Discussion on the paper ‘Statistical contributions to bioinformatics: Design, modelling, structure learning and integration’ by Jeffrey S. Morris and Veerabhadran Baladandayuthapani
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Jeanine J. Houwing-Duistermaat | Arief Gusnanto | Hae-Won Uh | J. Houwing-Duistermaat | H. Uh | A. Gusnanto
[1] Kanti V. Mardia,et al. Bayesian Methods in Structural Bioinformatics , 2012 .
[2] R. Spang,et al. State-of-the art data normalization methods improve NMR-based metabolomic analysis , 2011, Metabolomics.
[3] Jesper Ferkinghoff-Borg,et al. A generative, probabilistic model of local protein structure , 2008, Proceedings of the National Academy of Sciences.
[4] Jeanine J Houwing-Duistermaat,et al. Secondary phenotype analysis in ascertained family designs: application to the Leiden longevity study , 2016, Statistics in medicine.
[5] S Banu Ozkan,et al. The protein folding problem: when will it be solved? , 2007, Current opinion in structural biology.
[6] Manfred Wuhrer,et al. Human Plasma N-glycosylation as Analyzed by Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance-MS Associates with Markers of Inflammation and Metabolic Health* , 2016, Molecular & Cellular Proteomics.
[7] K. Pearson. Mathematical contributions to the theory of evolution.—On a form of spurious correlation which may arise when indices are used in the measurement of organs , 1897, Proceedings of the Royal Society of London.
[8] Fabian J. Theis,et al. Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data , 2011, BMC Systems Biology.
[9] John D. Storey,et al. Empirical Bayes Analysis of a Microarray Experiment , 2001 .
[10] Nicolas Servant,et al. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis , 2013, Briefings Bioinform..
[11] John D. Storey. A direct approach to false discovery rates , 2002 .
[12] John Aitchison,et al. The Statistical Analysis of Compositional Data , 1986 .
[13] Paola Sebastiani,et al. Genome-Wide Association Studies (GWAS) , 2019, Definitions.
[14] Perttu Salo,et al. On the Combination of Omics Data for Prediction of Binary Outcomes , 2016, 1610.04465.
[15] Robert J. Moon,et al. Transforming Glycoscience: A Roadmap for the Future , 2012 .
[16] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[17] P. Kraft,et al. Genome‐wide association scans for secondary traits using case‐control samples , 2009, Genetic epidemiology.
[18] Johan Trygg,et al. O2‐PLS, a two‐block (X–Y) latent variable regression (LVR) method with an integral OSC filter , 2003 .
[19] Yudi Pawitan,et al. Filtering genes to improve sensitivity in oligonucleotide microarray data analysis. , 2007, Nucleic acids research.
[20] Christodoulos A. Floudas,et al. Advances in protein structure prediction and de novo protein design : A review , 2006 .
[21] Yudi Pawitan,et al. Fold-Change Estimation of Differentially Expressed Genes using Mixture Mixed-Model , 2005, Statistical applications in genetics and molecular biology.
[22] Yudi Pawitan,et al. Multidimensional local false discovery rate for microarray studies , 2006, Bioinform..
[23] Gerald W. Hart,et al. Glycomics Hits the Big Time , 2010, Cell.
[24] T. N. Bhat,et al. The Protein Data Bank , 2000, Nucleic Acids Res..
[25] Jeanine J. Houwing-Duistermaat,et al. Evaluation of O2PLS in Omics data integration , 2016, BMC Bioinformatics.