September 2018): 104–11. http://dx.doi.org/10.1016/j.fsigen.2018.06.013.
Full textJin, Xiao-Ye, Yu-Xin Guo, Chong Chen, Wei Cui, Yan-Fang Liu, Yun-Chun Tai, and Bo-Feng Zhu. "Ancestry Prediction Comparisons of Different AISNPs for Five Continental Populations and Population Structure Dissection of the Xinjiang Hui Group via a Self-Developed Panel." Genes 11, no. 5 (May 4, 2020): 505. http://dx.doi.org/10.3390/genes11050505.
Full textSzeniczey, Tamás. "A nazomaláris szög és szimotikus húr alkalmazása metrikus alapú taxonómiai osztályozási feladatokban." Anthropologiai Közlemények 61 (2020): 53–62. http://dx.doi.org/10.20330/anthropkozl.2020.61.53.
Full textButler, Katherine, Michelle Peck, Jessica Hart, Moses Schanfield, and Daniele Podini. "Molecular “eyewitness”: Forensic prediction of phenotype and ancestry." Forensic Science International: Genetics Supplement Series 3, no. 1 (December 2011): e498-e499. http://dx.doi.org/10.1016/j.fsigss.2011.09.109.
Full textMukadam, Naaheed, Olga Giannakopoulou, Nick Bass, Karoline Kuchenbaecker, and Andrew McQuillin. "Genetic risk scores and dementia risk across different ethnic groups in UK Biobank." PLOS ONE 17, no. 12 (December 7, 2022): e0277378. http://dx.doi.org/10.1371/journal.pone.0277378.
Full textDissertations / Theses on the topic "Ancestry prediction"
Allocco, Dominic. "Use of machine learning techniques for SNP based prediction of ancestry." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/35550.
Full textIncludes bibliographical references (leaves 29-30).
Some have argued that the genetic differences between continentally defined groups are relatively small and unlikely to have biomedical significance. In this study, the extent of variation between continentally defined groups was evaluated. Small numbers of randomly selected single nucleotide polymorphisms from the International HapMap Project were used to train classifiers for prediction of ancestral continent of origin. Predictive accuracy was then tested on independent data sets. A high degree of genetic similarity implies that groups will be difficult to distinguish, especially when only a limited amount of genetic information is used. It is shown that the genetic differences between continentally defined groups are sufficiently large that one can accurately predict ancestral continent of origin using only a minute, randomly selected fraction of the genetic variation present in the human genome. Genotype data from only 50 random single nucleotide polymorphisms can be used to predict ancestral continent of origin in the primary test data set with an average accuracy of 95%.
(cont.) Single nucleotide polymorphisms were also characterized as being in introns, coding exons, regulatory regions and regions coding for untranslated mRNA and classifiers constructed using only single nucleotide polymorphisms from a specific category. Predictive accuracy was similar across all of the classifiers created in this manner. Single nucleotide polymorphisms useful for prediction of ancestral continent of origin are common and distributed relatively evenly throughout the genome. These findings demonstrate the extent of variation between continentally defined groups and argue strongly against the contention that genetic differences between groups are too small to have biomedical significance.
by Dominic J. Allocco.
S.M.
James, Kyle. "DNA-MAP, a knowledge-based decision support system for Australian Defence Force forensic ancestry prediction." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/213211/1/Kyle_James_Thesis.pdf.
Full textGhaiyed, Andrew Peter. "A genomic ancestry panel for Australian and Japanese WWII military remains recovered in the Asia-Pacific." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/211296/1/Andrew_Ghaiyed_Thesis.pdf.
Full textJosey, Michelle. "Molecular-Genetic Methods for Predicting Bio-Geographical Ancestry From Bone Specimens to Aid in Forensic Identification." Honors in the Major Thesis, University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1036.
Full textBachelors
Sciences
Forensic Science
Alkindy, Bassam. "Combining approaches for predicting genomic evolution." Thesis, Besançon, 2015. http://www.theses.fr/2015BESA2012/document.
Full textIn Bioinformatics, understanding how DNA molecules have evolved over time remains an open and complex problem.Algorithms have been proposed to solve this problem, but they are limited either to the evolution of a given character (forexample, a specific nucleotide), or conversely focus on large nuclear genomes (several billion base pairs ), the latter havingknown multiple recombination events - the problem is NP complete when you consider the set of all possible operationson these sequences, no solution exists at present. In this thesis, we tackle the problem of reconstruction of ancestral DNAsequences by focusing on the nucleotide chains of intermediate size, and have experienced relatively little recombinationover time: chloroplast genomes. We show that at this level the problem of the reconstruction of ancestors can be resolved,even when you consider the set of all complete chloroplast genomes currently available. We focus specifically on the orderand ancestral gene content, as well as the technical problems this raises reconstruction in the case of chloroplasts. Weshow how to obtain a prediction of the coding sequences of a quality such as to allow said reconstruction and how toobtain a phylogenetic tree in agreement with the largest number of genes, on which we can then support our back in time- the latter being finalized. These methods, combining the use of tools already available (the quality of which has beenassessed) in high performance computing, artificial intelligence and bio-statistics were applied to a collection of more than450 chloroplast genomes
Leneuve, Dorilas Malika. "Les facteurs de risque de la naissance prématurée en Guyane Française Rosk factors for premature birth in French Guiana: the importance of reducing health inegalities Predictive factors of preterms delivery in French Guiana for singleton pregnancies: definition and validation of a predictive score Risk Factors for Very Preterm Births in French Guiana : The Burden of Induced Preterm Birth African ancestry and the threshold defining preterm delivery: in French Guiana black babies born at 36 weeks are as vulnerable as white babies." Thesis, Guyane, 2019. http://www.theses.fr/2019YANE0003.
Full textContext and objective: French Guiana, an overseas department and region, has nearly 8,000 births per year.Since 1992, the proportion of premature births, although stable, has remained high at around 13.5%, almost double that of France (7%) (data from the Pregnancy Outcome Register and national perinatal survey). While in most countries we see an increase in prematurity, we could, wrongly, be satisfied with a non-increase in the prematurity rate that would reflect progress. However, deaths from perinatal causes remain one of the main causes of premature mortality in French Guiana and partly explain the gap with France in terms of life expectancy at birth.Given this lack of improvement in the prematurity rate, it seems important to better understand the factors that make prematurity so frequent and so difficult to control in French Guiana. The thesis focused on identifying the predictive factors of prematurity with the ultimate aim of contributing to improving the care of pregnant women and curbing the curve of the prematurity rate. Methodology: This research work is divided into 4 areas of investigation:- A descriptive retrospective study, based on data from the RIGI (Register of Computerized Pregnancy Outcomes) 2013-2014 of 12,983 viable births in the department,- The development of a predictive prematurity score from the 2013-2014 RIGI, compared to the 2015 RIGI data of 6,914 viable births,- A case-control etiological study of extreme prematurity, monocentric, from February 2016 to January 2017 in the only type III health-care institution in the French Guiana Region,- Analysis of the average term at birth and morbidity and mortality from the RIG (Register of Pregnancy Outcomes) 2002-2007 of 35,648 viable births and the RIGI 2013-2014.Results:Over the study period, the proportion of preterm births was 13.5% (1,755/12,983). The proportion of spontaneous prematurity was 51.3% , compared to 48.7% of induced prematurity. More than half (57.2% or 7 421/12 983) of the study population had social security, but 9.3% had no social security coverage. The lack of social security coverage was a risk factor for prematurity with an adjusted OR of 1.9 CI at 95% [1.6-2.3] p=0.0001. Similarly, with regard to pregnancy management, the absence of prenatal care as well as that of birth preparation would double the risk of premature birth. For pathologies associated with pregnancy, pre-eclampsia syndrome was the main dysgravidia associated with the risk of prematurity (OR adjusted by 6.7[95% CI =5.6-8.1] p=0.0001). Finally, the fairly common hypothesis that part of the high prematurity rate is related to the fact that black babies are more mature and black mothers give birth physiologically a little earlier did not emerge in our analyses. Indeed, there was no statistically significant difference in morbidity and mortality for infants born to Afro-Caribbean mothers and Caucasian women. Conclusion: The work carried out has identified many factors associated with prematurity, factors already described elsewhere. Although at the individual level it was impossible to predict who would give birth prematurely, the weight of social factors and poor follow-up suggested that a population-based approach might be appropriate. Thus, the most vulnerable women often reside in well-identified areas that could be the subject of targeted actions to improve follow-up and identify complications. This problem of social inequalities in health goes well beyond prematurity and is found for almost all pathologies, suggesting that there are synergies to be sought and that the population scale is undoubtedly strategic. The weight of preeclampsia as a risk factor for induced prematurity in French Guiana raises questions: indeed, it seems much more important than elsewhere for reasons that remain to be clarified
Bardan, Felicia. "New forensic DNA profiling techniques for human identification." Thesis, 2019. http://hdl.handle.net/2440/120161.
Full textThesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 2019
Austin, Ayda Aukahi. "Native Hawaiian risky behavior the role of individual, social, and cultural factors in predicting substance use and violence /." Thesis, 2004. http://proquest.umi.com/pqdweb?index=0&did=775179201&SrchMode=2&sid=3&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1233348956&clientId=23440.
Full textBooks on the topic "Ancestry prediction"
Frudakis, Tony Nick. Molecular photofitting: Predicting ancestry and phenotype using DNA. Amsterdam: Elsevier/Academic Press, 2008.
Find full textFrudakis, Tony Nick. Molecular photofitting: Predicting ancestry and phenotype using DNA. Amsterdam: Elsevier/Academic Press, 2008.
Find full textMolecular Photofitting: Predicting Ancestry and Phenotype Using DNA. Academic Press, 2007.
Find full textFrudakis, Tony. Molecular Photofitting: Predicting Ancestry and Phenotype Using DNA. Elsevier Science & Technology Books, 2010.
Find full textForces, With Ancestral, and Rebecca Rogerson. Language of the Heart: Ancestral Presences, Teachings and Predictions. Independently Published, 2022.
Find full textKay, Chris, Emily Fisher, and Michael R. Hayden. Epidemiology. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199929146.003.0007.
Full textVarella, Marco A. C., Jaroslava Varella Valentova, and Ana María Fernández. Evolution of Artistic and Aesthetic Propensities through Female Competitive Ornamentation. Edited by Maryanne L. Fisher. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199376377.013.46.
Full textBook chapters on the topic "Ancestry prediction"
Ouangraoua, Aïda, Frédéric Boyer, Andrew McPherson, Éric Tannier, and Cedric Chauve. "Prediction of Contiguous Regions in the Amniote Ancestral Genome." In Bioinformatics Research and Applications, 173–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01551-9_18.
Full textRoss, Connie M., Gabriel Foley, Mikael Boden, and Elizabeth M. J. Gillam. "Using the Evolutionary History of Proteins to Engineer Insertion-Deletion Mutants from Robust, Ancestral Templates Using Graphical Representation of Ancestral Sequence Predictions (GRASP)." In Methods in Molecular Biology, 85–110. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1826-4_6.
Full textWeiner, J. S., and Chris Stringer. "A Darwinian Prediction." In The Piltdown Forgery. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780198607809.003.0007.
Full text"On Predicting Hominid Group Sizes." In The Archaeology of Human Ancestry, 222–44. Routledge, 2005. http://dx.doi.org/10.4324/9780203974131-22.
Full textCutter, Asher D. "Genealogy in evolution." In A Primer of Molecular Population Genetics, 85–112. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838944.003.0005.
Full textMurray, Elisabeth A., Steven P. Wise, Mary K. L. Baldwin, and Kim S. Graham. "Beastly brains." In The Evolutionary Road to Human Memory, 38–53. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198828051.003.0003.
Full textGerard, Philip. "Glory Bound." In The Last Battleground, 29–33. University of North Carolina Press, 2019. http://dx.doi.org/10.5149/northcarolina/9781469649566.003.0006.
Full textWhitehouse, Harvey. "Imagistic Ritual, Fusion, and Self-Sacrifice." In The Ritual Animal, 82–105. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780199646364.003.0004.
Full textCutter, Asher D. "Molecular deviants." In A Primer of Molecular Population Genetics, 159–94. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838944.003.0008.
Full textConference papers on the topic "Ancestry prediction"
Jolley, Clarissa R., Hannah J. Lee, Kristen A. Lucas, and William P. McDevitt. "Short Tandem Repeat Analysis as a Novel Method for Biogeographic Ancestry Prediction." In 2022 Systems and Information Engineering Design Symposium (SIEDS). IEEE, 2022. http://dx.doi.org/10.1109/sieds55548.2022.9799365.
Full textFejerman, Laura. "Abstract IA12: Variation in genetic ancestry proportions among Latinos and its impact on cancer risk, prediction, and outcomes." In Abstracts: Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; September 25-28, 2016; Fort Lauderdale, FL. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7755.disp16-ia12.
Full textWang, S., F. Qian, Y. Zheng, T. Ogundiran, O. Ojengbede, W. Zheng, W. Blot, et al. "Abstract P5-09-02: Breast cancer risk prediction using a polygenic risk score in women of African ancestry: Findings from GWAS in breast cancer in the African diaspora." In Abstracts: 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, Texas. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.sabcs16-p5-09-02.
Full textToma, Tanjin, Tayo Olufemi-Ajayi, Jeremy Dawson, and Donald Adjeroh. "Random Subspace Projection for Predicting Biogeographical Ancestry." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621222.
Full textBaun, Ward O. "Method for the Early Development of a Bayesian Prior Time-to-Failure Distribution for an Evolutionary Product Design." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-41022.
Full textYang, Kuan, and Joao C. Setubal. "Homology prediction refinement and reconstruction of gene content and order of ancestral bacterial genomes." In the First ACM International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1854776.1854810.
Full textHasanova, Aytakin. "PREDICTIVE GENETIC SCREENING." In The First International Scientific-Practical Conference- “Modern Tendencies of Dialogue in Multidenominational Society: philosophical, religious, legal view”. IRETC MTÜ, 2020. http://dx.doi.org/10.36962/mtdms202029.
Full textOzturk, Utkudeniz, Jose Maria Cabrera, and Jessica Calvo. "A Physically Based Model for High Temperature Deformation of Inconel 718Plus™." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-64043.
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