Changes in expression of VGF, SPECC1L, HLA-DRA and RANBP3L act with APOE E4 to alter risk for late onset Alzheimer's disease
S Branciamore, G Gogoshin, AS Rodin, AJ Myers - Scientific Reports, 2024 - nature.com
While there are currently over 40 replicated genes with mapped risk alleles for Late Onset
Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest …
Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest …
[HTML][HTML] Using Bayesian latent Gaussian graphical models to infer symptom associations in verbal autopsies
Learning dependence relationships among variables of mixed types provides insights in a
variety of scientific settings and is a well-studied problem in statistics. Existing methods …
variety of scientific settings and is a well-studied problem in statistics. Existing methods …
Linear Regression
J Lederer, J Lederer - Fundamentals of High-Dimensional Statistics: With …, 2022 - Springer
Linear regression relates predictor variables and outcome variables, such as gene copy
numbers and the level of a biomarker. The assumed linearity of the relationships makes the …
numbers and the level of a biomarker. The assumed linearity of the relationships makes the …
An expectation conditional maximization approach for Gaussian graphical models
ZR Li, TH McCormick - Journal of Computational and Graphical …, 2019 - Taylor & Francis
Bayesian graphical models are a useful tool for understanding dependence relationships
among many variables, particularly in situations with external prior information. In high …
among many variables, particularly in situations with external prior information. In high …
Maximum regularized likelihood estimators: A general prediction theory and applications
Maximum regularized likelihood estimators (MRLEs) are arguably the most established
class of estimators in high‐dimensional statistics. In this paper, we derive guarantees for …
class of estimators in high‐dimensional statistics. In this paper, we derive guarantees for …
Thresholded adaptive validation: Tuning the graphical lasso for graph recovery
M Laszkiewicz, A Fischer… - … Conference on Artificial …, 2021 - proceedings.mlr.press
Abstract Many Machine Learning algorithms are formulated as regularized optimization
problems, but their performance hinges on a regularization parameter that needs to be …
problems, but their performance hinges on a regularization parameter that needs to be …
Graphical model inference with external network data
ABSTRACT A frequent challenge when using graphical models in practice is that the sample
size is limited relative to the number of parameters. They also become hard to interpret when …
size is limited relative to the number of parameters. They also become hard to interpret when …
False discovery rates in biological networks
The increasing availability of data has generated unprecedented prospects for network
analyses in many biological fields, such as neuroscience (eg, brain networks), genomics …
analyses in many biological fields, such as neuroscience (eg, brain networks), genomics …
A modeling framework for detecting and leveraging node-level information in Bayesian network inference
X Xi, H Ruffieux - Biostatistics, 2024 - academic.oup.com
Bayesian graphical models are powerful tools to infer complex relationships in high
dimension, yet are often fraught with computational and statistical challenges. If exploited in …
dimension, yet are often fraught with computational and statistical challenges. If exploited in …
[HTML][HTML] The Human Brainome: changes in expression of VGF, SPECC1L, HLA-DRA and RANBP3L act with APOE E4 to alter risk for late onset Alzheimer's disease
S Branciamore, G Gogoshin, AS Rodin… - Research …, 2023 - ncbi.nlm.nih.gov
While there are currently over 40 replicated genes with mapped risk alleles for Late Onset
Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest …
Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest …