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Ian Johnston
Boston University
Genome-wide association studyCurse of dimensionalityMachine learningGenetic associationPosterior probability
5Publications
1H-index
3Citations
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Publications 5
Newest
#1Shigeru YamaguchiH-Index: 1
#2Takahiro Nishimura (Kyoto University)H-Index: 42
Last. Ian Johnston (BU: Boston University)H-Index: 1
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In organic chemistry, Comparative Molecular Field Analysis (CoMFA) can be defined as a regression analysis between reaction outcomes and molecular fields, wherein we can extract and visualize important structural information from the coefficients of the constructed regression models. In CoMFA, partial least-squares (PLS) regression, which determines all coefficients in the model, is used for fitting the regression models. However, in organic reactions, steric effects are observed only near the r...
1 CitationsSource
#1Ian Johnston (BU: Boston University)H-Index: 1
#2Yang Jin (BU: Boston University)
Last. Luis Carvalho (BU: Boston University)H-Index: 6
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Bayesian variable selection provides a principled framework for incorporating prior information to regularize parameters in high-dimensional large-p-small-n regression models such as genomewide association studies (GWAS). Although these models produce more informative results, researchers often disregard them in favor of simpler models because of their high computational cost. We explore our recently proposed spatial boost model for GWAS on quantitative traits to assess the computational efficie...
Source
#1Ian Johnston (BU: Boston University)H-Index: 1
#2Luis Carvalho (BU: Boston University)H-Index: 6
The primary goal of genome-wide association studies is to determine which genetic markers are associated with genetic traits, most commonly human diseases. As a result of the "large p, small n" nature of genome-wide association study data sets, and especially because of the collinearity due to linkage disequilibrium, multivariate regression results in an ill-posed problem. To overcome these obstacles, we propose preprocessing single-nucleotide polymorphisms to adjust for linkage disequilibrium, ...
2 CitationsSource
#1Ian JohnstonH-Index: 1
#2Timothy HancockH-Index: 9
Last. Luis CarvalhoH-Index: 6
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Motivated by the important problem of detecting association between genetic markers and binary traits in genome-wide association studies, we present a novel Bayesian model that establishes a hierarchy between markers and genes by defining weights according to gene lengths and distances from genes to markers. The proposed hierarchical model uses these weights to define unique prior probabilities of association for markers based on their proximities to genes that are believed to be relevant to the...
#1Ian JohnstonH-Index: 1
#2Timothy HancockH-Index: 9
Last. Luis CarvalhoH-Index: 6
view all 4 authors...
Motivated by the important problem of detecting association between genetic markers and binary traits in genome-wide association studies, we present a novel Bayesian model that establishes a hierarchy between markers and genes by defining weights according to gene lengths and distances from genes to markers. The proposed hierarchical model uses these weights to define unique prior probabilities of association for markers based on their proximities to genes that are believed to be relevant to the...
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