Analysis on mannose-binding lectin as a treatment of helicobacter pylori by using data mining

التفاصيل البيبلوغرافية
العنوان: Analysis on mannose-binding lectin as a treatment of helicobacter pylori by using data mining
المؤلفون: Seojun Kim, Juho Jung, Taeseon Yoon, Wonjong Lee
المصدر: 2017 19th International Conference on Advanced Communication Technology (ICACT).
بيانات النشر: IEEE, 2017.
سنة النشر: 2017
مصطلحات موضوعية: 0301 basic medicine, Innate immune system, biology, Computer science, medicine.medical_treatment, Lectin, Mannose, chemical and pharmacologic phenomena, Helicobacter pylori, bacterial infections and mycoses, biology.organism_classification, Microbiology, Targeted therapy, 03 medical and health sciences, chemistry.chemical_compound, 030104 developmental biology, Immune system, chemistry, medicine, biology.protein, Mannan-binding lectin
الوصف: As a critical role in overall human body reactions to foreign organisms, innate immune system, especially Mannose-binding lectin (MBL), has worked for the preservation of life. Since targeted therapy on bacterial infection using innate immune system has been researched for destroying pathogens without harming ourselves, MBL could be used for the targeted therapy. Based on three algorithms; Decision Tree Algorithm, Apriori Algorithm and Support Vector Machine, analysis on chemical bond formation by comparing the similarities between two proteins which have direct relevance with mannose could suggest the potential of utilizing proteins of MBL for targeting foreign factors. According to the results, Helicobacter pylori and Homo sapiens showed distinguishable features but indicated a few common factors. We could improve the targeting treatments by considering immunological approach using MBL; to analyze the possibility for forming chemical bond between human MBL and mannose of Helicobacter pylori.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::bc2c5ead1ef7cf8def49b0874d811196
https://doi.org/10.23919/icact.2017.7890155
رقم الأكسشن: edsair.doi...........bc2c5ead1ef7cf8def49b0874d811196
قاعدة البيانات: OpenAIRE