کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
403471 677241 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Improving network topology-based protein interactome mapping via collaborative filtering
ترجمه فارسی عنوان
بهبود نقشه برداری پروتئین مبتنی بر توپولوژی شبکه از طریق فیلتر همگانی
کلمات کلیدی
تعامل پروتئین-پروتئین، متقابل پروتئین، ارزیابی، پیش بینی، توپولوژی شبکه، شباهت بین همسایگی، وزن تقریبی کارکردی فیلترینگ همکاری
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

High-throughput screening (HTS) techniques enable massive identification of protein–protein interactions (PPIs). Nonetheless, it is still intractable to observe the full mapping of PPIs. With acquired PPI data, scalable and inexpensive computation-based approaches to protein interactome mapping (PIM), which aims at increasing the data confidence and predicting new PPIs, are desired in such context. Network topology-based approaches prove to be highly efficient in addressing this issue; yet their performance deteriorates significantly on sparse HTS-PPI networks. This work aims at implementing a highly efficient network topology-based approach to PIM via collaborative filtering (CF), which is a successful approach to addressing sparse matrices for personalized-recommendation. The motivation is that the problems of PIM and personalized-recommendation have similar solution spaces, where the key is to model the relationship among involved entities based on incomplete information. Therefore, it is expected to improve the performance of a topology-based approach on sparse HTS-PPI networks via integrating the idea of CF into it. We firstly model the HTS-PPI data into an incomplete matrix, where each entry describes the interactome weight between corresponding protein pair. Based on it, we transform the functional similarity weight in topology-based approaches into the inter-neighborhood similarity (I-Sim) to model the protein–protein relationship. Finally, we apply saturation-based strategies to the I-Sim model to achieve the CF-enhanced topology-based (CFT) approach to PIM.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 90, December 2015, Pages 23–32
نویسندگان
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