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Statistical and computational genetics

Section edited by Rongling Wu

This section incorporates all aspects of statistical and computational genetics, including but not limited to: methods and applications for the analysis of all types of genetic data.

Page 2 of 2

  1. Content type: Software

    Risk prediction models capitalizing on genetic and environmental information hold great promise for individualized disease prediction and prevention. Nevertheless, linking the genetic and environmental risk pr...

    Authors: Chengyin Ye and Qing Lu

    Citation: BMC Genetics 2013 14:122

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  2. Content type: Methodology article

    MicroRNAs (miRNAs) regulate many biological processes by post-translational gene silencing. Analysis of miRNA expression profiles is a reliable method for investigating particular biological processes due to t...

    Authors: Bo Sun, Fei Yang, Fei-Hu Hu, Ning-Ping Huang and Zhong-Dang Xiao

    Citation: BMC Genetics 2013 14:120

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  3. Content type: Software

    Identification of true to breed type animal for conservation purpose is imperative. Breed dilution is one of the major problems in sustainability except cases of commercial crossbreeding under controlled condi...

    Authors: Mir Asif Iquebal, Sarika, Sandeep Kumar Dhanda, Vasu Arora, Sat Pal Dixit, Gajendra PS Raghava, Anil Rai and Dinesh Kumar

    Citation: BMC Genetics 2013 14:118

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  4. Content type: Methodology article

    The advent of genome-wide association studies has led to many novel disease-SNP associations, opening the door to focused study on their biological underpinnings. Because of the importance of analyzing these a...

    Authors: David M Swanson, Deborah Blacker, Taofik AlChawa, Kerstin U Ludwig, Elisabeth Mangold and Christoph Lange

    Citation: BMC Genetics 2013 14:108

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  5. Content type: Research article

    On thinking quantitatively of complex diseases, there are at least three statistical strategies for analyzing the gene-gene interaction: SNP by SNP interaction on single trait, gene-gene (each can involve mult...

    Authors: Fangyu Li, Jinghua Zhao, Zhongshang Yuan, Xiaoshuai Zhang, Jiadong Ji and Fuzhong Xue

    Citation: BMC Genetics 2013 14:89

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  6. Content type: Methodology article

    Pooling is a cost effective way to collect data for genetic association studies, particularly for rare genetic variants. It is of interest to estimate the haplotype frequencies, which contain more information ...

    Authors: Anthony YC Kuk, Xiang Li and Jinfeng Xu

    Citation: BMC Genetics 2013 14:82

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  7. Content type: Methodology article

    In cross breeding, it is important to choose a good parental combination that has high probability of generating offspring with desired characteristics. This study examines a method for predicting the segregat...

    Authors: Hiroyoshi Iwata, Takeshi Hayashi, Shingo Terakami, Norio Takada, Toshihiro Saito and Toshiya Yamamoto

    Citation: BMC Genetics 2013 14:81

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  8. Content type: Methodology article

    Triad families are routinely used to test association between genetic variants and complex diseases. Triad studies are important and popular since they are robust in terms of being less prone to false positive...

    Authors: Ruzong Fan, Annie Lee, Zhaohui Lu, Aiyi Liu, James F Troendle and James L Mills

    Citation: BMC Genetics 2013 14:78

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  9. Content type: Methodology article

    We address the task of extracting accurate haplotypes from genotype data of individuals of large F1 populations for mapping studies. While methods for inferring parental haplotype assignments on large F1 populati...

    Authors: Filippo Utro, Niina Haiminen, Donald Livingstone III, Omar E Cornejo, Stefan Royaert, Raymond J Schnell, Juan Carlos Motamayor, David N Kuhn and Parida Laxmi

    Citation: BMC Genetics 2013 14:48

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  10. Content type: Research article

    F2 resource populations have been used extensively to map QTL segregating between pig breeds. A limitation associated with the use of these resource populations for fine mapping of QTL is the reduced number of f....

    Authors: Jose L Gualdrón Duarte, Ronald O Bates, Catherine W Ernst, Nancy E Raney, Rodolfo JC Cantet and Juan P Steibel

    Citation: BMC Genetics 2013 14:38

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  11. Content type: Methodology article

    For genetic association studies in designs of unrelated individuals, current statistical methodology typically models the phenotype of interest as a function of the genotype and assumes a known statistical mod...

    Authors: Sharon Lutz, Wai-Ki Yip, John Hokanson, Nan Laird and Christoph Lange

    Citation: BMC Genetics 2013 14:13

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  12. Content type: Research article

    Recombination rates vary at the level of the species, population and individual. Now recognized as a transient feature of the genome, recombination rates at a given locus can change markedly over time. Existin...

    Authors: Murray P Cox, Barbara R Holland, Matthew C Wilkins and Jan Schmid

    Citation: BMC Genetics 2013 14:11

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  13. Content type: Research article

    Genotype imputation is a cost efficient alternative to use of high density genotypes for implementing genomic selection. The objective of this study was to investigate variables affecting imputation accuracy f...

    Authors: Yvonne M Badke, Ronald O Bates, Catherine W Ernst, Clint Schwab, Justin Fix, Curtis P Van Tassell and Juan P Steibel

    Citation: BMC Genetics 2013 14:8

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  14. Content type: Methodology article

    The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genoty...

    Authors: Rafael Izbicki, Victor Fossaluza, Ana Gabriela Hounie, Eduardo Yoshio Nakano and Carlos Alberto de Bragança Pereira

    Citation: BMC Genetics 2012 13:103

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  15. Content type: Correspondence

    Mathematical models of viral dynamics in vivo provide incredible insights into the mechanisms for the nonlinear interaction between virus and host cell populations, the dynamics of viral drug resistance, and the ...

    Authors: Wei Hou, Yihan Sui, Zhong Wang, Yaqun Wang, Ningtao Wang, Jingyuan Liu, Yao Li, Maureen Goodenow, Li Yin, Zuoheng Wang and Rongling Wu

    Citation: BMC Genetics 2012 13:91

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  16. Content type: Software

    Accurate genetic maps are the cornerstones of genetic discovery, but their construction can be hampered by missing parental genotype information. Inference of parental haplotypes and correction of phase errors...

    Authors: Zhiqiu Hu, Jeffrey D Ehlers, Philip A Roberts, Timothy J Close, Mitchell R Lucas, Steve Wanamaker and Shizhong Xu

    Citation: BMC Genetics 2012 13:9

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  17. Content type: Research article

    The advent of high throughput sequencing technology has enabled the 1000 Genomes Project Pilot 3 to generate complete sequence data for more than 906 genes and 8,140 exons representing 697 subjects. The 1000 G...

    Authors: Xinyi Cindy Zhang, Bo Zhang, Shuying Sue Li, Xin Huang, John A Hansen and Lue Ping Zhao

    Citation: BMC Genetics 2012 13:6

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  18. Content type: Methodology article

    Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and betwe...

    Authors: Maksim V Struchalin, Najaf Amin, Paul HC Eilers, Cornelia M van Duijn and Yurii S Aulchenko

    Citation: BMC Genetics 2012 13:4

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  19. Content type: Methodology article

    Genome-wide association studies (GWAS) aim to identify causal variants and genes for complex disease by independently testing a large number of SNP markers for disease association. Although genes have been imp...

    Authors: Sara Ballouz, Jason Y Liu, Martin Oti, Bruno Gaeta, Diane Fatkin, Melanie Bahlo and Merridee A Wouters

    Citation: BMC Genetics 2011 12:98

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  20. Content type: Methodology article

    In the study of associations between genomic data and complex phenotypes there may be relationships that are not amenable to parametric statistical modeling. Such associations have been investigated mainly usi...

    Authors: Daniel Gianola, Hayrettin Okut, Kent A Weigel and Guilherme JM Rosa

    Citation: BMC Genetics 2011 12:87

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  21. Content type: Research article

    In genetic association study, especially in GWAS, gene- or region-based methods have been more popular to detect the association between multiple SNPs and diseases (or traits). Kernel principal component analy...

    Authors: Qingsong Gao, Yungang He, Zhongshang Yuan, Jinghua Zhao, Bingbing Zhang and Fuzhong Xue

    Citation: BMC Genetics 2011 12:75

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  22. Content type: Methodology article

    Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects...

    Authors: Dörte Wittenburg, Nina Melzer and Norbert Reinsch

    Citation: BMC Genetics 2011 12:74

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  23. Content type: Methodology article

    Association studies consist in identifying the genetic variants which are related to a specific disease through the use of statistical multiple hypothesis testing or segregation analysis in pedigrees. This typ...

    Authors: Stefano Cabras, Maria Eugenia Castellanos, Ginevra Biino, Ivana Persico, Alessandro Sassu, Laura Casula, Stefano del Giacco, Francesco Bertolino, Mario Pirastu and Nicola Pirastu

    Citation: BMC Genetics 2011 12:63

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  24. Content type: Research article

    The use of DNA methods for the identification and management of natural resources is gaining importance. In the future, it is likely that DNA registers will play an increasing role in this development. Microsa...

    Authors: Øystein A Haaland, Kevin A Glover, Bjørghild B Seliussen and Hans J Skaug

    Citation: BMC Genetics 2011 12:36

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  25. Content type: Research article

    Most quantitative traits are controlled by multiple quantitative trait loci (QTL). The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome se...

    Authors: Zhiqiu Hu, Yongguang Li, Xiaohui Song, Yingpeng Han, Xiaodong Cai, Shizhong Xu and Wenbin Li

    Citation: BMC Genetics 2011 12:15

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