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https://www.readbyqxmd.com/read/28548951/development-of-a-novel-score-for-the-prediction-of-hospital-mortality-in-patients-with-severe-sepsis-the-use-of-electronic-healthcare-records-with-lasso-regression
#1
Zhongheng Zhang, Yucai Hong
BACKGROUND AND OBJECTIVE: There are several disease severity scores being used for the prediction of mortality in critically ill patients. However, none of them was developed and validated specifically for patients with severe sepsis. The present study aimed to develop a novel prediction score for severe sepsis. RESULTS: A total of 3206 patients with severe sepsis were enrolled, including 1054 non-survivors and 2152 survivors. The LASSO score showed the best discrimination (area under curve: 0...
May 15, 2017: Oncotarget
https://www.readbyqxmd.com/read/28546826/ipf-lasso-integrative-l1-penalized-regression-with-penalty-factors-for-prediction-based-on-multi-omics-data
#2
Anne-Laure Boulesteix, Riccardo De Bin, Xiaoyu Jiang, Mathias Fuchs
As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed "omics" data in this paper), such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28541712/a-comparison-of-two-stage-approaches-based-on-penalized-regression-for-estimating-gene-networks
#3
Minhyeok Lee, Junhee Seok, Donghyun Tae, Hua Zhong, Sung Won Han
Graphical models are commonly used for illustrating gene networks. However, estimating directed networks are generally challenging because of the limited sample size compared with the dimensionality of an experiment. Many previous studies have provided insight into the problem, and recently, two-stage approaches have shown significant improvements for estimating directed acyclic graphs. These two-stage approaches find neighborhoods in the first stage and determine the directions of the edges in the second stage...
May 25, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28534238/a-fast-algorithm-for-bayesian-multi-locus-model-in-genome-wide-association-studies
#4
Weiwei Duan, Yang Zhao, Yongyue Wei, Sheng Yang, Jianling Bai, Sipeng Shen, Mulong Du, Lihong Huang, Zhibin Hu, Feng Chen
Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data...
May 22, 2017: Molecular Genetics and Genomics: MGG
https://www.readbyqxmd.com/read/28533786/high-density-linkage-map-construction-and-mapping-of-yield-trait-qtls-in-maize-zea-mays-using-the-genotyping-by-sequencing-gbs-technology
#5
Chengfu Su, Wei Wang, Shunliang Gong, Jinghui Zuo, Shujiang Li, Shizhong Xu
Increasing grain yield is the ultimate goal for maize breeding. High resolution quantitative trait loci (QTL) mapping can help us understand the molecular basis of phenotypic variation of yield and thus facilitate marker assisted breeding. The aim of this study is to use genotyping-by-sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of all F2 individuals from a cross between two varieties of maize that are in clear contrast in yield and related traits. A set of 199 F2 progeny derived from the cross of varieties SG-5 and SG-7 were generated and genotyped by GBS...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28532387/robust-estimation-of-the-expected-survival-probabilities-from-high-dimensional-cox-models-with-biomarker-by-treatment-interactions-in-randomized-clinical-trials
#6
Nils Ternès, Federico Rotolo, Stefan Michiels
BACKGROUND: Thanks to the advances in genomics and targeted treatments, more and more prediction models based on biomarkers are being developed to predict potential benefit from treatments in a randomized clinical trial. Despite the methodological framework for the development and validation of prediction models in a high-dimensional setting is getting more and more established, no clear guidance exists yet on how to estimate expected survival probabilities in a penalized model with biomarker-by-treatment interactions...
May 22, 2017: BMC Medical Research Methodology
https://www.readbyqxmd.com/read/28522086/correlates-of-sleep-quality-in-midlife-and-beyond-a-machine-learning-analysis
#7
Katherine A Kaplan, Prajesh P Hardas, Susan Redline, Jamie M Zeitzer
OBJECTIVES: In older adults, traditional metrics derived from polysomnography (PSG) are not well correlated with subjective sleep quality. Little is known about whether the association between PSG and subjective sleep quality changes with age, or whether quantitative electroencephalography (qEEG) is associated with sleep quality. Therefore, we examined the relationship between subjective sleep quality and objective sleep characteristics (standard PSG and qEEG) across middle to older adulthood...
June 2017: Sleep Medicine
https://www.readbyqxmd.com/read/28520730/analysis-of-heterogeneity-in-t2-weighted-mr-images-can-differentiate-pseudoprogression-from-progression-in-glioblastoma
#8
Thomas C Booth, Timothy J Larkin, Yinyin Yuan, Mikko I Kettunen, Sarah N Dawson, Daniel Scoffings, Holly C Canuto, Sarah L Vowler, Heide Kirschenlohr, Michael P Hobson, Florian Markowetz, Sarah Jefferies, Kevin M Brindle
PURPOSE: To develop an image analysis technique that distinguishes pseudoprogression from true progression by analyzing tumour heterogeneity in T2-weighted images using topological descriptors of image heterogeneity called Minkowski functionals (MFs). METHODS: Using a retrospective patient cohort (n = 50), and blinded to treatment response outcome, unsupervised feature estimation was performed to investigate MFs for the presence of outliers, potential confounders, and sensitivity to treatment response...
2017: PloS One
https://www.readbyqxmd.com/read/28514941/effects-of-marker-density-and-population-structure-on-the-genomic-prediction-accuracy-for-growth-trait-in-pacific-white-shrimp-litopenaeus-vannamei
#9
Quanchao Wang, Yang Yu, Jianbo Yuan, Xiaojun Zhang, Hao Huang, Fuhua Li, Jianhai Xiang
BACKGROUND: Due to the great advantages in selection accuracy and efficiency, genomic selection (GS) has been widely studied in livestock, crop and aquatic animals. Our previous study based on one full-sib family of Litopenaeus vannamei (L. vannamei) showed that GS was feasible in penaeid shrimp. However, the applicability of GS might be influenced by many factors including heritability, marker density and population structure etc. Therefore it is necessary to evaluate the major factors affecting the prediction ability of GS in shrimp...
May 17, 2017: BMC Genetics
https://www.readbyqxmd.com/read/28499008/rippminer-a-bioinformatics-resource-for-deciphering-chemical-structures-of-ripps-based-on-prediction-of-cleavage-and-cross-links
#10
Priyesh Agrawal, Shradha Khater, Money Gupta, Neetu Sain, Debasisa Mohanty
Ribosomally synthesized and post-translationally modified peptides (RiPPs) constitute a rapidly growing class of natural products with diverse structures and bioactivities. We have developed RiPPMiner, a novel bioinformatics resource for deciphering chemical structures of RiPPs by genome mining. RiPPMiner derives its predictive power from machine learning based classifiers, trained using a well curated database of more than 500 experimentally characterized RiPPs. RiPPMiner uses Support Vector Machine to distinguish RiPP precursors from other small proteins and classify the precursors into 12 sub-classes of RiPPs...
May 12, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28497927/the-potential-role-of-pain-related-sseps-in-the-early-prognostication-of-long-term-functional-outcome-in-post-anoxic-coma
#11
Alessandra Del Felice, Stefano Bargellesi, Federico Linassi, Bruno Scarpa, Emanuela Formaggio, Paolo Boldrini, Stefano Masiero, Paolo Zanatta
BACKGROUND: Cardiac arrest (CA) is a common cause of disability. Multimodal evaluation has improved prognosis but precocious biomarkers are not appropriate in determining long-term functional outcome. AIM: to identify early prognostication markers of long-term functional outcome in post-anoxic coma. DESIGN: retrospective assessment of outcomes. POPULATION: Individuals older than 18 years with post-anoxic coma hospitalized in intensive care units after cardiac arrest (CA) regardless of cause (cardiac or non-cardiac) and location of event (in or out-of-hospital)...
May 12, 2017: European Journal of Physical and Rehabilitation Medicine
https://www.readbyqxmd.com/read/28490319/prediction-of-gene-expression-with-cis-snps-using-mixed-models-and-regularization-methods
#12
Ping Zeng, Xiang Zhou, Shuiping Huang
BACKGROUND: It has been shown that gene expression in human tissues is heritable, thus predicting gene expression using only SNPs becomes possible. The prediction of gene expression can offer important implications on the genetic architecture of individual functional associated SNPs and further interpretations of the molecular basis underlying human diseases. METHODS: We compared three types of methods for predicting gene expression using only cis-SNPs, including the polygenic model, i...
May 11, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28487748/node-structured-integrative-gaussian-graphical-model-guided-by-pathway-information
#13
SungHwan Kim, Jae-Hwan Jhong, JungJun Lee, Ja-Yong Koo, ByungYong Lee, SungWon Han
Up to date, many biological pathways related to cancer have been extensively applied thanks to outputs of burgeoning biomedical research. This leads to a new technical challenge of exploring and validating biological pathways that can characterize transcriptomic mechanisms across different disease subtypes. In pursuit of accommodating multiple studies, the joint Gaussian graphical model was previously proposed to incorporate nonzero edge effects. However, this model is inevitably dependent on post hoc analysis in order to confirm biological significance...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28484471/genomic-selection-for-drought-tolerance-using-genome-wide-snps-in-maize
#14
Mittal Shikha, Arora Kanika, Atmakuri Ramakrishna Rao, Mallana Gowdra Mallikarjuna, Hari Shanker Gupta, Thirunavukkarasu Nepolean
Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS) has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28482933/models-solely-using-claims-based-administrative-data-are-poor-predictors-of-rheumatoid-arthritis-disease-activity
#15
Brian C Sauer, Chia-Chen Teng, Neil A Accortt, Zachary Burningham, David Collier, Mona Trivedi, Grant W Cannon
BACKGROUND: This study developed and validated a claims-based statistical model to predict rheumatoid arthritis (RA) disease activity, measured by the 28-joint count Disease Activity Score (DAS28). METHOD: Veterans enrolled in the Veterans Affairs Rheumatoid Arthritis (VARA) registry with one year of data available for review before being assessed by the DAS28, were studied. Three models were developed based on initial selection of variables for analyses. The first model was based on clinically defined variables, the second leveraged grouping systems for high dimensional data and the third approach prescreened all possible predictors based on a significant bivariate association with the DAS28...
May 8, 2017: Arthritis Research & Therapy
https://www.readbyqxmd.com/read/28479862/estimation-of-high-dimensional-mean-regression-in-the-absence-of-symmetry-and-light-tail-assumptions
#16
Jianqing Fan, Quefeng Li, Yuyan Wang
Data subject to heavy-tailed errors are commonly encountered in various scientific fields. To address this problem, procedures based on quantile regression and Least Absolute Deviation (LAD) regression have been developed in recent years. These methods essentially estimate the conditional median (or quantile) function. They can be very different from the conditional mean functions, especially when distributions are asymmetric and heteroscedastic. How can we efficiently estimate the mean regression functions in ultra-high dimensional setting with existence of only the second moment? To solve this problem, we propose a penalized Huber loss with diverging parameter to reduce biases created by the traditional Huber loss...
January 2017: Journal of the Royal Statistical Society. Series B, Statistical Methodology
https://www.readbyqxmd.com/read/28475830/bayeswham-a-bayesian-approach-for-free-energy-estimation-reweighting-and-uncertainty-quantification-in-the-weighted-histogram-analysis-method
#17
Andrew L Ferguson
The weighted histogram analysis method (WHAM) is a powerful approach to estimate molecular free energy surfaces (FES) from biased simulation data. Bayesian reformulations of WHAM are valuable in proving statistically optimal use of the data and providing a transparent means to incorporate regularizing priors and estimate statistical uncertainties. In this work, we develop a fully Bayesian treatment of WHAM to generate statistically optimal FES estimates in any number of biasing dimensions under arbitrary choices of the Bayes prior...
May 5, 2017: Journal of Computational Chemistry
https://www.readbyqxmd.com/read/28474020/characterization-of-the-structure-dynamics-and-allosteric-pathways-of-human-npp1-in-its-free-form-and-substrate-bound-complex-from-molecular-modeling
#18
Xavier Barbeau, Patrick Mathieu, Jean-François Paquin, Patrick Lagüe
The ectonucleotide phosphodiesterase/pyrophosphatase-1 (NPP1) is a type II transmembrane glycoprotein that regulates extracellular inorganic purine nucleotide and inorganic diphosphate levels through the hydrolysis of ATP into AMP and diphosphate. NPP1 is a promising drug target as it plays a role in several disorders. In the present work, we report the 3D structure modeling and extensive molecular dynamics simulations of NPP1-h, both in its free and ATP-bound forms. We identified the key residues involved in the binding of the ATP and the binding modes...
May 5, 2017: Molecular BioSystems
https://www.readbyqxmd.com/read/28472344/gene-set-selection-via-lasso-penalized-regression-slpr
#19
H Robert Frost, Christopher I Amos
Gene set testing is an important bioinformatics technique that addresses the challenges of power, interpretation and replication. To better support the analysis of large and highly overlapping gene set collections, researchers have recently developed a number of multiset methods that jointly evaluate all gene sets in a collection to identify a parsimonious group of functionally independent sets. Unfortunately, current multiset methods all use binary indicators for gene and gene set activity and assume that a gene is active if any containing gene set is active...
May 2, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28472220/the-spike-and-slab-lasso-cox-model-for-survival-prediction-and-associated-genes-detection
#20
Zaixiang Tang, Yueping Shen, Xinyan Zhang, Nengjun Yi
Motivation: Large-scale molecular profiling data have offered extraordinary opportunities to improve survival prediction of cancers and other diseases and to detect disease associated genes. However, there are considerable challenges in analyzing large-scale molecular data. Results: We propose new Bayesian hierarchical Cox proportional hazards models, called the spike-and-slab lasso Cox, for predicting survival outcomes and detecting associated genes. We also develop an efficient algorithm to fit the proposed models by incorporating EM steps (Expectation-Maximization) into the extremely fast cyclic coordinate descent algorithm...
May 4, 2017: Bioinformatics
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