Online Predicted Human Interaction Database

Brown, Kevin R.; Jurišica, Igor

doi:10.1093/bioinformatics/bti273

Cited by 549 publications

(435 citation statements)

References 41 publications

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“…(ii) Annotation and enrichment analysis using 25 KEGG signaling pathways and cellular processes (Table S4C). (iii) Matching of differentially expressed genes to PPIs in I2D v1.72 (14,15) with additional PPI updates. Experimental PPI networks were generated by querying I2D with the target genes/proteins to obtain their immediate interacting proteins.…”

Section: Methodsmentioning

confidence: 99%

“…Although the number of overlapped genes was small, GO analysis still showed that these genes were enriched in genes of the extracellular region (9/14, P = 0.006) and KEGG pathways, including ECM-receptor interaction (3/14, P = 0.005) and focal adhesion (3/14, P = 0.01), which was in agreement with findings in the CAF vs. NF and tumor stroma vs. normal lung. Ten of the 14 genes were also mapped to protein-protein interactions (PPIs) in Interolog Interaction Database (I2D) v1.72 (14,15). Nine of the 10 genes/proteins interact via shared neighboring proteins (Fig.…”

Section: Shared Differentially Expressed Genes Of Caf and Tumor Stromamentioning

confidence: 99%

See 1 more Smart Citation

Prognostic gene-expression signature of carcinoma-associated fibroblasts in non-small cell lung cancer

Navab

Strumpf

Bandarchi

et al. 2011

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

316

302

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The tumor microenvironment strongly influences cancer development, progression, and metastasis. The role of carcinoma-associated fibroblasts (CAFs) in these processes and their clinical impact has not been studied systematically in non-small cell lung carcinoma (NSCLC). We established primary cultures of CAFs and matched normal fibroblasts (NFs) from 15 resected NSCLC. We demonstrate that CAFs have greater ability than NFs to enhance the tumorigenicity of lung cancer cell lines. Microarray gene-expression analysis of the 15 matched CAF and NF cell lines identified 46 differentially expressed genes, encoding for proteins that are significantly enriched for extracellular proteins regulated by the TGF-β signaling pathway. We have identified a subset of 11 genes (13 probe sets) that formed a prognostic gene-expression signature, which was validated in multiple independent NSCLC microarray datasets. Functional annotation using protein-protein interaction analyses of these and published cancer stroma-associated gene-expression changes revealed prominent involvement of the focal adhesion and MAPK signaling pathways. Fourteen (30%) of the 46 genes also were differentially expressed in laser-capture-microdissected corresponding primary tumor stroma compared with the matched normal lung. Six of these 14 genes could be induced by TGF-β1 in NF. The results establish the prognostic impact of CAF-associated gene-expression changes in NSCLC patients.integrin α11 | NAViGaTOR | adenocarcinoma | extracellular matrix

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Section: Methodsmentioning

confidence: 99%

Section: Shared Differentially Expressed Genes Of Caf and Tumor Stromamentioning

confidence: 99%

Prognostic gene-expression signature of carcinoma-associated fibroblasts in non-small cell lung cancer

Navab

Strumpf

Bandarchi

et al. 2011

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

316

302

View full text Add to dashboard Cite

show abstract

“…Link Content NCBI Gene [66] www.ncbi.nlm.nih.gov/gene Atlas of 59,500 human genes GOA [67] www.ebi.ac.uk/GOA 487,409 Gene Ontology annotations for 48,569 human gene products ENCODE [68] www.encodeproject.org Functional annotations of coding/non-coding DNA elements NCBI Epigenomics [69] www.ncbi.nlm.nih.gov/epigenomics 5,110 epigenetic modifications 4DGenome [70] 4dgenome [73] www.ebi.ac.uk/gxa Differential and baseline gene expression data CMAP [74] www.broadinstitute.org/cmap ∼ 7,000 expression profiles for 1,309 perturbagen compounds COXPRESdb [75] coxpresdb.jp Co-expression of 19,803 human genes GeneFriends [76] genefriends.org Co-expression of 159,184 human genes and transcripts UniProt [77] www.uniprot.org Information about human proteome (69,693 proteins) NeXtProt [78] www.nextprot.org Knowledgebase on 20,066 human proteins RCSB PDB [79] www.rcsb.org/pdb Portal to 113,494 biological macromolecular 3D-structures HPA [80] www.thehpp.org Maps of human proteome on 44 normal and 20 cancer type tissues IntAct [81] www.ebi.ac.uk/intact 209,852 human protein-protein interactions BioGrid [82] thebiogrid.org 215,952 human protein-protein interactions I2D [83] ophid.utoronto.ca 183,524 (+ 55,985 predicted) protein-protein interactions STRING [84] string-db.org 8,548,005 interactions between 20,457 proteins HMDB [85] www.hmdb.ca Atlas of 41,993 human metabolites KEGG Pathway [86] www.genome.jp/kegg/pathway 298 human pathways SMPD [87] www.smpdb.ca ∼700 human metabolic and disease pathways Reactome [88] www.reactome.org 8,770 reactions in 1,887 human pathways SugarBindDB [89] sugarbind.expasy.org 1,256 interactions between 200 glycans and 551 pathogenic agents UniCarbKB [90] www.unicarbkb.org 3,740 glycan structure entries and 400 glycoproteins KEGG Glycan [91] www.genome.jp/kegg/glycan/ Glycan metabolic pathways OMIM [92] www.omim.org Catalog of mendelian disorders and over 15,000 genes NCBI dbGaP [93] www.ncbi.nlm.nih.gov/gap Database of genotypes and phenotypes GWAS Catalog [94] www.ebi.ac.uk/gwas/ Genome wide association studies, assaying ∼ 100,000 SNPs COSMIC...…”

Section: Databasementioning

confidence: 99%

Integrative methods for analyzing big data in precision medicine

2016

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We provide an overview of recent developments in big data analyses in the context of precision medicine and health informatics. With the advance in technologies capturing molecular and medical data, we entered the area of Big Data in biology and medicine. These data offer many opportunities to advance precision medicine.We outline key challenges in precision medicine and present recent advances in data integrationbased methods to uncover personalized information from big data produced by various omics studies. We survey recent integrative methods for disease subtyping, bio-markers discovery and drug repurposing, and list the tools that are available to domain scientists. Given the ever-growing nature of these big data, we highlight key issues that big data integration methods will face.

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“…PPI data were imported from eight existing PPI databases, including the Human Annotated and Predicted Protein Interaction Database (HAPPI) [23] , Reactome [24] , Online Predicted Human Interaction Database (OPHID) [25] , InAct [26] , Human Protein Reference Database (HPRD) [27] , Molecular Interaction Database (MINT) [28] , Database of Interacting Proteins (DIP) [29] , and PDZBase [30] . Detailed information about these PPI databases is described in Supplementary Table S3.…”

Section: Protein-protein Interaction (Ppi) Datamentioning

confidence: 99%

Deciphering the pharmacological mechanism of the Chinese formula Huanglian-Jie-Du decoction in the treatment of ischemic stroke using a systems biology-based strategy

et al. 2015

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Aim: Huanglian-Jie-Du decoction (HLJDD) is an important multiherb remedy in TCM, which is recently demonstrated to be effective to treat ischemic stroke. Here, we aimed to investigate the pharmacological mechanisms of HLJDD in the treatment of ischemic stroke using systems biology approaches. Methods: Putative targets of HLJDD were predicted using MetaDrug. An interaction network of putative HLJDD targets and known therapeutic targets for the treatment of ischemic stroke was then constructed, and candidate HLJDD targets were identified by calculating topological features, including 'Degree', 'Node-betweenness', 'Closeness', and 'K-coreness'. The binding efficiencies of the candidate HLJDD targets with the corresponding compositive compounds were further validated by a molecular docking simulation. Results: A total of 809 putative targets were obtained for 168 compositive compounds in HLJDD. Additionally, 39 putative targets were common to all four herbs of HLJDD. Next, 49 major nodes were identified as candidate HLJDD targets due to their network topological importance. The enrichment analysis based on the Gene Ontology (GO) annotation system and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that candidate HLJDD targets were more frequently involved in G-protein-coupled receptor signaling pathways, neuroactive ligand-receptor interactions and gap junctions, which all played important roles in the progression of ischemic stroke. Finally, the molecular docking simulation showed that 170 pairs of chemical components and candidate HLJDD targets had strong binding efficiencies. Conclusion: This study has developed for the first time a comprehensive systems approach integrating drug target prediction, network analysis and molecular docking simulation to reveal the relationships between the herbs contained in HLJDD and their putative targets and ischemic stroke-related pathways.

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Online Predicted Human Interaction Database

Abstract: http://ophid.utoronto.ca/supplInfo.pdf.

Cited by 549 publications

References 41 publications

Prognostic gene-expression signature of carcinoma-associated fibroblasts in non-small cell lung cancer

Prognostic gene-expression signature of carcinoma-associated fibroblasts in non-small cell lung cancer

Integrative methods for analyzing big data in precision medicine

Deciphering the pharmacological mechanism of the Chinese formula Huanglian-Jie-Du decoction in the treatment of ischemic stroke using a systems biology-based strategy

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