A5004979421- Genomics and Rare Diseases
- Gene expression and cancer classification
- Statistical Methods and Bayesian Inference
- Bioinformatics and Genomic Networks
- Molecular Biology Techniques and Applications
- Optimal Experimental Design Methods
- Genetic Mapping and Diversity in Plants and Animals
- RNA Interference and Gene Delivery
- Genetic Associations and Epidemiology
- Statistical Methods in Clinical Trials
- Prostate Cancer Treatment and Research
- COVID-19 epidemiological studies
- SARS-CoV-2 and COVID-19 Research
- Prostate Cancer Diagnosis and Treatment
- Protein Degradation and Inhibitors
- Soil Geostatistics and Mapping
- Radiomics and Machine Learning in Medical Imaging
- Advanced Chemical Sensor Technologies
- Computational Drug Discovery Methods
- Genetic and phenotypic traits in livestock
- Liver Disease Diagnosis and Treatment
- Statistical Distribution Estimation and Applications
- Bayesian Methods and Mixture Models
- Cancer Genomics and Diagnostics
- Genomics and Chromatin Dynamics
Film Independent
2024
Massachusetts Institute of Technology
2024
Triangle
2024
Public Health Foundation
2024
SAS Institute (United States)
2010-2023
King's College London
2023
North Carolina State University
2002-2018
University of Otago
1998
SAS Institute (United Kingdom)
1997
A useful extension of the generalized linear model involves addition random effects andlor correlated errors. pseudo-likelihood estimation procedure is developed to fit this class mixed models based on an approximate marginal for mean response. The implemented via iterated fitting a weighted Gaussian modified dependent variable. approach allows flexible specification covariance structures both and An estimate additional dispersion parameter underlying exponential family distributions...
This article describes a unified approach to variance modeling and inference in the context of general form normal-theory linear mixed model. The primary objects are parameterized covari-ance structures, examples being diagonal, compound-symmetry, unstructured, timeseries, spatial. These structures can enter two different places model, combination one or both these with variety provides rich class models. is likelihood-based, involves use maximum likelihood restricted likelihood. Two provide...
Abstract The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number possible combinations vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large combination dataset, consisting 11,576 experiments from 910 across 85 molecularly characterized cell lines, and results a DREAM Challenge evaluate computational strategies for...
How will this molecule smell? We still do not understand what a given substance smell like. Keller et al. launched an international crowd-sourced competition in which many teams tried to solve how the of be perceived by humans. The were access database responses from subjects who had sniffed large number molecules and been asked rate each across range different qualities. also comprehensive list physical chemical features smelled. produced algorithms predict correspondence between quality...
An approximation to Laplace's method for integrals is applied marginal distributions of data arising from models in which both fixed and random effects enter nonlinearly. The approach provides alternative derivations some recent algorithms fitting such models, it has direct ties with Gaussian restricted maximum likelihood the accompanying mixed model equations.
Algorithms are described for computing the Gaussian likelihood or restricted corresponding to a general linear mixed model. Included arbitrary covariance structures both random effects and errors. Formulas also given first second derivatives of likelihoods, thus enabling Newton–Raphson implementation. The algorithms make heavy use Cholesky decomposition, sweep operator, W-transformation. Also modifications needed variance profiling, Fisher scoring, MIVQUE(0), as well computational order procedures.
Abstract Background Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation precision medicine and a complicated process in which each step affects variant call quality. Systematically assessing reproducibility WGS impact needed understanding improving quality from WGS. Results To dissect factors involved WGS, we sequence triplicates eight DNA samples representing two populations on three short-read platforms using library kits six labs...
Our understanding of COVID-19 synthetic, modified mRNA (modmRNA) products and their public health impact has evolved substantially since December 2020. Published reports from the original randomized placebo-controlled trials concluded that modmRNA injections could greatly reduce symptoms. However, premature termination both obviated any reliable assessment potential adverse events due to an insufficient timeframe for proper safety evaluation. Following authorization global distribution,...
The mechanisms underlying defence reactions to a pathogen attack, though well studied in crop plants, are poorly understood conifers. To analyze changes gene transcript abundance Pinus sylvestris L. root tissues infected by Heterobasidion annosum (Fr.) Bref. s.l., cDNA microarray containing 2109 ESTs from P. taeda was used. Mixed model statistical analysis identified 179 expressed sequence tags differentially at 1, 5 or 15 days post inoculation. In general, the total number of genes during...
The thermophilic anaerobe Clostridium thermocellum is a candidate consolidated bioprocessing (CBP) biocatalyst for cellulosic ethanol production. aim of this study was to investigate C. genes required ferment biomass substrates and conduct robust comparison DNA microarray RNA sequencing (RNA-seq) analytical platforms.C. ATCC 27405 fermentations were conducted with 5 g/L solid substrate loading either pretreated switchgrass or Populus. Quantitative saccharification inductively coupled plasma...
Microarray-based prediction of clinical endpoints may be performed using either a one-color approach reflecting mRNA abundance in absolute intensity values or two-color yielding ratios fluorescent intensities. In this study, as part the MAQC-II project, we systematically compared classification performance resulting from one- and gene-expression profiles 478 neuroblastoma samples. total, 196 models were applied to these measurements predict four endpoints, performances terms accuracy, area...
This bibliography lists all published methodological works (statistical methodology, implementation review papers, descriptions of software) in the area population pharmacokinetics/pharmacodynamics up to 1993 and describing applications 1992.
The need to assess correlation in settings where multiple measurements are available on each of the variables interest often arises environmental science. However, this topic is not covered introductory statistics texts. Although several ad hoc approaches can be used, they easily lead invalid conclusions and a difficult choice an appropriate measure correlation. Lam et al. approached problem by using maximum likelihood estimation cases replicate linked over time, but method requires...
Somatic embryogenesis of Norway spruce (Picea abies L.) is a versatile model system to study molecular mechanisms regulating embryo development because it proceeds through defined developmental stages corresponding specific culture treatments. Normal embryonic involves early differentiation proembryogenic masses (PEMs) into somatic embryos, followed by and late embryogeny leading the formation mature cotyledonary embryos. In some cell lines there arrest at PEM−somatic transition. To learn...
Microarray-based classifiers and associated signature genes generated from various platforms are abundantly reported in the literature; however, utility of cross-platform prediction applications remains largely uncertain. As part MicroArray Quality Control Phase II (MAQC-II) project, we show this study 80-90% consistency using a large toxicogenomics data set by illustrating that: (1) classifier one platform can be directly applied to another develop predictive classifier; (2) developed...
Abstract Recent research has fostered new guidance on preventing and treating missing data. This article is the consensus opinion of Drug Information Association's Scientific Working Group Missing Data. Common elements from recent are distilled means for putting into action proposed. The primary goal to maximize proportion patients that adhere protocol specified interventions. In so doing, trial design conduct should be considered. Completion rate focused upon as much enrollment rate, with...
Abstract The effectiveness of most cancer targeted therapies is short lived since tumors evolve and develop resistance. Combinations drugs offer the potential to overcome resistance, however number possible combinations vast necessitating data-driven approaches find optimal treatments tailored a patient’s tumor. AstraZeneca carried out 11,576 experiments on 910 drug across 85 cell lines, recapitulating in vivo response profiles. These data, largest openly available screen, were hosted by...