Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates
المؤلفون المشاركون
Gantner, Melisa Edith
Di Ianni, Mauricio Emiliano
Ruiz, María Esperanza
Talevi, Alan
Bruno Blanch, Luis E.
المصدر
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-08-01
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
ABC efflux transporters are polyspecific members of the ABC superfamily that, acting as drug and metabolite carriers, provide a biochemical barrier against drug penetration and contribute to detoxification.
Their overexpression is linked to multidrug resistance issues in a diversity of diseases.
Breast cancer resistance protein (BCRP) is the most expressed ABC efflux transporter throughout the intestine and the blood-brain barrier, limiting oral absorption and brain bioavailability of its substrates.
Early recognition of BCRP substrates is thus essential to optimize oral drug absorption, design of novel therapeutics for central nervous system conditions, and overcome BCRP-mediated cross-resistance issues.
We present the development of an ensemble of ligand-based machine learning algorithms for the early recognition of BCRP substrates, from a database of 262 substrates and nonsubstrates compiled from the literature.
Such dataset was rationally partitioned into training and test sets by application of a 2-step clustering procedure.
The models were developed through application of linear discriminant analysis to random subsamples of Dragon molecular descriptors.
Simple data fusion and statistical comparison of partial areas under the curve of ROC curves were applied to obtain the best 2-model combination, which presented 82% and 74.5% of overall accuracy in the training and test set, respectively.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Gantner, Melisa Edith& Di Ianni, Mauricio Emiliano& Ruiz, María Esperanza& Talevi, Alan& Bruno Blanch, Luis E.. 2013. Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates. BioMed Research International،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1005300
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Gantner, Melisa Edith…[et al.]. Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates. BioMed Research International No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-1005300
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Gantner, Melisa Edith& Di Ianni, Mauricio Emiliano& Ruiz, María Esperanza& Talevi, Alan& Bruno Blanch, Luis E.. Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1005300
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1005300
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