Integrated Text Mining and Chemoinformatics Analysis Associates Diet to Health Benefit at Molecular Level
- Publication Date
- January 16, 2014
- Journal
- PLOS Computational Biology
- Authors
- Kasper Jensen, Gianni Panagiotou & Irene Kouskoumvekaki
- Volume
- 10
- Issue
- 1
- Pages
- e1003432
- DOI
- https://dx.plos.org/10.1371/journal.pcbi.1003432
- Publisher URL
- http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1003432
- PubMed
- http://www.ncbi.nlm.nih.gov/pubmed/24453957
- PubMed Central
- http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894162
- Europe PMC
- http://europepmc.org/abstract/MED/24453957
- Web of Science
- 000337948500032
- Scopus
- 84896733774
- Mendeley
- http://www.mendeley.com/research/integrated-text-mining-chemoinformatics-analysis-associates-diet-health-benefit-molecular-level
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Mendeley | Further Information
{"title"=>"Integrated Text Mining and Chemoinformatics Analysis Associates Diet to Health Benefit at Molecular Level", "type"=>"journal", "authors"=>[{"first_name"=>"Kasper", "last_name"=>"Jensen", "scopus_author_id"=>"57201310214"}, {"first_name"=>"Gianni", "last_name"=>"Panagiotou", "scopus_author_id"=>"8566179700"}, {"first_name"=>"Irene", "last_name"=>"Kouskoumvekaki", "scopus_author_id"=>"6602787035"}], "year"=>2014, "source"=>"PLoS Computational Biology", "identifiers"=>{"sgr"=>"84896733774", "doi"=>"10.1371/journal.pcbi.1003432", "pui"=>"372348784", "pmid"=>"24453957", "scopus"=>"2-s2.0-84896733774", "issn"=>"1553734X", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)"}, "id"=>"dc87caa0-5716-3a0b-b0ad-841385d652f6", "abstract"=>"Awareness that disease susceptibility is not only dependent on genetic make up, but can be affected by lifestyle decisions, has brought more attention to the role of diet. However, food is often treated as a black box, or the focus is limited to few, well-studied compounds, such as polyphenols, lipids and nutrients. In this work, we applied text mining and Naïve Bayes classification to assemble the knowledge space of food-phytochemical and food-disease associations, where we distinguish between disease prevention/amelioration and disease progression. We subsequently searched for frequently occurring phytochemical-disease pairs and we identified 20,654 phytochemicals from 16,102 plants associated to 1,592 human disease phenotypes. We selected colon cancer as a case study and analyzed our results in three directions; i) one stop legacy knowledge-shop for the effect of food on disease, ii) discovery of novel bioactive compounds with drug-like properties, and iii) discovery of novel health benefits from foods. This works represents a systematized approach to the association of food with health effect, and provides the phytochemical layer of information for nutritional systems biology research.", "link"=>"http://www.mendeley.com/research/integrated-text-mining-chemoinformatics-analysis-associates-diet-health-benefit-molecular-level", "reader_count"=>70, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Librarian"=>1, "Researcher"=>21, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>1, "Student > Master"=>9, "Student > Bachelor"=>5, "Lecturer"=>2, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Librarian"=>1, "Researcher"=>21, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>1, "Student > Master"=>9, "Student > Bachelor"=>5, "Lecturer"=>2, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Agricultural and Biological Sciences"=>19, "Arts and Humanities"=>1, "Chemistry"=>2, "Computer Science"=>15, "Earth and Planetary Sciences"=>1, "Engineering"=>4, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>7, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>6, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Physics and Astronomy"=>1, "Psychology"=>2, "Linguistics"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>6}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>2}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>2}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>4}, "Chemistry"=>{"Chemistry"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>19}, "Computer Science"=>{"Computer Science"=>15}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Linguistics"=>{"Linguistics"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}}, "reader_count_by_country"=>{"Canada"=>1, "Czech Republic"=>1, "Netherlands"=>1, "Korea (South)"=>1, "United States"=>2, "Brazil"=>1, "United Kingdom"=>1, "Italy"=>1, "Australia"=>1, "Switzerland"=>2, "Spain"=>2, "India"=>1}, "group_count"=>7}CrossRef
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Scopus | Further Information
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Relative Metric
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