In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms
Transcriptional regulatory networks specify the interactions among regulatory genes and between regu...
Inference of gene regulatory network from expression data is a challenging task. Many methods have b...
Advances in molecular biological and computational technologies are enabling us to systematically in...
Gene regulatory networks are powerful abstractions of biological systems. Since the advent of high-t...
Transcriptomic data quantifying gene expression states for single cells or cell populations at a gen...
Transcriptomic data quantifying gene expression states for single cells or cell populations at a gen...
Transcriptomic data quantifying gene expression states for single cells or cell populations at a gen...
This volume explores recent techniques for the computational inference of gene regulatory networks (...
Motivation: Prior biological knowledge greatly facilitates the mean-ingful interpretation of gene-ex...
Numerous methods have been developed for inferring gene regulatory networks from expression data, ho...
(A) Our network inference algorithm takes as input a gene expression matrix, X, and a prior on netwo...
ABSTRACT Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of...
Inference of gene regulatory network from expression data is a challenging task. Many methods have b...
Advances in molecular biological and computational technologies are enabling us to systematically in...
In this thesis we present a new model for identifying dependencies withina gene regulatory cycle. Th...
Transcriptional regulatory networks specify the interactions among regulatory genes and between regu...
Inference of gene regulatory network from expression data is a challenging task. Many methods have b...
Advances in molecular biological and computational technologies are enabling us to systematically in...
Gene regulatory networks are powerful abstractions of biological systems. Since the advent of high-t...
Transcriptomic data quantifying gene expression states for single cells or cell populations at a gen...
Transcriptomic data quantifying gene expression states for single cells or cell populations at a gen...
Transcriptomic data quantifying gene expression states for single cells or cell populations at a gen...
This volume explores recent techniques for the computational inference of gene regulatory networks (...
Motivation: Prior biological knowledge greatly facilitates the mean-ingful interpretation of gene-ex...
Numerous methods have been developed for inferring gene regulatory networks from expression data, ho...
(A) Our network inference algorithm takes as input a gene expression matrix, X, and a prior on netwo...
ABSTRACT Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of...
Inference of gene regulatory network from expression data is a challenging task. Many methods have b...
Advances in molecular biological and computational technologies are enabling us to systematically in...
In this thesis we present a new model for identifying dependencies withina gene regulatory cycle. Th...
Transcriptional regulatory networks specify the interactions among regulatory genes and between regu...
Inference of gene regulatory network from expression data is a challenging task. Many methods have b...
Advances in molecular biological and computational technologies are enabling us to systematically in...