Biological Network Exploration with Cytoscape 3

Su, Gang; Morris, John H.; Demchak, Barry; Bader, Gary D.

doi:10.1002/0471250953.bi0813s47

Cited by 826 publications

(705 citation statements)

References 42 publications

Supporting

Mentioning

681

Contrasting

Unclassified

Order By: Relevance

“…Only Gene Ontology (terms) and Kyoto Encyclopedia Genes and Genomes (KEGG) pathways with p-value < 0.05 were retained. Besides, associations among significant GO terms were explored and visualized through enrichmentMap plug-in [27] of Cytoscape software [28].…”

Section: Functional Enrichment Analysismentioning

confidence: 99%

A Six-LncRNA Expression Signature Associated with Prognosis of Colorectal Cancer Patients

Zhao

Shang

et al. 2018

Cell Physiol Biochem

View full text Add to dashboard Cite

Background/Aims: Colorectal cancer (CRC) is one of the most common malignant tumor with high migration and invasion capacity. Long non-coding RNAs (lncRNAs) have been identified to influence multiple cancers progression through competitively binding microRNAs (miRNAs). In this study, we proposed to develop a lncRNA-based signature for CRC survival outcomes. Methods: LncRNA expression profiles of CRC patients were extracted from the Gene Expression Omnibus (GEO) data sets GSE38832 (training set) and GSE29621 (testing set) . Associations between lncRNA expression and CRC disease free survival (DFS) were evaluated through univariate Cox regression analysis, and prognosis signature constructed by combination of weighted lncRNA expression values were obtained through multivariate Cox regression analysis. Robustness of the prognosis signature was evaluated through receiver operating characteristics analysis in the testing set. Results: A weighted prognosis signature of six lncRNAs, including LINC01583, LINC00276, LUNAR1, DKFZp434J0226, SFTA1P and OGFOD3, was yielded from multivariate Cox regression analysis. Samples with significantly different DFS dislayed distinct signatures, indicating considerable predictory accuracy of this expression signature. Conclusion: Robustness of the prognosis signature was evaluated in the testing set through Kaplan-Meier and receiver operating characteristics (ROC) analysis. Furthermore, functional enrichment analysis of lncRNAs suggested significant enrichment of cancer related pathways. Our results revealed the promise of lncRNAs as prognostic biomarkers.

show abstract

Section: Functional Enrichment Analysismentioning

confidence: 99%

A Six-LncRNA Expression Signature Associated with Prognosis of Colorectal Cancer Patients

Zhao

Shang

et al. 2018

Cell Physiol Biochem

View full text Add to dashboard Cite

show abstract

“…We recently developed the infrastructure to perform these tasks via a web interface at gnps.ucsd.edu/ProteoSAFe/static/gnps-splash.jsp (40). The resulting network is then exported and visualized in Cytoscape software (41,42) with nodes connected by edges where each node corresponds to a consensus MS/MS spectra.…”

Section: Molecular Networking To Characterize Matched Chemicals Betwementioning

confidence: 99%

Lifestyle chemistries from phones for individual profiling

Bouslimani

Melnik

et al. 2016

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

View full text Add to dashboard Cite

Imagine a scenario where personal belongings such as pens, keys, phones, or handbags are found at an investigative site. It is often valuable to the investigative team that is trying to trace back the belongings to an individual to understand their personal habits, even when DNA evidence is also available. Here, we develop an approach to translate chemistries recovered from personal objects such as phones into a lifestyle sketch of the owner, using mass spectrometry and informatics approaches. Our results show that phones' chemistries reflect a personalized lifestyle profile. The collective repertoire of molecules found on these objects provides a sketch of the lifestyle of an individual by highlighting the type of hygiene/beauty products the person uses, diet, medical status, and even the location where this person may have been. These findings introduce an additional form of trace evidence from skin-associated lifestyle chemicals found on personal belongings. Such information could help a criminal investigator narrowing down the owner of an object found at a crime scene, such as a suspect or missing person.skin | phones | lifestyle chemistries | trace evidence

show abstract

“…Subsequently, Cytoscape software v3.5.0 (http://www. cytoscape.org/index.html) (20) was used for visualization of the PPI network, in which nodes represented genes and edges represented interactions between genes. The degree of a node was defined as the number of direct interactions between the corresponding gene and others in the network.…”

Section: Methodsmentioning

confidence: 99%

Gene expression profiling and bioinformatics analysis of hereditary gingival fibromatosis

Fang

Wang²,

Chen

2017

biom rep

View full text Add to dashboard Cite

Abstract. Hereditary gingival fibromatosis (HGF) is a benign, non-hemorrhagic and fibrous gingival overgrowth that may cover all or part of the teeth. It typically interferes with speech, lip closure and chewing, and can also be a psychological burden that affects the self-esteem of patients. Owing to high genetic heterogeneity, genetic testing to confirm diagnosis is not justified. It is therefore important to identify key signature genes and to understand the molecular mechanisms underlying HGF. The aim of the present study was to determine HGF-related genes and to analyze these genes through bioinformatics methods. A total of 249 differentially expressed genes (DEGs), consisting of 65 upregulated and 184 downregulated genes, were identified in the GSE4250 dataset of Gene Expression Omnibus (GEO) when comparing with the gums of HGF patients with those of healthy controls using the affy and limma packages in R. Subsequently, 28 enriched gene ontology terms were obtained from the Database for Annotation, Visualization and Integrated Discovery, and a protein-protein interaction (PPI) network was constructed and analyzed using STRING and Cytoscape. There were 99 nodes and 118 edges in the PPI network of these DEGs obtained through STRING. Among these nodes, 12 core genes were identified, of which the highest degree node was the gene for POTE ankyrin domain family member I. Collectively the results indicate that bioinformatics methods may provide effective strategies for predicting HGF-related genes and for understanding the molecular mechanisms of HGF.

show abstract

Biological Network Exploration with Cytoscape 3

Cited by 826 publications

References 42 publications

A Six-LncRNA Expression Signature Associated with Prognosis of Colorectal Cancer Patients

A Six-LncRNA Expression Signature Associated with Prognosis of Colorectal Cancer Patients

Lifestyle chemistries from phones for individual profiling

Gene expression profiling and bioinformatics analysis of hereditary gingival fibromatosis

Contact Info

Product

Resources

About