Network medicine in the age of biomedical big data
Network medicine is an emerging area of research dealing with molecular and genetic
interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale …
interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale …
Inferring cellular networks using probabilistic graphical models
N Friedman - Science, 2004 - science.org
High-throughput genome-wide molecular assays, which probe cellular networks from
different perspectives, have become central to molecular biology. Probabilistic graphical …
different perspectives, have become central to molecular biology. Probabilistic graphical …
A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics
J Schäfer, K Strimmer - Statistical applications in genetics and …, 2005 - degruyter.com
Inferring large-scale covariance matrices from sparse genomic data is an ubiquitous
problem in bioinformatics. Clearly, the widely used standard covariance and correlation …
problem in bioinformatics. Clearly, the widely used standard covariance and correlation …
An empirical Bayes approach to inferring large-scale gene association networks
J Schäfer, K Strimmer - Bioinformatics, 2005 - academic.oup.com
Motivation: Genetic networks are often described statistically using graphical models (eg
Bayesian networks). However, inferring the network structure offers a serious challenge in …
Bayesian networks). However, inferring the network structure offers a serious challenge in …
AP2/EREBP transcription factors are part of gene regulatory networks and integrate metabolic, hormonal and environmental signals in stress acclimation and …
KJ Dietz, MO Vogel, A Viehhauser - Protoplasma, 2010 - Springer
To optimize acclimation responses to environmental growth conditions, plants integrate and
weigh a diversity of input signals. Signal integration within the signalling networks occurs at …
weigh a diversity of input signals. Signal integration within the signalling networks occurs at …
Discovery of meaningful associations in genomic data using partial correlation coefficients
A De La Fuente, N Bing, I Hoeschele, P Mendes - Bioinformatics, 2004 - academic.oup.com
Motivation: A major challenge of systems biology is to infer biochemical interactions from
large-scale observations, such as transcriptomics, proteomics and metabolomics. We …
large-scale observations, such as transcriptomics, proteomics and metabolomics. We …
Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana
A Wille, P Zimmermann, E Vranová, A Fürholz, O Laule… - Genome biology, 2004 - Springer
We present a novel graphical Gaussian modeling approach for reverse engineering of
genetic regulatory networks with many genes and few observations. When applying our …
genetic regulatory networks with many genes and few observations. When applying our …
Network structure inference, a survey: Motivations, methods, and applications
Networks represent relationships between entities in many complex systems, spanning from
online social interactions to biological cell development and brain connectivity. In many …
online social interactions to biological cell development and brain connectivity. In many …
Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns
We describe a method based on the principle of entropy maximization to identify the gene
interaction network with the highest probability of giving rise to experimentally observed …
interaction network with the highest probability of giving rise to experimentally observed …
Statistical estimation of correlated genome associations to a quantitative trait network
Many complex disease syndromes, such as asthma, consist of a large number of highly
related, rather than independent, clinical or molecular phenotypes. This raises a new …
related, rather than independent, clinical or molecular phenotypes. This raises a new …