This is the repository for the input datasets and config files used for datasets from synthetic and curated networks used in BEELINE
To understand how the components of a complex system like the biological cell interact and regulate ...
These are collections of previously published gene regulatory networks and perturbation transcriptom...
International audienceNetworks are powerful tools to represent and investigate biological systems. T...
This repository contains input files from the synthetic, curated, and processed experimental single-...
Abstract: The complexity of biological systems is encoded in gene regulatory networks. Unravelling t...
Over 400 simulated datasets (across six synthetic networks and four curated Boolean models) original...
Background: In the last decade, a great number of methods for reconstructing gene regulatory network...
The complexity of biological systems is encoded in gene regulatory networks. Unravelling this intric...
This datasets includes time-series gene expression datasets derived from the well-known DREAM3 and D...
This archive contains benchmarking input data and results for using single cell gene expression data...
Numerous methods have been developed for inferring gene regulatory networks from expression data, ho...
Background: Single cell RNA-sequencing (scRNA-seq) has very rapidly become the new workhorse of mode...
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...
Motivation: Over the last decade, numerous methods have been developed for inference of regulatory n...
To understand how the components of a complex system like the biological cell interact and regulate ...
These are collections of previously published gene regulatory networks and perturbation transcriptom...
International audienceNetworks are powerful tools to represent and investigate biological systems. T...
This repository contains input files from the synthetic, curated, and processed experimental single-...
Abstract: The complexity of biological systems is encoded in gene regulatory networks. Unravelling t...
Over 400 simulated datasets (across six synthetic networks and four curated Boolean models) original...
Background: In the last decade, a great number of methods for reconstructing gene regulatory network...
The complexity of biological systems is encoded in gene regulatory networks. Unravelling this intric...
This datasets includes time-series gene expression datasets derived from the well-known DREAM3 and D...
This archive contains benchmarking input data and results for using single cell gene expression data...
Numerous methods have been developed for inferring gene regulatory networks from expression data, ho...
Background: Single cell RNA-sequencing (scRNA-seq) has very rapidly become the new workhorse of mode...
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...
Motivation: Over the last decade, numerous methods have been developed for inference of regulatory n...
To understand how the components of a complex system like the biological cell interact and regulate ...
These are collections of previously published gene regulatory networks and perturbation transcriptom...
International audienceNetworks are powerful tools to represent and investigate biological systems. T...
DOI
Add to ORKG