| Name : R-networkABC
| |
| Version : 0.8.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.5
| Date : 2024-06-14 12:00:42
|
| Group : Development/Libraries/Other
| Source RPM : R-networkABC-0.8.1-lp153.2.5.src.rpm
|
| Size : 0.49 MB
| |
| Packager : (none)
| |
| Summary : Network Reverse Engineering with Approximate Bayesian Computation
|
Description :
We developed an inference tool based on approximate Bayesian
computation to decipher network data and assess the strength of the
inferred links between network\'s actors. It is a new multi-level
approximate Bayesian computation (ABC) approach. At the first level,
the method captures the global properties of the network, such as a
scale-free structure and clustering coefficients, whereas the second
level is targeted to capture local properties, including the
probability of each couple of genes being linked. Up to now,
Approximate Bayesian Computation (ABC) algorithms have been scarcely
used in that setting and, due to the computational overhead, their
application was limited to a small number of genes. On the contrary,
our algorithm was made to cope with that issue and has low
computational cost. It can be used, for instance, for elucidating gene
regulatory network, which is an important step towards understanding
the normal cell physiology and complex pathological phenotype.
Reverse-engineering consists in using gene expressions over time or
over different experimental conditions to discover the structure of the
gene network in a targeted cellular process. The fact that gene
expression data are usually noisy, highly correlated, and have high
dimensionality explains the need for specific statistical methods to
reverse engineer the underlying network.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
