KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor

Zhang, Jitao David; Wiemann, Stefan

doi:10.1093/bioinformatics/btp167

Cited by 295 publications

(223 citation statements)

References 12 publications

Supporting

Mentioning

223

Contrasting

Order By: Relevance

“…In the graph representation, each protein is associated with a node (also known as a vertex), and interactions between proteins are associated with edges (connections between pairs of nodes). To generate the actual list of edges (the adjacency list), an external package not provided by KEGG was used, the KEGGgraph package (KEGGgraph can be downloaded from the Bioconductor Web site, http://www.bioconductor.org/) (30). The pathways in KEGG have directional connections (i.e., separate incoming and outgoing paths); however, this information was not required for the computation of the network metrics, and therefore the directionality information was discarded and undirected graphs were generated.…”

Section: Methodsmentioning

confidence: 99%

Molecular signaling network complexity is correlated with cancer patient survivability

Breitkreutz

Hlatky

Rietman

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

101

118

View full text Add to dashboard Cite

The 5-y survival for cancer patients after diagnosis and treatment is strongly dependent on tumor type. Prostate cancer patients have a >99% chance of survival past 5 y after diagnosis, and pancreatic patients have <6% chance of survival past 5 y. Because each cancer type has its own molecular signaling network, we asked if there are "signatures" embedded in these networks that inform us as to the 5-y survival. In other words, are there statistical metrics of the network that correlate with survival? Furthermore, if there are, can such signatures provide clues to selecting new therapeutic targets? From the Kyoto Encyclopedia of Genes and Genomes Cancer Pathway database we computed several conventional and some less conventional network statistics. In particular we found a correlation (R 2 = 0.7) between degree-entropy and 5-y survival based on the Surveillance Epidemiology and End Results database. This correlation suggests that cancers that have a more complex molecular pathway are more refractory than those with less complex molecular pathway. We also found potential new molecular targets for drugs by computing the betweenness-a statistical metric of the centrality of a node-for the molecular networks.network entropy | signaling pathway | degree distribution | prostate cancer | basal cell carcinoma

show abstract

Section: Methodsmentioning

confidence: 99%

Molecular signaling network complexity is correlated with cancer patient survivability

Breitkreutz

Hlatky

Rietman

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

101

118

View full text Add to dashboard Cite

show abstract

“…The KEGG database was used to build the network of pathways based on the relationship between the pathways and compounds in the database [16][17][18]. Similarly, the differentially expressed genes were selected to build genesact-network according to the relationship among the genes, proteins, and compounds in the KEGG database.…”

Section: Analysis Of Gomentioning

confidence: 99%

Gene expression profiling of human bone marrow-derived mesenchymal stem cells during adipogenesis

Yan

et al. 2015

Folia Histochem Cytobiol.

View full text Add to dashboard Cite

Introduction. Adipogenesis comprises multiple processes by which mesenchymal stem cells differentiate into adipocytes. To increase our knowledge of the mechanism underlying adipogenic differentiation of human bone marrow mesenchymal stem cells (hMSCs), we performed full-genome gene expression microarray and gene ontology analyses of induced differentiation of hMSCs. Material and methods. Adipogenic differentiation of hMSCs was induced by an adipogenic medium, and total RNA was extracted from undifferentiated hMSCs (day 0) and differentiated adipocytes (day 14). Then microarray hybridization of RNA samples was performed. The GeneChip Operating Software was used to analyze the hybridization data to identify differentially expressed genes, which were performed Gene Ontology categorization and pathway analysis. Pathway-act-network and genes-act-network were built according to the Kyoto Encyclopedia of Genes and Genomes database. Some differentially expressed genes were subjected to qRT-PCR to verify the microarray data. Results. We detected a total of 3,821 differentially expressed genes, of which 753 were upregulated and 3,068 downregulated. These genes were well represented in a variety of functional categories, including collagen fibril organization, brown fat cell differentiation, cell division, and S phase of mitotic cell cycle. Subsequently, pathway analysis was conducted, and significant pathways (from top 50) were selected for pathway-act-network analysis, which indicated that the mitogen-activated protein kinase (MAPK) pathway and cell cycle were of high degrees (> 10). Gene-act-network analysis showed that insulin-like growth factor 1 receptor (IGF1R), histone deacetylase 1 (HDAC1), HDAC2, MAPK13, MAPK8, phosphoinositide-3-kinase regulatory subunit 1 (PI3KR1), and PI3KR2 also had high degrees (> 18). Conclusions. Collectively, these data provide novel information and could serve as a basis for future study to clarify the mechanisms underlying adipocyte differentiation of hMSCs.

show abstract

“…where σ st is the number of shortest paths from s to t, and σ st (v) is the number of shortest paths from s to t that pass through a vertex v (24)(25)(26)(27)(28).…”

Section: Go Analysismentioning

confidence: 99%

Identification of multi-target effects of Huaier aqueous extract via microarray profiling in triple-negative breast cancer cells

Kong

Ding

Yang

2015

International Journal of Oncology

View full text Add to dashboard Cite

Abstract. Breast cancer is one of the most common malignant tumors in the world. Long-term maintenance treatment is important for breast cancer. However, effective maintenance treatment is lacking for triple-negative breast cancer (TNBC). Traditional Chinese medicine (TCM) has shown its potential anticancer roles as an effective maintenance treatment for TNBC. However its mechanisms remained unclear. In this study, we detected the differentially expressed genes (DEGs) after treatment with Huaier aqueous extract by using microarray profiling in MDA-MB-231 cells. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene-gene interaction network were conducted to confirm the altered biological functions induced by Huaier extract. Screening of DEGs gave 387 genes (226 upregulated and 161 downregulated) in MDA-MB-231 cells which were regulated significantly by Huaier extract. GO and KEGG pathway analysis suggested that a number of functions were affected by Huaier, including proliferation, apoptosis, migration, and angiogenesis. Gene-gene interaction network showed the detailed molecular signal-net. Based on microarray data, we studied several functions of Huaier extract and in return verified the results of microarray profiling. This study had important guidance roles and indicated new research directions.

show abstract

KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor

Cited by 295 publications

References 12 publications

Molecular signaling network complexity is correlated with cancer patient survivability

Molecular signaling network complexity is correlated with cancer patient survivability

Gene expression profiling of human bone marrow-derived mesenchymal stem cells during adipogenesis

Identification of multi-target effects of Huaier aqueous extract via microarray profiling in triple-negative breast cancer cells

Contact Info

Product

Resources

About