Long Noncoding RNA AFAP1-AS1 Promotes Cell Proliferation and Metastasis via the miR-155-5p/FGF7 Axis and Predicts Poor Prognosis in Gastric Cancer.

Background: Actin filament-associated protein 1-antisense RNA 1 (AFAP1-AS1) plays an important role in the development and progression of several human cancers. However, its biological function in gastric cancer (GC) progression is still unknown.

Methods: We used qRT-PCR to detect the relative expression of AFAP1-AS1 in GC tissues and cell lines.

The reconstruction and analysis of tissue specific human metabolic networks.

Human tissues have distinct biological functions. Many proteins/enzymes are known to be expressed only in specific tissues and therefore the metabolic networks in various tissues are different. Though high quality global human metabolic networks and metabolic networks for certain tissues such as liver have already been studied, a systematic study of tissue specific metabolic networks for all main tissues is still missing.

Compartmentalization of the Edinburgh Human Metabolic Network.

Background: Direct in vivo investigation of human metabolism is complicated by the distinct metabolic functions of various sub-cellular organelles. Diverse micro-environments in different organelles may lead to distinct functions of the same protein and the use of different enzymes for the same metabolic reaction. To better understand the complexity in the human metabolism, a compartmentalized human metabolic network with integrated sub-cellular location information is required.

Metabolic flux analysis of the two astaxanthin-producing microorganisms Haematococcus pluvialis and Phaffia rhodozyma in the pure and mixed cultures.

The two major astaxanthin-producing microorganisms Phaffia rhodozyma and Haematococcus pluvialis exhibited elevated astaxanthin yields under the mixed culture regime, and the changes in flux distribution were investigated by means of metabolic flux analysis (MFA). In the mixed culture of the two strains, the carbon flux towards astaxanthin formation in P. rhodozyma increased by 20%, which may be due to the enriched oxygen evolved through the photosynthesis of H.

An extended transcriptional regulatory network of Escherichia coli and analysis of its hierarchical structure and network motifs.

Recent studies of genome-wide transcriptional regulatory network (TRN) revealed several intriguing structural and dynamic features of gene expression at a system level. Unfortunately, the network under study is often far from complete. A critical question is thus how much the network is incomplete and to what extent this would affect the results of analysis.

Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach.

Background: Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN) of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules.

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

Motivation: Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network.

Phylogenetic comparison of metabolic capacities of organisms at genome level.

Horizontal gene transfer (HGT) has been shown to widely spread in organisms by comparative genomic studies. However, its effect on the phylogenetic relationship of organisms, especially at a system level of different cellular functions, is still not well understood. In this work, we have constructed phylogenetic trees based on the enzyme, reaction, and gene contents of metabolic networks reconstructed from annotated genome information of 82 sequenced organisms.

The connectivity structure, giant strong component and centrality of metabolic networks.

Motivation: Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important.