Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms
المؤلفون المشاركون
Peng, Huai-Shun
Huang, Chien-Hung
Ng, Ka-Lok
المصدر
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-03-17
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Many proteins are known to be associated with cancer diseases.
It is quite often that their precise functional role in disease pathogenesis remains unclear.
A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types.
In this study, we extended Aragues’s method by employing the protein-protein interaction (PPI) data, domain-domain interaction (DDI) data, weighted domain frequency score (DFS), and cancer linker degree (CLD) data to predict cancer proteins.
Performances were benchmarked based on three kinds of experiments as follows: (I) using individual algorithm, (II) combining algorithms, and (III) combining the same classification types of algorithms.
When compared with Aragues’s method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures.
We demonstrated the accuracy of the proposed method on two independent datasets.
The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively.
It is anticipated that the current research could help understand disease mechanisms and diagnosis.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Huang, Chien-Hung& Peng, Huai-Shun& Ng, Ka-Lok. 2015. Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms. BioMed Research International،Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1055000
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Huang, Chien-Hung…[et al.]. Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms. BioMed Research International No. 2015 (2015), pp.1-15.
https://search.emarefa.net/detail/BIM-1055000
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Huang, Chien-Hung& Peng, Huai-Shun& Ng, Ka-Lok. Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1055000
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1055000
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