Data Repository

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 10, we are given 4 perturbations (each one with 21 time points).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 10, we are given 4 perturbations (each one with 21 time points).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 50, the same number of time courses as in the DREAM2 in silico challenge are provided (23 different perturbations).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 50, the same number of time courses as in the DREAM2 in silico challenge are provided (23 different perturbations).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 50, the same number of time courses as in the DREAM2 in silico challenge are provided (23 different perturbations).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 50, the same number of time courses as in the DREAM2 in silico challenge are provided (23 different perturbations).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 50, the same number of time courses as in the DREAM2 in silico challenge are provided (23 different perturbations).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 100, they give 46 perturbations (each one with 21 time points).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 100, they give 46 perturbations (each one with 21 time points).

The Gold Standard simply states the presence of a relationship, not the direction.

[meninonas]

Dr. Yoo,

The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data and to predict the directed unsigned network topology from the given in silico generated gene expression datasets. There are three in-silico challenges corresponding to gene networks with 10, 50, and 100 genes.

For every network, the following experiments are simulated:

Heterozygous knock-down. The files -heterozygous contain the steady state levels for the wild-type and the heterozygous knock-down strains for each gene.

Null-mutants. The files -null-mutants contain the steady state levels for the wild-type and the null-mutant strains for each gene.

Trajectories. The files -trajectories contain time courses of the network recovering from several external perturbations. For the networks of size 100, they give 46 perturbations (each one with 21 time points).

The Gold Standard simply states the presence of a relationship, not the direction.