Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 1 to 12 of 15 entries
Sorted by: Best Match Show Resources per page
The Reactome BioMart.

Database : the journal of biological databases and curation

Haw RA, Croft D, Yung CK, Ndegwa N, D'Eustachio P, Hermjakob H, Stein LD.
PMID: 22012987
Database (Oxford). 2011 Oct 19;2011:bar031. doi: 10.1093/database/bar031. Print 2011.

Reactome is an open source, expert-authored, manually curated and peer-reviewed database of reactions, pathways and biological processes. We provide an intuitive web-based user interface to pathway knowledge and a suite of data analysis tools. The Reactome BioMart provides biologists...

Cite
Haw RA, Croft D, Yung CK, et al. The Reactome BioMart. Database (Oxford). 2011;2011:bar031doi: 10.1093/database/bar031.
Haw, R. A., Croft, D., Yung, C. K., Ndegwa, N., D'Eustachio, P., Hermjakob, H., & Stein, L. D. (2011). The Reactome BioMart. Database : the journal of biological databases and curation, 2011bar031. https://doi.org/10.1093/database/bar031
Haw, Robin A, et al. "The Reactome BioMart." Database : the journal of biological databases and curation vol. 2011 (2011): bar031. doi: https://doi.org/10.1093/database/bar031
Haw RA, Croft D, Yung CK, Ndegwa N, D'Eustachio P, Hermjakob H, Stein LD. The Reactome BioMart. Database (Oxford). 2011 Oct 19;2011:bar031. doi: 10.1093/database/bar031. Print 2011. PMID: 22012987; PMCID: PMC3197281.
Copy Download .nbib Format: NLM
Network-Based Predictors of Progression in Head and Neck Squamous Cell Carcinoma.

Frontiers in genetics

Sanati N, Iancu OD, Wu G, Jacobs JE, McWeeney SK.
PMID: 29910823
Front Genet. 2018 May 29;9:183. doi: 10.3389/fgene.2018.00183. eCollection 2018.

The heterogeneity in head and neck squamous cell carcinoma (HNSCC) has made reliable stratification extremely challenging. Behavioral risk factors such as smoking and alcohol consumption contribute to this heterogeneity. To help elucidate potential mechanisms of progression in HNSCC, we...

Cite
Sanati N, Iancu OD, Wu G, et al. Network-Based Predictors of Progression in Head and Neck Squamous Cell Carcinoma. Front Genet. 2018;9:183doi: 10.3389/fgene.2018.00183.
Sanati, N., Iancu, O. D., Wu, G., Jacobs, J. E., & McWeeney, S. K. (2018). Network-Based Predictors of Progression in Head and Neck Squamous Cell Carcinoma. Frontiers in genetics, 9183. https://doi.org/10.3389/fgene.2018.00183
Sanati, Nasim, et al. "Network-Based Predictors of Progression in Head and Neck Squamous Cell Carcinoma." Frontiers in genetics vol. 9 (2018): 183. doi: https://doi.org/10.3389/fgene.2018.00183
Sanati N, Iancu OD, Wu G, Jacobs JE, McWeeney SK. Network-Based Predictors of Progression in Head and Neck Squamous Cell Carcinoma. Front Genet. 2018 May 29;9:183. doi: 10.3389/fgene.2018.00183. eCollection 2018. PMID: 29910823; PMCID: PMC5992410.
Copy Download .nbib Format: NLM
Author-sourced capture of pathway knowledge in computable form using Biofactoid.

eLife

Wong JV, Franz M, Siper MC, Fong D, Durupinar F, Dallago C, Luna A, Giorgi J, Rodchenkov I, Babur Ö, Bachman JA, Gyori BM, Demir E, Bader GD, Sander C.
PMID: 34860157
Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292.

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a...

Cite
Wong JV, Franz M, Siper MC, et al. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021;10doi: 10.7554/eLife.68292.
Wong, J. V., Franz, M., Siper, M. C., Fong, D., Durupinar, F., Dallago, C., Luna, A., Giorgi, J., Rodchenkov, I., Babur, �. �., Bachman, J. A., Gyori, B. M., Demir, E., Bader, G. D., & Sander, C. (2021). Author-sourced capture of pathway knowledge in computable form using Biofactoid. eLife, 10. https://doi.org/10.7554/eLife.68292
Wong, Jeffrey V, et al. "Author-sourced capture of pathway knowledge in computable form using Biofactoid." eLife vol. 10 (2021). doi: https://doi.org/10.7554/eLife.68292
Wong JV, Franz M, Siper MC, Fong D, Durupinar F, Dallago C, Luna A, Giorgi J, Rodchenkov I, Babur Ö, Bachman JA, Gyori BM, Demir E, Bader GD, Sander C. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292. PMID: 34860157.
Copy Download .nbib Format: NLM
Using Reactome to build an autophagy mechanism knowledgebase.

Autophagy

Varusai TM, Jupe S, Sevilla C, Matthews L, Gillespie M, Stein L, Wu G, D'Eustachio P, Metzakopian E, Hermjakob H.
PMID: 32486891
Autophagy. 2021 Jun;17(6):1543-1554. doi: 10.1080/15548627.2020.1761659. Epub 2020 Jun 02.

The 21st century has revealed much about the fundamental cellular process of autophagy. Autophagy controls the catabolism and recycling of various cellular components both as a constitutive process and as a response to stress and foreign material invasion. There...

Cite
Varusai TM, Jupe S, Sevilla C, et al. Using Reactome to build an autophagy mechanism knowledgebase. Autophagy. 2020;17(6):1543-1554doi: 10.1080/15548627.2020.1761659.
Varusai, T. M., Jupe, S., Sevilla, C., Matthews, L., Gillespie, M., Stein, L., Wu, G., D'Eustachio, P., Metzakopian, E., & Hermjakob, H. (2021). Using Reactome to build an autophagy mechanism knowledgebase. Autophagy, 17(6), 1543-1554. https://doi.org/10.1080/15548627.2020.1761659
Varusai, Thawfeek Mohamed, et al. "Using Reactome to build an autophagy mechanism knowledgebase." Autophagy vol. 17,6 (2021): 1543-1554. doi: https://doi.org/10.1080/15548627.2020.1761659
Varusai TM, Jupe S, Sevilla C, Matthews L, Gillespie M, Stein L, Wu G, D'Eustachio P, Metzakopian E, Hermjakob H. Using Reactome to build an autophagy mechanism knowledgebase. Autophagy. 2021 Jun;17(6):1543-1554. doi: 10.1080/15548627.2020.1761659. Epub 2020 Jun 02. PMID: 32486891; PMCID: PMC8204961.
Copy Download .nbib Format: NLM
ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis.

F1000Research

Wu G, Dawson E, Duong A, Haw R, Stein L.
PMID: 25309732
F1000Res. 2014 Jul 01;3:146. doi: 10.12688/f1000research.4431.2. eCollection 2014.

High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded...

Cite
Wu G, Dawson E, Duong A, et al. ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis. F1000Res. 2014;3:146doi: 10.12688/f1000research.4431.2.
Wu, G., Dawson, E., Duong, A., Haw, R., & Stein, L. (2014). ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis. F1000Research, 3146. https://doi.org/10.12688/f1000research.4431.2
Wu, Guanming, et al. "ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis." F1000Research vol. 3 (2014): 146. doi: https://doi.org/10.12688/f1000research.4431.2
Wu G, Dawson E, Duong A, Haw R, Stein L. ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis. F1000Res. 2014 Jul 01;3:146. doi: 10.12688/f1000research.4431.2. eCollection 2014. PMID: 25309732; PMCID: PMC4184317.
Copy Download .nbib Format: NLM
Annotating cancer variants and anti-cancer therapeutics in reactome.

Cancers

Milacic M, Haw R, Rothfels K, Wu G, Croft D, Hermjakob H, D'Eustachio P, Stein L.
PMID: 24213504
Cancers (Basel). 2012 Nov 08;4(4):1180-211. doi: 10.3390/cancers4041180.

Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our...

Cite
Milacic M, Haw R, Rothfels K, et al. Annotating cancer variants and anti-cancer therapeutics in reactome. Cancers (Basel). 2012;4(4):1180-211doi: 10.3390/cancers4041180.
Milacic, M., Haw, R., Rothfels, K., Wu, G., Croft, D., Hermjakob, H., D'Eustachio, P., & Stein, L. (2012). Annotating cancer variants and anti-cancer therapeutics in reactome. Cancers, 4(4), 1180-211. https://doi.org/10.3390/cancers4041180
Milacic, Marija, et al. "Annotating cancer variants and anti-cancer therapeutics in reactome." Cancers vol. 4,4 (2012): 1180-211. doi: https://doi.org/10.3390/cancers4041180
Milacic M, Haw R, Rothfels K, Wu G, Croft D, Hermjakob H, D'Eustachio P, Stein L. Annotating cancer variants and anti-cancer therapeutics in reactome. Cancers (Basel). 2012 Nov 08;4(4):1180-211. doi: 10.3390/cancers4041180. PMID: 24213504; PMCID: PMC3712731.
Copy Download .nbib Format: NLM
Reactome and the Gene Ontology: Digital convergence of data resources.

Bioinformatics (Oxford, England)

Good BM, Van Auken K, Hill DP, Mi H, Carbon S, Balhoff JP, Albou LP, Thomas PD, Mungall CJ, Blake JA, D'Eustachio P.
PMID: 33964129
Bioinformatics. 2021 May 08; doi: 10.1093/bioinformatics/btab325. Epub 2021 May 08.

MOTIVATION: GO Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions, and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of...

Cite
Good BM, Van Auken K, Hill DP, et al. Reactome and the Gene Ontology: Digital convergence of data resources. Bioinformatics. 2021;doi: 10.1093/bioinformatics/btab325.
Good, B. M., Van Auken, K., Hill, D. P., Mi, H., Carbon, S., Balhoff, J. P., Albou, L. P., Thomas, P. D., Mungall, C. J., Blake, J. A., & D'Eustachio, P. (2021). Reactome and the Gene Ontology: Digital convergence of data resources. Bioinformatics (Oxford, England), . https://doi.org/10.1093/bioinformatics/btab325
Good, Benjamin M, et al. "Reactome and the Gene Ontology: Digital convergence of data resources." Bioinformatics (Oxford, England) vol. (2021). doi: https://doi.org/10.1093/bioinformatics/btab325
Good BM, Van Auken K, Hill DP, Mi H, Carbon S, Balhoff JP, Albou LP, Thomas PD, Mungall CJ, Blake JA, D'Eustachio P. Reactome and the Gene Ontology: Digital convergence of data resources. Bioinformatics. 2021 May 08; doi: 10.1093/bioinformatics/btab325. Epub 2021 May 08. PMID: 33964129; PMCID: PMC8504636.
Copy Download .nbib Format: NLM
Author-sourced capture of pathway knowledge in computable form using Biofactoid.

eLife

Wong JV, Franz M, Siper MC, Fong D, Durupinar F, Dallago C, Luna A, Giorgi J, Rodchenkov I, Babur Ö, Bachman JA, Gyori BM, Demir E, Bader GD, Sander C.
PMID: 34860157
Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292.

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a...

Cite
Wong JV, Franz M, Siper MC, et al. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021;10doi: 10.7554/eLife.68292.
Wong, J. V., Franz, M., Siper, M. C., Fong, D., Durupinar, F., Dallago, C., Luna, A., Giorgi, J., Rodchenkov, I., Babur, �. �., Bachman, J. A., Gyori, B. M., Demir, E., Bader, G. D., & Sander, C. (2021). Author-sourced capture of pathway knowledge in computable form using Biofactoid. eLife, 10. https://doi.org/10.7554/eLife.68292
Wong, Jeffrey V, et al. "Author-sourced capture of pathway knowledge in computable form using Biofactoid." eLife vol. 10 (2021). doi: https://doi.org/10.7554/eLife.68292
Wong JV, Franz M, Siper MC, Fong D, Durupinar F, Dallago C, Luna A, Giorgi J, Rodchenkov I, Babur Ö, Bachman JA, Gyori BM, Demir E, Bader GD, Sander C. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292. PMID: 34860157; PMCID: PMC8683078.
Copy Download .nbib Format: NLM
Perform Pathway Enrichment Analysis Using ReactomeFIViz.

Methods in molecular biology (Clifton, N.J.)

Haw R, Loney F, Ong E, He Y, Wu G.
PMID: 31583638
Methods Mol Biol. 2020;2074:165-179. doi: 10.1007/978-1-4939-9873-9_13.

Modern large-scale biological data analysis often generates a set of significant genes, frequently associated with scores. Pathway-based approaches are routinely performed to understand the functional contexts of these genes. Reactome is the most comprehensive open-access biological pathway knowledge base,...

Cite
Haw R, Loney F, Ong E, et al. Perform Pathway Enrichment Analysis Using ReactomeFIViz. Methods Mol Biol. 2020;2074:165-179doi: 10.1007/978-1-4939-9873-9_13.
Haw, R., Loney, F., Ong, E., He, Y., & Wu, G. (2020). Perform Pathway Enrichment Analysis Using ReactomeFIViz. Methods in molecular biology (Clifton, N.J.), 2074165-179. https://doi.org/10.1007/978-1-4939-9873-9_13
Haw, Robin, et al. "Perform Pathway Enrichment Analysis Using ReactomeFIViz." Methods in molecular biology (Clifton, N.J.) vol. 2074 (2020): 165-179. doi: https://doi.org/10.1007/978-1-4939-9873-9_13
Haw R, Loney F, Ong E, He Y, Wu G. Perform Pathway Enrichment Analysis Using ReactomeFIViz. Methods Mol Biol. 2020;2074:165-179. doi: 10.1007/978-1-4939-9873-9_13. PMID: 31583638.
Copy Download .nbib Format: NLM
Automation of ReactomeFIViz via CyREST API.

F1000Research

Loney F, Wu G.
PMID: 29946442
F1000Res. 2018 May 02;7:531. doi: 10.12688/f1000research.14776.2. eCollection 2018.

Pathway- and network-based approaches project seemingly unrelated genes onto the context of pathways and networks, enhancing the analysis power that cannot be achieved via gene-based approaches. Pathway and network approaches are routinely applied in large-scale data analysis for cancer...

Cite
Loney F, Wu G. Automation of ReactomeFIViz via CyREST API. F1000Res. 2018;7:531doi: 10.12688/f1000research.14776.2.
Loney, F., & Wu, G. (2018). Automation of ReactomeFIViz via CyREST API. F1000Research, 7531. https://doi.org/10.12688/f1000research.14776.2
Loney, Fred, and Wu, Guanming. "Automation of ReactomeFIViz via CyREST API." F1000Research vol. 7 (2018): 531. doi: https://doi.org/10.12688/f1000research.14776.2
Loney F, Wu G. Automation of ReactomeFIViz via CyREST API. F1000Res. 2018 May 02;7:531. doi: 10.12688/f1000research.14776.2. eCollection 2018. PMID: 29946442; PMCID: PMC5998009.
Copy Download .nbib Format: NLM
ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis.

F1000Research

Wu G, Dawson E, Duong A, Haw R, Stein L.
PMID: 25309732
F1000Res. 2014 Jul 01;3:146. doi: 10.12688/f1000research.4431.1. eCollection 2014.

High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded...

Cite
Wu G, Dawson E, Duong A, et al. ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis. F1000Res. 2014;3:146doi: 10.12688/f1000research.4431.1.
Wu, G., Dawson, E., Duong, A., Haw, R., & Stein, L. (2014). ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis. F1000Research, 3146. https://doi.org/10.12688/f1000research.4431.1
Wu, Guanming, et al. "ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis." F1000Research vol. 3 (2014): 146. doi: https://doi.org/10.12688/f1000research.4431.1
Wu G, Dawson E, Duong A, Haw R, Stein L. ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis. F1000Res. 2014 Jul 01;3:146. doi: 10.12688/f1000research.4431.1. eCollection 2014. PMID: 25309732.
Copy Download .nbib Format: NLM
Author-sourced capture of pathway knowledge in computable form using Biofactoid.

eLife

Wong JV, Franz M, Siper MC, Fong D, Durupinar F, Dallago C, Luna A, Giorgi JM, Rodchenkov I, Babur Ö, Bachman JA, Gyori B, Demir E, Bader GD, Sander C.
PMID: 34860157
Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292. Epub 2021 Dec 03.

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a...

Cite
Wong JV, Franz M, Siper MC, et al. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021;10doi: 10.7554/eLife.68292.
Wong, J. V., Franz, M., Siper, M. C., Fong, D., Durupinar, F., Dallago, C., Luna, A., Giorgi, J. M., Rodchenkov, I., Babur, �. �., Bachman, J. A., Gyori, B., Demir, E., Bader, G. D., & Sander, C. (2021). Author-sourced capture of pathway knowledge in computable form using Biofactoid. eLife, 10. https://doi.org/10.7554/eLife.68292
Wong, Jeffrey V, et al. "Author-sourced capture of pathway knowledge in computable form using Biofactoid." eLife vol. 10 (2021). doi: https://doi.org/10.7554/eLife.68292
Wong JV, Franz M, Siper MC, Fong D, Durupinar F, Dallago C, Luna A, Giorgi JM, Rodchenkov I, Babur Ö, Bachman JA, Gyori B, Demir E, Bader GD, Sander C. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292. Epub 2021 Dec 03. PMID: 34860157.
Copy Download .nbib Format: NLM
Showing 1 to 12 of 15 entries