NutriChem: A systems chemical biology resource to explore the medicinal value of plant-based foods

Nucleic Acids Research

Volumn 43, Issue D1, 2015, Pages D940-D945

  Jensen, Kasper ^a   Panagiotou, Gianni ^b   Kouskoumvekaki, Irene ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

PLANT MEDICINAL PRODUCT;

ARTICLE; CHEMICAL DATABASE; DATA MINING; DIETARY INTAKE; DISEASE ASSOCIATION; FEEDING BEHAVIOR; FOOD ANALYSIS; FOOD COMPOSITION; MEDICINAL PLANT; NUTRICHEM DATABASE; NUTRITIONAL VALUE; PHENOTYPE; PHYTOCHEMISTRY; PREDICTION; PRIORITY JOURNAL; DIET; DISEASES; EDIBLE PLANT; FACTUAL DATABASE; HUMAN; INTERNET; PREVENTIVE MEDICINE;

DATABASES, FACTUAL; DIET; DISEASE; HUMANS; INTERNET; PHENOTYPE; PHYTOCHEMICALS; PLANTS, EDIBLE; PREVENTIVE MEDICINE;

EID: 84946035755     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gku724     Document Type: Article

References (24)

1. Brook, R. D., Rajagopalan, S., Pope, C. A. III., Brook, J. R., Bhatnagar, A., Diez-Roux, A. V., Holguin, F., Hong, Y., Luepker, R. V., Mittleman, M. A. et al. (2010) Particulate matter air pollution and cardiovascular disease: an update to the scientific statement from the American Heart Association. Circulation, 121, 2331-2378.
2. Heinrich, J. (2011) Influence of indoor factors in dwellings on the development of childhood asthma. Int. J. Hyg. Environ. Health, 214, 1-25.
3. Wild, C. P. (2011) Future research perspectives on environment and health: the requirement for a more expansive concept of translational cancer research. Environ. Health Glob. Access Sci. Source, 10, (Suppl. 1), e1.
4. Paoloni-Giacobino, A. (2011) Post genomic decade-the epigenome and exposome challenges. Swiss Med. Wkly., 141, w13321.
5. Rappaport, S. M. (2012) Discovering environmental causes of disease. J. Epidemiol. Community Health, 66, 99-102.
6. Tran, B., Falster, M. O., Douglas, K., Blyth, F. and Jorm, L. R. (2014) Health behaviours and potentially preventable hospitalisation: a prospective study of older Australian adults. PLoS One, 9, e93111.
7. Woodside, J. V., Young, I. S. and McKinley, M. C. (2013) Fruit and vegetable intake and risk of cardiovascular disease. Proc. Nutr. Soc., 72, 399-406.
8. Esfahani, A., Wong, J. M. W., Truan, J., Villa, C. R., Mirrahimi, A., Srichaikul, K. and Kendall, C. W. C. (2011) Health effects of mixed fruit and vegetable concentrates: a systematic review of the clinical interventions. J. Am. Coll. Nutr., 30, 285-294.
9. He, F. J., Nowson, C. A., Lucas, M. and MacGregor, G. A. (2007) Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: meta-analysis of cohort studies. J. Hum. Hypertens., 21, 717-728.
10. Dauchet, L., Amouyel, P., Hercberg, S. and Dallongeville, J. (2006) Fruit and vegetable consumption and risk of coronary heart disease: a meta-analysis of cohort studies. J. Nutr., 136, 2588-2593.
11. Dauchet, L., Amouyel, P. and Dallongeville, J. (2005) Fruit and vegetable consumption and risk of stroke: a meta-analysis of cohort studies. Neurology, 65, 1193-1197.
12. He, F. J., Nowson, C. A. and MacGregor, G. A. (2006) Fruit and vegetable consumption and stroke: meta-analysis of cohort studies. Lancet, 367, 320-326.
13. Neveu, V., Perez-Jimenez, J., Vos, F., Crespy, V., du Chaffaut, L., Mennen, L., Knox, C., Eisner, R., Cruz, J., Wishart, D. et al. (2010) Phenol-Explorer: an online comprehensive database on polyphenol contents in foods. Database (Oxford), 2010, e1.
14. Afendi, F. M., Okada, T., Yamazaki, M., Hirai-Morita, A., Nakamura, Y., Nakamura, K., Ikeda, S., Takahashi, H., Altaf-Ul-Amin, M., Darusman, L. K. et al. (2012) KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research. Plant Cell Physiol., 53, e1.
15. Zhu, F., Shi, Z., Qin, C., Tao, L., Liu, X., Xu, F., Zhang, L., Song, Y., Liu, X., Zhang, J. et al. (2012) Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res., 40, D1128-D1136.
16. Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., Goldberg, L. J., Eilbeck, K., Ireland, A., Mungall, C. J. et al. (2007) The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat. Biotechnol., 25, 1251-1255.
17. Bolton, E. E., Wang, Y., Thiessen, P. A. and Bryant, S. H. PubChem: integrated platform of small molecules and biological activities. Annu. Rep. Comput. Chem., 4, 217-241.
18. Hastings, J., de Matos, P., Dekker, A., Ennis, M., Harsha, B., Kale, N., Muthukrishnan, V., Owen, G., Turner, S., Williams, M. et al. (2013) The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013. Nucleic Acids Res., 41, D456-D463.
19. Hettne, K. M., Stierum, R. H., Schuemie, M. J., Hendriksen, P. J. M., Schijvenaars, B. J. A., Mulligen, E. M., van Kleinjans, J. and Kors, J. A. (2009) A dictionary to identify small molecules and drugs in free text. Bioinformatics, 25, 2983-2991.
20. Shen, J., Xu, X., Cheng, F., Liu, H., Luo, X., Chen, K., Zhao, W., Shen, X. and Jiang, H. (2003) Virtual screening on natural products for discovering active compounds and target information. Curr. Med. Chem., 10, 2327-2342.
21. Polur, H., Joshi, T., Workman, C. T., Lavekar, G. and Kouskoumvekaki, I. (2011) Back to the roots: prediction of biologically active natural products from ayurveda traditional medicine. Mol. Inform., 30, 181-187.
22. Jensen, K., Panagiotou, G. and Kouskoumvekaki, I. (2014) Integrated text mining and chemoinformatics analysis associates diet to health benefit at molecular level. PLoS Comput. Biol., 10, e1003432.
23. Durant, J. L., Leland, B. A., Henry, D. R. and Nourse, J. G. (2002) Reoptimization of MDL keys for use in drug discovery. J. Chem. Inf. Comput. Sci., 42, 1273-1280.
24. O'Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T. and Hutchison, G. R. (2011) Open babel: an open chemical toolbox. J. Cheminformatics, 3, e1.