Novel Approach to Classify Plants Based on Metabolite-Content Similarity
المؤلفون المشاركون
Altaf-Ul-Amin, Md.
Abdullah, Azian Azamimi
Nishioka, Takaaki
Huang, Ming
Liu, Kang
Kanaya, Shigehiko
المصدر
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-01-09
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Secondary metabolites are bioactive substances with diverse chemical structures.
Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes).
This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants.
However, such a chemical taxonomic approach has limitations of incomplete metabolomics data.
We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content.
Structurally similar metabolites have been clustered using the network clustering algorithm DPClus.
Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward’s method of hierarchical clustering.
Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants.
This finding reveals the significance of metabolite content as a taxonomic marker.
We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants.
As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Kang& Abdullah, Azian Azamimi& Huang, Ming& Nishioka, Takaaki& Altaf-Ul-Amin, Md.& Kanaya, Shigehiko. 2017. Novel Approach to Classify Plants Based on Metabolite-Content Similarity. BioMed Research International،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1137544
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Kang…[et al.]. Novel Approach to Classify Plants Based on Metabolite-Content Similarity. BioMed Research International No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1137544
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Kang& Abdullah, Azian Azamimi& Huang, Ming& Nishioka, Takaaki& Altaf-Ul-Amin, Md.& Kanaya, Shigehiko. Novel Approach to Classify Plants Based on Metabolite-Content Similarity. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1137544
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1137544
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر