Sentence examples for module inference algorithms from inspiring English sources

All these four module inference algorithms are statistics-based methods.

However, all these module inference algorithms are statistics-based methods, treating dynamic time series gene expression data the same way as static steady state gene expression data.

During the last decade, much progress has been made in the development of robust and powerful module network inference algorithms.

In this study, we analyze and assess experimentally a module network inferred from both miRNA and mRNA expression data, using our recently developed module network inference algorithm based on probabilistic optimization techniques.

We have applied a robust and unbiased module network inference algorithm to a cancer-related expression data set of both mRNAs and miRNAs.

Because Arboretum is based on the EM algorithm, final module inference and parameter estimation results may depend upon initial parameter settings.

By combining current transcription factor binding site (TFBS) [ 19, 20], mutant [ 20], ChIP-chip [ 21], and heat shock time series gene expression data [ 18], we developed a module inference method, called Heat-Inducible Module Identification Algorithm (HIMIA), to reconstruct heat-inducible GRMs in yeast (see Figure 1).

The knowledge-based system consists of several modules such as knowledge acquisition module, inference module and user interface module.

Phylogenetic analysis was performed using both maximum likelihood (ML) and Bayesian inference algorithms.

Consequently such networks cannot be deemed as totally reliable benchmarks to compare inference algorithms.

Therefore SAMBA provides an efficient way of validating network inference algorithms.