Sentence examples for molecular network data from inspiring English sources

In addition, large-scale molecular network data are available [ 10– 12], such as protein-protein interaction data, metabolic pathway data, and gene regulation data.

Here, we extend this method to take multiple types of molecular network data and use them to reconstruct and update GO with new information.

In this review, we introduce a few concepts and tools that are in our view useful for analyzing and visualizing pathway and molecular network data.

Motivated by this work, we develop a novel data integration framework that integrates multiple types of molecular network data to reconstruct and update GO.

Motivation: Recently, a shift was made from using Gene Ontology (GO) to evaluate molecular network data to using these data to construct and evaluate GO.

The predictive strength of this strategy is based on the combined constraints arising from multiple biological data sources, including time course gene expression data, combined molecular interaction network data, and GO category information.

Integrating data from different high-throughput measurement platforms (e.g. transcriptomic and proteomic) can be particularly useful to comprehensively detect disease-associated genes, and statistical approaches have been specifically developed to iteratively expand a molecular network using multiple data types (Hwang et al, 2005).

IPA has key components for Signaling and Metabolic pathways analysis, Cellular and Disease Process Analysis, Molecular Network Analysis and Contextual Data analysis.

In particular, we focused on those approaches that explore transcriptome, molecular network, and drug effect data due to their public availability.

That is, we are now minimizing: (3) min G 1 ≥ 0, G 2 ≥ 0 J = || R 12 − G 1 S 12 G 2 T || 2   + t r (G 1 T L 1 G 1 ) + t r (G 2 T L 2 G 2 ) where L α = D α − A α represents network Laplacian of the molecular network of the α data type; A α is the network adjacency matrix, and D α is the diagonal degree matrix with entries being row summation of the matrix A α : D α (i, i ) = ∑ j A α (i, j ).

The genes from the data set were overlaid onto a global molecular network developed from information contained in the IPKB.