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  1. Monozygotic twin pairs who are genetically identical would be potentially useful in gene expression study for specific traits as cases and controls, because there would be much less gene expression variation w...

    Authors: Ying T Mak, Geeta Hampson, Jon N Beresford and Tim D Spector
    Citation: BMC Genetics 2004 5:14
  2. Drosophila mojavensis has been a model system for genetic studies of ecological adaptation and speciation. However, despite its use for over half a century, no linkage map has been produced for this species or it...

    Authors: Regina Staten, Sheri Dixon Schully and Mohamed AF Noor
    Citation: BMC Genetics 2004 5:12
  3. The adequacy of association studies for complex diseases depends critically on the existence of linkage disequilibrium (LD) between functional alleles and surrounding SNP markers.

    Authors: Ji-Rong Long, Lan-Juan Zhao, Peng-Yuan Liu, Yan Lu, Volodymyr Dvornyk, Hui Shen, Yong-Jun Liu, Yuan-Yuan Zhang, Dong-Hai Xiong, Peng Xiao and Hong-Wen Deng
    Citation: BMC Genetics 2004 5:11
  4. At the turn of the 19th century the first observations of a female-biased sex ratio in broods and populations of the head louse, Pediculus humanus capitis, had been reported. A study by Buxton in 1940 on the sex ...

    Authors: M Alejandra Perotti, Silvia S Catalá, Analía del V Ormeño, Monika Żelazowska, Szczepan M Biliński and Henk R Braig
    Citation: BMC Genetics 2004 5:10
  5. For a diploid organism such as human, the two alleles of a particular gene can be expressed at different levels due to X chromosome inactivation, gene imprinting, different local promoter activity, or mRNA sta...

    Authors: Chunming Ding, Esther Maier, Adelbert A Roscher, Andreas Braun and Charles R Cantor
    Citation: BMC Genetics 2004 5:8
  6. A major boost to the cystic fibrosis disease research was given by the generation of various mouse models using gene targeting in embryonal stem cells. Moreover, the introduction of the same mutation on differ...

    Authors: Nikoletta Charizopoulou, Silke Jansen, Martina Dorsch, Frauke Stanke, Julia R Dorin, Hans-Jürgen Hedrich and Burkhard Tümmler
    Citation: BMC Genetics 2004 5:6
  7. The incidence of Type 1 diabetes (T1DM) is increasing fast in many populations. The reasons for this are not known, although an increase in the penetrance of the diabetes-associated alleles, through changes in...

    Authors: Janne Pitkäniemi, Päivi Onkamo, Jaakko Tuomilehto and Elja Arjas
    Citation: BMC Genetics 2004 5:5
  8. Public SNP databases are frequently used to choose SNPs for candidate genes in the association and linkage studies of complex disorders. However, their utility for such studies of diseases with ethnic-dependen...

    Authors: Volodymyr Dvornyk, Ji-Rong Long, Dong-Hai Xiong, Peng-Yuan Liu, Lan-Juan Zhao, Hui Shen, Yuan-Yuan Zhang, Yong-Jun Liu, Sonia Rocha-Sanchez, Peng Xiao, Robert R Recker and Hong-Wen Deng
    Citation: BMC Genetics 2004 5:4
  9. Rheumatoid arthritis (RA) and juvenile rheumatoid arthritis (JRA) are complex multifactorial diseases caused by environmental influences and an unknown number of predisposing genes. The present study was under...

    Authors: Bianca Miterski, Susanne Drynda, Gundula Böschow, Wolfram Klein, Joachim Oppermann, Jörn Kekow and Jörg Thomas Epplen
    Citation: BMC Genetics 2004 5:2
  10. The genus Morus, known as mulberry, is a dioecious and cross-pollinating plant that is the sole food for the domesticated silkworm, Bombyx mori. Traditional methods using morphological traits for classification a...

    Authors: Arvind K Awasthi, GM Nagaraja, GV Naik, Sriramana Kanginakudru, K Thangavelu and Javaregowda Nagaraju
    Citation: BMC Genetics 2004 5:1
  11. To find specific genes predisposing to heavy alcohol consumption (self-reported consumption of 24 grams or more of alcohol per day among men and 12 grams or more among women), we studied 330 families collected...

    Authors: Diego F Wyszynski, Carolien I Panhuysen, Qianli Ma, Agustin G Yip, Marsha Wilcox, Porat Erlich and Lindsay A Farrer
    Citation: BMC Genetics 2003 4(Suppl 1):S106

    This article is part of a Supplement: Volume 4 Supplement 1

  12. Atherogenic dyslipidemia (AD) is a common feature in persons with premature coronary heart disease. While several linkage studies have been carried out to dissect the genetic etiology of lipid levels, few have...

    Authors: Agustin G Yip, Qianli Ma, Marsha Wilcox, Carolien I Panhuysen, John Farrell, Lindsay A Farrer and Diego F Wyszynski
    Citation: BMC Genetics 2003 4(Suppl 1):S100

    This article is part of a Supplement: Volume 4 Supplement 1

  13. Despite strong evidence for a genetic component to variation in high-density lipoprotein cholesterol levels (HDL-C), specific polymorphisms associated with normal variation in HDL-C have not been identified. I...

    Authors: Kari E North, Lisa J Martin, Tom Dyer, Anthony G Comuzzie and Jeff T Williams
    Citation: BMC Genetics 2003 4(Suppl 1):S98

    This article is part of a Supplement: Volume 4 Supplement 1

  14. Insulin resistance, obesity, dyslipidemia, and high blood pressure characterize the metabolic syndrome. In an effort to explore the utility of different multivariate methods of data reduction to better underst...

    Authors: Lisa J Martin, Kari E North, Tom Dyer, John Blangero, Anthony G Comuzzie and Jeff Williams
    Citation: BMC Genetics 2003 4(Suppl 1):S95

    This article is part of a Supplement: Volume 4 Supplement 1

  15. Compared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression me...

    Authors: Saurabh Ghosh, Sarah Bertelsen and Theodore Reich
    Citation: BMC Genetics 2003 4(Suppl 1):S92

    This article is part of a Supplement: Volume 4 Supplement 1

  16. Elevated blood pressure in middle age is a major risk factor for subsequent cardiovascular complications. An important longitudinal characteristic of blood pressure is the "tracking phenomenon". Tracking is de...

    Authors: Tao Wang, Guohua Zhu and Kevin J Keen
    Citation: BMC Genetics 2003 4(Suppl 1):S88

    This article is part of a Supplement: Volume 4 Supplement 1

  17. For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effect...

    Authors: Julia MP Soler and John Blangero
    Citation: BMC Genetics 2003 4(Suppl 1):S87

    This article is part of a Supplement: Volume 4 Supplement 1

  18. Only one genome scan to date has attempted to make use of the longitudinal data available in the Framingham Heart Study, and this attempt yielded evidence of linkage to a gene for mean systolic blood pressure....

    Authors: Kevin B Jacobs, Courtney Gray-McGuire, Kevin C Cartier and Robert C Elston
    Citation: BMC Genetics 2003 4(Suppl 1):S82

    This article is part of a Supplement: Volume 4 Supplement 1

  19. Often, multiple measures of a trait are available in a genetic linkage analysis. We compare Monte Carlo Markov chain analysis of two very different measures of hypertension in the simulated Genetic Analysis Wo...

    Authors: E Warwick Daw, Xiaoming Liu and Chih-Chieh Wu
    Citation: BMC Genetics 2003 4(Suppl 1):S80

    This article is part of a Supplement: Volume 4 Supplement 1

  20. We describe a method for mapping quantitative trait loci that allows for locus heterogeneity. A genome-wide linkage analysis of blood pressure was performed using sib-pair data from the Framingham Heart Study....

    Authors: Xinqun Yang, Kai Wang, Jian Huang and Veronica J Vieland
    Citation: BMC Genetics 2003 4(Suppl 1):S78

    This article is part of a Supplement: Volume 4 Supplement 1

  21. A genome-wide linkage analysis was conducted on systolic blood pressure using a score statistic. The randomly selected Replicate 34 of the simulated data was used. The score statistic was applied to the sibshi...

    Authors: Kai Wang and Yingwei Peng
    Citation: BMC Genetics 2003 4(Suppl 1):S77

    This article is part of a Supplement: Volume 4 Supplement 1

  22. This Genetic Analysis Workshop 13 contribution presents a linkage analysis of hypertension in the Framingham data based on the posterior probability of linkage, or PPL. We dichotomized the phenotype, coding in...

    Authors: Mark W Logue, Rhinda J Goedken and Veronica J Vieland
    Citation: BMC Genetics 2003 4(Suppl 1):S75

    This article is part of a Supplement: Volume 4 Supplement 1

  23. Our Markov chain Monte Carlo (MCMC) methods were used in linkage analyses of the Framingham Heart Study data using all available pedigrees. Our goal was to detect and map loci associated with covariate-adjuste...

    Authors: Andrew W George, Saonli Basu, Na Li, Joseph H Rothstein, Solveig K Sieberts, William Stewart, Ellen M Wijsman and Elizabeth A Thompson
    Citation: BMC Genetics 2003 4(Suppl 1):S71

    This article is part of a Supplement: Volume 4 Supplement 1

  24. In the analysis of complex traits such as fasting plasma glucose levels, researchers often adjust the trait for some important covariates before assessing gene susceptibility, and may at times encounter confou...

    Authors: Chien-Hsiun Chen, Chee Jen Chang, Wei-Shiung Yang, Chun-Liang Chen and Cathy SJ Fann
    Citation: BMC Genetics 2003 4(Suppl 1):S65

    This article is part of a Supplement: Volume 4 Supplement 1

  25. We report tree-based association analysis as applied to the two Framingham cohorts and to the first replication of the simulated data obtained from the Genetic Analysis Workshop 13. For this analysis, familial...

    Authors: Elizabeth J Atkinson and Mariza de Andrade
    Citation: BMC Genetics 2003 4(Suppl 1):S63

    This article is part of a Supplement: Volume 4 Supplement 1

  26. We performed a bivariate analysis on cholesterol and triglyceride levels on data from the Framingham Heart Study using a new score statistic developed for the detection of potential pleiotropic, or cluster, ge...

    Authors: Xuyang Zhang and Kai Wang
    Citation: BMC Genetics 2003 4(Suppl 1):S62

    This article is part of a Supplement: Volume 4 Supplement 1

  27. Using the genome-wide screening data of the Framingham Heart Study (394 nuclear families, 1328 genotyped subjects, 397 marker loci) we have quantified the underlying genetic diversity through high-dimensional ...

    Authors: Hans H Stassen, Katrin Hoffman and Christian Scharfetter
    Citation: BMC Genetics 2003 4(Suppl 1):S59

    This article is part of a Supplement: Volume 4 Supplement 1

  28. Plasma triglyceride and high density lipoprotein cholesterol levels are inversely correlated and both are genetically related. Two correlated traits may be influenced both by shared and unshared genes. The pow...

    Authors: Jing-Ping Lin
    Citation: BMC Genetics 2003 4(Suppl 1):S47

    This article is part of a Supplement: Volume 4 Supplement 1

  29. Methods to handle missing data have been an area of statistical research for many years. Little has been done within the context of pedigree analysis. In this paper we present two methods for imputing missing ...

    Authors: Brooke Fridley, Kari Rabe and Mariza de Andrade
    Citation: BMC Genetics 2003 4(Suppl 1):S42

    This article is part of a Supplement: Volume 4 Supplement 1

  30. Several different approaches can be used to examine generational and temporal trends in family studies. The measurement of offspring and parents can be made over a short period of time with parents and offspri...

    Authors: Rasika A Mathias, Marie-Hélène Roy-Gagnon, Cristina M Justice, George J Papanicolaou, Yu Ti Fan, Elizabeth W Pugh and Alexander F Wilson
    Citation: BMC Genetics 2003 4(Suppl 1):S36

    This article is part of a Supplement: Volume 4 Supplement 1

  31. To evaluate linkage evidence for body mass index (BMI) using both cross-sectional and longitudinal data, we performed genome-wide multipoint linkage analyses on subjects who had complete data at four selected ...

    Authors: Xiaohui Li, Dai Wang, Kai Yang, Xiuqing Guo, Ying-chao Lin, Carlos G Samayoa and Huiying Yang
    Citation: BMC Genetics 2003 4(Suppl 1):S35

    This article is part of a Supplement: Volume 4 Supplement 1

  32. The repeated measures in the Framingham Heart Study in the Genetic Analysis Workshop 13 data set allow us to test for consistency of linkage results within a study across time. We compared regression-based lin...

    Authors: Larry D Atwood, Nancy L Heard-Costa, L Adrienne Cupples and Daniel Levy
    Citation: BMC Genetics 2003 4(Suppl 1):S30

    This article is part of a Supplement: Volume 4 Supplement 1

  33. The Framingham Heart Study is a very successful longitudinal research for cardiovascular diseases. The completion of a 10-cM genome scan in Framingham families provided an opportunity to evaluate linkage using...

    Authors: Dai Wang, Xiaohui Li, Ying-Chao Lin, Kai Yang, Xiuqing Guo and Huiying Yang
    Citation: BMC Genetics 2003 4(Suppl 1):S28

    This article is part of a Supplement: Volume 4 Supplement 1

  34. The design of appropriate strategies to analyze and interpret linkage results for complex human diseases constitutes a challenge. Parameters such as power, definition of phenotype, and replicability have to be...

    Authors: Neil Shephard, Milena Falcaro, Eleftheria Zeggini, Philip Chapman, Anne Hinks, Anne Barton, Jane Worthington, Andrew Pickles and Sally John
    Citation: BMC Genetics 2003 4(Suppl 1):S26

    This article is part of a Supplement: Volume 4 Supplement 1

  35. The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of t...

    Authors: Stuart Macgregor, Sara A Knott, Ian White and Peter M Visscher
    Citation: BMC Genetics 2003 4(Suppl 1):S22

    This article is part of a Supplement: Volume 4 Supplement 1

  36. We compare two methods to detect genetic linkage by using serial observations of systolic blood pressure in pedigree data from the Framingham Heart Study focusing on chromosome 17. The first method is a varian...

    Authors: Mariza de Andrade and Curtis Olswold
    Citation: BMC Genetics 2003 4(Suppl 1):S17

    This article is part of a Supplement: Volume 4 Supplement 1

  37. We investigate the power of heterogeneity LOD test to detect linkage when a trait is determined by several major genes using Genetic Analysis Workshop 13 simulated data. We consider three traits, two of which ...

    Authors: Yun Joo Yoo, Yanling Huo, Yuming Ning, Derek Gordon, Stephen Finch and Nancy R Mendell
    Citation: BMC Genetics 2003 4(Suppl 1):S16

    This article is part of a Supplement: Volume 4 Supplement 1

  38. Problem 1 of the Genetic Analysis Workshop 13(GAW13) contains longitudinal data of cardiovascular measurements from 330 pedigrees. The longitudinal data complicates the phenotype definition because multiple me...

    Authors: Susan L Slager and Stephen J Iturria
    Citation: BMC Genetics 2003 4(Suppl 1):S13

    This article is part of a Supplement: Volume 4 Supplement 1

  39. One of the great strengths of the Framingham Heart Study data, provided for the Genetic Analysis Workshop 13, is the long-term survey of phenotypic data. We used this unique data to create new phenotypes repre...

    Authors: Astrid Golla, Konstantin Strauch, Johannes Dietter and Max P Baur
    Citation: BMC Genetics 2003 4(Suppl 1):S7

    This article is part of a Supplement: Volume 4 Supplement 1

  40. We used a random coefficient regression (RCR) model to estimate growth parameters for the time series of observed serum glucose levels in the Replicate 1 of the Genetic Analysis Workshop 13 simulated data. For...

    Authors: Jonathan Corbett, Aldi Kraja, Ingrid B Borecki and Michael A Province
    Citation: BMC Genetics 2003 4(Suppl 1):S5

    This article is part of a Supplement: Volume 4 Supplement 1

  41. We performed variance components linkage analysis in nuclear families from the Framingham Heart Study on nine phenotypes derived from systolic blood pressure (SBP). The phenotypes were the maximum and mean SBP...

    Authors: Martyn C Byng, Sheila A Fisher, Cathryn M Lewis and John C Whittaker
    Citation: BMC Genetics 2003 4(Suppl 1):S4

    This article is part of a Supplement: Volume 4 Supplement 1

  42. Authors: Laura Almasy, Christopher I Amos, Joan E Bailey-Wilson, Rita M Cantor, Cashell E Jaquish, Maria Martinez, Rosalind J Neuman, Jane M Olson, Lyle J Palmer, Stephen S Rich, M Anne Spence and Jean W MacCluer
    Citation: BMC Genetics 2003 4(Suppl 1):S1

    This article is part of a Supplement: Volume 4 Supplement 1

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