publication . Article . 2017

NFP: An R Package for Characterizing and Comparing of Annotated Biological Networks.

Cao, Yang; Xu, Wenjian; Niu, Chao; Bo, Xiaochen; Li, Fei;
Open Access
  • Published: 01 Feb 2017 Journal: BioMed Research International, volume 2,017, pages 1-5 (issn: 2314-6133, eissn: 2314-6141, Copyright policy)
  • Publisher: Hindawi Limited
Abstract
<jats:p>Large amounts of various biological networks exist for representing different types of interaction data, such as genetic, metabolic, gene regulatory, and protein-protein relationships. Recent approaches on biological network study are based on different mathematical concepts. It is necessary to construct a uniform framework to judge the functionality of biological networks. We recently introduced a knowledge-based computational framework that reliably characterized biological networks in system level. The method worked by making systematic comparisons to a set of well-studied “basic networks,” measuring both the functional and topological similarities. A...
Subjects
free text keywords: Medicine, R, Article Subject, Research Article
26 references, page 1 of 2

Gligorijević, V., Pržulj, N.. Methods for biological data integration: perspectives and challenges. Journal of the Royal Society Interface . 2015; 12 (112) [OpenAIRE] [] [DOI]

Barabási, A.-L., Oltvai, Z. N.. Network biology: understanding the cell's functional organization. Nature Reviews Genetics . 2004; 5 (2): 101-113 [OpenAIRE] [] [DOI]

Yu, D., Kim, M., Xiao, G., Hwang, T. H.. Review of biological network data and its applications. Genomics & Informatics . 2013; 11 (4): 200-210 [OpenAIRE] [DOI]

Hayes, W., Sun, K., Pržulj, N.. Graphlet-based measures are suitable for biological network comparison. Bioinformatics . 2013; 29 (4): 483-491 [OpenAIRE] [] [DOI]

Kanehisa, M., Goto, S., Sato, Y., Furumichi, M., Tanabe, M.. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Research . 2012; 40 (1): D109-D114 [OpenAIRE] [] [DOI]

Joshi-Tope, G., Gillespie, M., Vastrik, I., D'Eustachio, P., Schmidt, E., de Bono, B., Jassal, B., Gopinath, G. R., Wu, G. R., Matthews, L., Lewis, S., Birney, E., Stein, L.. Reactome: a knowledgebase of biological pathways. Nucleic Acids Research . 2005; 33: D428-D432 [OpenAIRE] [] [DOI]

Peri, S., Navarro, J. D., Kristiansen, T. Z., Amanchy, R., Surendranath, V., Muthusamy, B., Gandhi, T. K. B., Chandrika, K. N., Deshpande, N., Suresh, S., Rashmi, B. P., Shanker, K., Padma, N., Niranjan, V., Harsha, H. C., Talreja, N., Vrushabendra, B. M., Ramya, M. A., Yatish, A. J., Joy, M., Shivashankar, H. N., Kavitha, M. P., Menezes, M., Choudhury, D. R., Ghosh, N., Saravana, R., Chandran, S., Mohan, S., Jonnalagadda, C. K., Prasad, C. K., Kumar-Sinha, C., Deshpande, K. S., Pandey, A.. Human protein reference database as a discovery resource for proteomics. Nucleic Acids Research . 2004; 32: D497-D501 [OpenAIRE] [] [DOI]

Cui, X., He, H., He, F., Wang, S., Li, F., Bo, X.. Network fingerprint: a knowledge-based characterization of biomedical networks. Scientific Reports . 2015; 5, article 13286 [OpenAIRE] [DOI]

Le Novere, N.. Quantitative and logic modelling of molecular and gene networks. Nature Reviews Genetics . 2015; 16 (3): 146-158 [OpenAIRE] [] [DOI]

Frey, B. J., Dueck, D.. Clustering by passing messages between data points. Science . 2007; 315 (5814): 972-976 [OpenAIRE] [] [DOI]

Csardi, G., Nepusz, T.. The igraph software package for complex network research. International Journal of Complex Systems . 2006; 1695 (5): 1-9

Gentleman, R., Whalen, E., Huber, W., Falcon, S.. Graph: a package to handle graph data structures. R Package . 2009

Wickham, H.. Ggplot2: Elegant Graphics for Data Analysis . 2009

26 references, page 1 of 2
Abstract
<jats:p>Large amounts of various biological networks exist for representing different types of interaction data, such as genetic, metabolic, gene regulatory, and protein-protein relationships. Recent approaches on biological network study are based on different mathematical concepts. It is necessary to construct a uniform framework to judge the functionality of biological networks. We recently introduced a knowledge-based computational framework that reliably characterized biological networks in system level. The method worked by making systematic comparisons to a set of well-studied “basic networks,” measuring both the functional and topological similarities. A...
Subjects
free text keywords: Medicine, R, Article Subject, Research Article
26 references, page 1 of 2

Gligorijević, V., Pržulj, N.. Methods for biological data integration: perspectives and challenges. Journal of the Royal Society Interface . 2015; 12 (112) [OpenAIRE] [] [DOI]

Barabási, A.-L., Oltvai, Z. N.. Network biology: understanding the cell's functional organization. Nature Reviews Genetics . 2004; 5 (2): 101-113 [OpenAIRE] [] [DOI]

Yu, D., Kim, M., Xiao, G., Hwang, T. H.. Review of biological network data and its applications. Genomics & Informatics . 2013; 11 (4): 200-210 [OpenAIRE] [DOI]

Hayes, W., Sun, K., Pržulj, N.. Graphlet-based measures are suitable for biological network comparison. Bioinformatics . 2013; 29 (4): 483-491 [OpenAIRE] [] [DOI]

Kanehisa, M., Goto, S., Sato, Y., Furumichi, M., Tanabe, M.. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Research . 2012; 40 (1): D109-D114 [OpenAIRE] [] [DOI]

Joshi-Tope, G., Gillespie, M., Vastrik, I., D'Eustachio, P., Schmidt, E., de Bono, B., Jassal, B., Gopinath, G. R., Wu, G. R., Matthews, L., Lewis, S., Birney, E., Stein, L.. Reactome: a knowledgebase of biological pathways. Nucleic Acids Research . 2005; 33: D428-D432 [OpenAIRE] [] [DOI]

Peri, S., Navarro, J. D., Kristiansen, T. Z., Amanchy, R., Surendranath, V., Muthusamy, B., Gandhi, T. K. B., Chandrika, K. N., Deshpande, N., Suresh, S., Rashmi, B. P., Shanker, K., Padma, N., Niranjan, V., Harsha, H. C., Talreja, N., Vrushabendra, B. M., Ramya, M. A., Yatish, A. J., Joy, M., Shivashankar, H. N., Kavitha, M. P., Menezes, M., Choudhury, D. R., Ghosh, N., Saravana, R., Chandran, S., Mohan, S., Jonnalagadda, C. K., Prasad, C. K., Kumar-Sinha, C., Deshpande, K. S., Pandey, A.. Human protein reference database as a discovery resource for proteomics. Nucleic Acids Research . 2004; 32: D497-D501 [OpenAIRE] [] [DOI]

Cui, X., He, H., He, F., Wang, S., Li, F., Bo, X.. Network fingerprint: a knowledge-based characterization of biomedical networks. Scientific Reports . 2015; 5, article 13286 [OpenAIRE] [DOI]

Le Novere, N.. Quantitative and logic modelling of molecular and gene networks. Nature Reviews Genetics . 2015; 16 (3): 146-158 [OpenAIRE] [] [DOI]

Frey, B. J., Dueck, D.. Clustering by passing messages between data points. Science . 2007; 315 (5814): 972-976 [OpenAIRE] [] [DOI]

Csardi, G., Nepusz, T.. The igraph software package for complex network research. International Journal of Complex Systems . 2006; 1695 (5): 1-9

Gentleman, R., Whalen, E., Huber, W., Falcon, S.. Graph: a package to handle graph data structures. R Package . 2009

Wickham, H.. Ggplot2: Elegant Graphics for Data Analysis . 2009

26 references, page 1 of 2
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