Academic literature on the topic 'Haplotype analysi'
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Journal articles on the topic "Haplotype analysi"
Kesik, Harun Kaya, Figen Celik, Seyma Gunyakti Kilinc, Sami Simsek, Haroon Ahmed, Yujuan Shen, and Jianping Cao. "Genetic Diversity and Haplotype Analysis of Cattle Hydatid Cyst Isolates Using Mitochondrial Markers in Turkey." Pathogens 11, no. 5 (April 28, 2022): 519. http://dx.doi.org/10.3390/pathogens11050519.
Full textEpifanio, John M., Bonnie L. Brown, Peter E. Smouse, and Carol J. Kobak. "Mitochondrial DNA divergence among popylations of American shad (Alosa sapidissima): how much variation is enough for mixed-stock analysis?" Canadian Journal of Fisheries and Aquatic Sciences 52, no. 8 (August 1, 1995): 1688–702. http://dx.doi.org/10.1139/f95-761.
Full textSantos, Daniel Wagner C. L., Vania Aparecida Vicente, Vinicius Almir Weiss, G. Sybren de Hoog, Renata R. Gomes, Edith M. M. Batista, Sirlei Garcia Marques, Flávio de Queiroz-Telles, Arnaldo Lopes Colombo, and Conceição de Maria Pedrozo e. Silva de Azevedo. "Chromoblastomycosis in an Endemic Area of Brazil: A Clinical-Epidemiological Analysis and a Worldwide Haplotype Network." Journal of Fungi 6, no. 4 (October 3, 2020): 204. http://dx.doi.org/10.3390/jof6040204.
Full textKaul, Noyonika, Prem Lal Kashyap, Sudheer Kumar, Deepti Singh, and Gyanendra Pratap Singh. "Genetic Diversity and Population Structure of Head Blight Disease Causing Fungus Fusarium graminearum in Northern Wheat Belt of India." Journal of Fungi 8, no. 8 (August 5, 2022): 820. http://dx.doi.org/10.3390/jof8080820.
Full textBhattacharyya, Nitai Pada, Priyadarshi Basu, Madhusudan Das, Srimanta Pramanik, Rajat Banerjee, Bidyut Roy, Susanta Roychoudhury, and Partha P. Majumder. "Negligible Male Gene Flow Across Ethnic Boundaries in India, Revealed by Analysis of Y-Chromosomal DNA Polymorphisms." Genome Research 9, no. 8 (August 1, 1999): 711–19. http://dx.doi.org/10.1101/gr.9.8.711.
Full textVathipadiekal, Vinod, Abdulrahman Alsultan, John Farrell, A. M. Al-Rubaish, Fahad Al-Muhanna, Z. Naserullah, A. Alsuliman, et al. "Polymorphisms Associated with the Arab-Indian Haplotype of Sickle Cell Anemia Are Candidate Fetal Hemoglobin Gene Modulators." Blood 126, no. 23 (December 3, 2015): 3388. http://dx.doi.org/10.1182/blood.v126.23.3388.3388.
Full textTjensvoll, Kjersti, Ove Bruland, Ylva Floderus, Øyvind Skadberg, Sverre Sandberg, and Jaran Apold. "Haplotype Analysis of Norwegian and Swedish Patients with Acute Intermittent Porphyria (AIP): Extreme Haplotype Heterogeneity for the Mutation R116W." Disease Markers 19, no. 1 (2003): 41–46. http://dx.doi.org/10.1155/2003/384971.
Full textTAN, QIHUA, LENE CHRISTIANSEN, KAARE CHRISTENSEN, LISE BATHUM, SHUXIA LI, JING HUA ZHAO, and TORBEN A. KRUSE. "Haplotype association analysis of human disease traits using genotype data of unrelated individuals." Genetical Research 86, no. 3 (November 25, 2005): 223–31. http://dx.doi.org/10.1017/s0016672305007792.
Full textAnantaphruti, Malinee, Urusa Thaenkham, Teera Kusolsuk, Wanna Maipanich, Surapol Saguankiat, Somjit Pubampen, and Orawan Phuphisut. "Genetic Variation and Population Genetics ofTaenia saginatain North and Northeast Thailand in relation toTaenia asiatica." Journal of Parasitology Research 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/310605.
Full textPae, C. U. "Association Analysis of Heat Shock Protein 70 Gene Polymorphisms in Schizophrenia." European Psychiatry 24, S1 (January 2009): 1. http://dx.doi.org/10.1016/s0924-9338(09)71415-4.
Full textDissertations / Theses on the topic "Haplotype analysi"
Waldron, Edward. "Analysis of genetic association studies via haplotype clustering." Thesis, Imperial College London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497253.
Full textTai, Bik-wah Diana, and 戴碧華. "Haplotype analysis of the family with Lynch syndrome." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45153772.
Full textYatskiv, Yuriy Romanovich. "A Haplotype Analysis of an Archaic Denisovan Genome." University of Toledo Health Science Campus / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=mco1481145733356233.
Full textZhao, Jiantao. "Combining Association and Haplotype Studies Towards the Improvement of Fruit Quality in Tomato Multiple haplotype-based analyses provide genetic and evolutionary insights into tomato fruit weight and composition Meta-analysis of genome-wide association studies provides insights into genetic control of tomato flavor Genomic designing for climate smart tomato." Thesis, Avignon, 2019. http://www.theses.fr/2019AVIG0712.
Full textConsumers have been complaining about tomato flavor for decades. Tomato taste is mainly influenced by sugars, acids and a diverse set of volatiles. Improving tomato flavor remains one of the main challenges for improving tomato sensory quality and consumer acceptability in modern tomato breeding. The main purpose of this thesis was to decipher the genetic and evolutionary control of tomato flavor by using high density SNPs and a diverse set of flavor-related metabolites, including sugars, acids, amino acids and volatiles. In the first part, I performed multiple haplotype-based analyses on a tomato core collection. Several approaches were used and compared to identify the genomic regions under selection. Haplotype and SNP-based Bayesian models identified 108 significant associations for 26 traits. Among these associations, some promising candidate genes were identified. I also compared marker local haplotype sharing (mLHS) with LD in determining the candidate regions. In addition, some general benefits of using haplotypes were also provided as general discussions. In the second part, I pioneered in introducing meta-analysis of genome-wide association studies using three tomato association panels. I demonstrated the efficiency of genotype imputation in increasing the genome-wide SNP coverage. Both fixed-effect and random-effect models (for those SNPs with heterogeneity I2 > 25) of meta-analysis were performed in order to control cross-study heterogeneity. A total of 305 significant loci were identified and 211 of which were new. Among them, 24 loci exhibited cis-eQTLs in a previous transcriptome-wide association study in fruit tissue. Enrichment analysis for all associations showed that up to 10 biological processes were significantly enriched and all of which were closely involved in flavor-related metabolites. A list of promising candidate genes was provided, which could be of great interest for functional validation. I also demonstrated the possibility to significantly increase the content of volatiles that positively contribute to consumer preferences while reducing unpleasant volatiles, by selection of the relevant allele combinations. Taken together, this thesis provides a comprehensive knowledge of the genetic control of tomato flavor, which will promote its improvement
Lächelt, Sandra [Verfasser]. "Funktionelle Analyse von ABCC2-Haplotypen / Sandra Lächelt." Kiel : Universitätsbibliothek Kiel, 2009. http://d-nb.info/1019869933/34.
Full textHughes, David J. "Mutation characterisation and microsatellite haplotype analysis of the CFTR gene." Thesis, Queen's University Belfast, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361278.
Full textOsman, Abdimajid. "Studies on warfarin treatment with emphasis on inter-individual variations and drug monitoring." Doctoral thesis, Linköping : Linköping University, 2007. http://www.bibl.liu.se/liupubl/disp/disp2007/med1000s.pdf.
Full textROSA, Rogério dos Santos. "Associating genotype sequence properties to haplotype inference errors." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/16011.
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Haplotype information has a central role in the understanding and diagnosis of certain illnesses, and also for evolution studies. Since that type of information is hard to obtain directly, computational methods to infer haplotype from genotype data have received great attention from the computational biology community. Unfortunately, haplotype inference is a very hard computational biology problem and the existing methods can only partially identify correct solutions. I present neural network models that use different properties of the data to predict when a method is more prone to make errors. I construct models for three different Haplotype Inference approaches and I show that our models are accurate and statistically relevant. The results of our experiments offer valuable insights on the performance of those methods, opening opportunity for a combination of strategies or improvement of individual approaches. I formally demonstrate that Linkage Disequilibrium (LD) and heterozygosity are very strong indicators of Switch Error tendency for four methods studied, and I delineate scenarios based on LD measures, that reveal a higher or smaller propension of the HI methods to present inference errors, so the correlation between LD and the occurrence of errors varies among regions along the genotypes. I present evidence that considering windows of length 10, immediately to the left of a SNP (upstream region), and eliminating the non-informative SNPs through Fisher’s Test leads to a more suitable correlation between LD and Inference Errors. I apply Multiple Linear Regression to explore the relevance of several biologically meaningful properties of the genotype sequences for the accuracy of the haplotype inference results, developing models for two databases (considering only Humans) and using two error metrics. The accuracy of our results and the stability of our proposed models are supported by statistical evidence.
Haplótipos têm um papel central na compreensão e diagnóstico de determinadas doenças e também para estudos de evolução. Este tipo de informação é difícil de obter diretamente, diante disto, métodos computacionais para inferir haplótipos a partir de dados genotípicos têm recebido grande atenção da comunidade de biologia computacional. Infelizmente, a Inferência de Halótipos é um problema difícil e os métodos existentes só podem predizer parcialmente soluções corretas. Foram desenvolvidos modelos de redes neurais que utilizam diferentes propriedades dos dados para prever quando um método é mais propenso a cometer erros. Foram calibrados modelos para três abordagens de Inferência de Haplótipos diferentes e os resultados validados estatisticamente. Os resultados dos experimentos oferecem informações valiosas sobre o desempenho e comportamento desses métodos, gerando condições para o desenvolvimento de estratégias de combinação de diferentes soluções ou melhoria das abordagens individuais. Foi demonstrado que Desequilíbrio de Ligação (LD) e heterozigosidade são fortes indicadores de tendência de erro, desta forma foram delineados cenários com base em medidas de LD, que revelam quando um método tem maior ou menor propensão de cometer erros. Foi identificado que utilizando janelas de 10 SNPs (polimorfismo de um único nucleotídeo), imediatamente a montante, e eliminando os SNPs não informativos pelo Teste de Fisher leva-se a uma correlação mais adequada entre LD e a ocorrência de erros. Por fim, foi aplicada análise de Regressão Linear para explorar a relevância de várias propriedades biologicamente significativas das sequências de genótipos para a precisão dos resultados de Inferência de Haplótipos, estimou-se modelos para duas bases de dados (considerando apenas humanos) utilizando duas métricas de erro. A precisão dos resultados e a estabilidade dos modelos propostos foram validadas por testes estatísticos.
Nettelblad, Carl. "Two Optimization Problems in Genetics : Multi-dimensional QTL Analysis and Haplotype Inference." Doctoral thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-180920.
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Neville, Catherine E. "The high resolution haplotype analysis and origin of the myotonic dystrophy mutation." Thesis, University of Ottawa (Canada), 1994. http://hdl.handle.net/10393/9857.
Full textBooks on the topic "Haplotype analysi"
Pound, Michelle C. Deletion screening and haplotype analysis in the Fraxe region at Xq28. [Portsmouth]: [University of Portsmouth], 2000.
Find full textSorin, Istrail, Waterman Michael S, and Clark Andrew G. 1954-, eds. Computational methods for SNPs and Haplotype inference: DIMACS/RECOMB satellite workshop, Piscataway, NJ, USA, November 21-22, 2002 : revised papers. Berlin: Springer-Verlag, 2004.
Find full textMészáros, Gábor, Marco Milanesi, Paolo Ajmone Marsan, and Yuri Tani Utsunomiya, eds. Haplotype Analysis Applied to Livestock Genomics. Frontiers Media SA, 2021. http://dx.doi.org/10.3389/978-2-88966-968-4.
Full textWaterman, Michael, Clark Andrew, and Sorin Istrail. Computational Methods for SNPs and Haplotype Inference: DIMACS/RECOMB Satellite Workshop, Piscataway, NJ, USA, November 21-22, 2002, Revised Papers. Springer London, Limited, 2004.
Find full textCrawford, Michael, and Rohina C. Rubicz. Molecular Genetic Evidence from Contemporary Populations for the Origins of Native North Americans. Edited by Max Friesen and Owen Mason. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199766956.013.4.
Full textLewis, Myles, and Tim Vyse. Genetics of connective tissue diseases. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0042.
Full textBook chapters on the topic "Haplotype analysi"
Martin, Marcel, Peter Ebert, and Tobias Marschall. "Read-Based Phasing and Analysis of Phased Variants with WhatsHap." In Methods in Molecular Biology, 127–38. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2819-5_8.
Full textDelaneau, Olivier, and Jean-François Zagury. "Haplotype Inference." In Data Production and Analysis in Population Genomics, 177–96. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-870-2_11.
Full textEpstein, Michael P., and Lydia C. Kwee. "Haplotype Association Analysis." In Handbook on Analyzing Human Genetic Data, 241–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-69264-5_8.
Full textStram, Daniel O. "Haplotype Imputation for Association Analysis." In Design, Analysis, and Interpretation of Genome-Wide Association Scans, 183–211. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9443-0_5.
Full textWetmur, James G., and Jia Chen. "Linking Emulsion PCR Haplotype Analysis." In Methods in Molecular Biology, 165–75. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-944-4_11.
Full textZheng, Gang, Yaning Yang, Xiaofeng Zhu, and Robert C. Elston. "Haplotype Analysis for Case-Control Data." In Analysis of Genetic Association Studies, 209–33. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-2245-7_7.
Full textGraça, Ana, João Marques-Silva, and Inês Lynce. "Haplotype Inference Using Propositional Satisfiability." In Mathematical Approaches to Polymer Sequence Analysis and Related Problems, 127–47. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6800-5_7.
Full textRoeder, Kathryn. "Evolutionary-Based Association Analysis Using Haplotype Data." In Computational Methods for SNPs and Haplotype Inference, 144. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24719-7_24.
Full textStram, Daniel O., and Venkatraman E. Seshan. "Multi-SNP Haplotype Analysis Methods for Association Analysis." In Methods in Molecular Biology, 423–52. Totowa, NJ: Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-555-8_23.
Full textStram, Daniel O. "Multi-SNP Haplotype Analysis Methods for Association Analysis." In Methods in Molecular Biology, 485–504. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7274-6_24.
Full textConference papers on the topic "Haplotype analysi"
Lin, Shili, and Terence P. Speed. "An algorithm for haplotype analysis." In the first annual international conference. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/267521.267548.
Full textTejera, P., Z. Wang, R. Zhai, L. Su, CC Sheu, and DC Christiani. "Functional Analysis of Haplotypes inPI3Promoter." In American Thoracic Society 2009 International Conference, May 15-20, 2009 • San Diego, California. American Thoracic Society, 2009. http://dx.doi.org/10.1164/ajrccm-conference.2009.179.1_meetingabstracts.a1884.
Full textSadovnychenko, Iurii, and Nataliia Pastukhova. "Open data of molecular genetic research through the prism of global trends." In First International Conference "Open Science and Innovation in Ukraine 2022". State Scientific and Technical Library of Ukraine, 2022. http://dx.doi.org/10.35668/978-966-479-129-5-7-18.
Full textProkhorova, E. E., and R. R. Usmanova. "GENETIC POLYMORPHISM OF SNAILS SUCCINEA PUTRIS (GASTROPODA, PULMONATA)." In V International Scientific Conference CONCEPTUAL AND APPLIED ASPECTS OF INVERTEBRATE SCIENTIFIC RESEARCH AND BIOLOGICAL EDUCATION. Tomsk State University Press, 2020. http://dx.doi.org/10.17223/978-5-94621-931-0-2020-33.
Full textUddin, Mohammed, Mitch Sturge, Courtenay Griffin, Steve Benteau, and Proton Rahman. "Variability of haplotype phase and its effect on genetic analysis." In 2008 Canadian Conference on Electrical and Computer Engineering - CCECE. IEEE, 2008. http://dx.doi.org/10.1109/ccece.2008.4564604.
Full textKHRABROVA, Lyudmila A., Alexander M. ZAITSEV, Larisa L. VIKULOVA, Marina V. ADAMKOVSKAYA, Nina V. BLOKHINA, and Sergey I. SOROKIN. "MtDNA Haplotype Analysis in Dam Families of the Thoroughbred Riding Horses." In XVIII International Scientific and Practical Conference "Modern Trends in Agricultural Production in the World Economy". Sibac, 2020. http://dx.doi.org/10.32743/kuz.agri.2020.34-42.
Full text"Haplotype Block Analysis of FSHR Gene in Sragen and Jabres Cattle." In Technology Innovations and Collaborations in Livestock Production for Sustainable Food Systems. IAARD Press, 2021. http://dx.doi.org/10.14334/proc.intsem.lpvt-2021-p.16.
Full textNG, MICHAEL K., ERIC S. FUNG, WAI-KI CHING, and YIU-FAI LEE. "A RECURSIVE METHOD FOR SOLVING HAPLOTYPE FREQUENCIES IN MULTIPLE LOCI LINKAGE ANALYSIS." In 4th Asia-Pacific Bioinformatics Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2005. http://dx.doi.org/10.1142/9781860947292_0016.
Full textKarkar, S., A. Gloaguen, Y. Le Guen, M. Pierre-Jean, C. Dandine-Roulland, E. Le Floch, C. Philippe, A. Tenenhaus, and V. Frouin. "Multivariate Haplotype Analysis Of 96 Sulci Opening For 15,612 UK-Biobank Sujects." In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI). IEEE, 2019. http://dx.doi.org/10.1109/isbi.2019.8759497.
Full textDevatha Venkatesh, Sowmya, Mathew Varghese, Ravi Yadav, Sanjeev Jain, and Meera Purushottam. "C10 Haplotype structure analysis of Indian Huntington’s disease patients at HTT gene locus." In EHDN 2022 Plenary Meeting, Bologna, Italy, Abstracts. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/jnnp-2022-ehdn.54.
Full textReports on the topic "Haplotype analysi"
Roecklein, Kathryn A. Haplotype Analysis of the Melanopsin Gene in Seasonal Affective Disorder and Controls. Fort Belvoir, VA: Defense Technical Information Center, May 2007. http://dx.doi.org/10.21236/ad1014058.
Full textMichelmore, Richard, Eviatar Nevo, Abraham Korol, and Tzion Fahima. Genetic Diversity at Resistance Gene Clusters in Wild Populations of Lactuca. United States Department of Agriculture, February 2000. http://dx.doi.org/10.32747/2000.7573075.bard.
Full textSherman, Amir, Rebecca Grumet, Ron Ophir, Nurit Katzir, and Yiqun Weng. Whole genome approach for genetic analysis in cucumber: Fruit size as a test case. United States Department of Agriculture, December 2013. http://dx.doi.org/10.32747/2013.7594399.bard.
Full textFahima, Tzion, and Jorge Dubcovsky. Map-based cloning of the novel stripe rust resistance gene YrG303 and its use to engineer 1B chromosome with multiple beneficial traits. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598147.bard.
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