Identifying microRNA and gene expression networks using graph communities
نویسندگان
چکیده
منابع مشابه
Prediction of Blasting Cost in Limestone Mines Using Gene Expression Programming Model and Artificial Neural Networks
The use of blasting cost (BC) prediction to achieve optimal fragmentation is necessary in order to control the adverse consequences of blasting such as fly rock, ground vibration, and air blast in open-pit mines. In this research work, BC is predicted through collecting 146 blasting data from six limestone mines in Iran using the artificial neural networks (ANNs), gene expression programming (G...
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University of California, Davis 27.
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The investigation of community structures in networks is an important issue in many domains and disciplines. This problem is relevant for social tasks (objective analysis of relationships on the web), biological inquiries (functional studies in metabolic and protein networks), or technological problems (optimization of large infrastructures). Several types of algorithms exist for revealing the ...
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BACKGROUND The mechanisms underlying chronic obstructive pulmonary disease (COPD) remain unclear. MicroRNAs (miRNAs or miRs) are small non-coding RNA molecules that modulate the levels of specific genes and proteins. Identifying expression patterns of miRNAs in COPD may enhance our understanding of the mechanisms of disease. A study was undertaken to determine if miRNAs are differentially expre...
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The proposed algorithm in this research is based on the multi-agent particle swarm optimization as a collective intelligence due to the connection between several simple components which enables them to regulate their behavior and relationships with the rest of the group according to certain rules. As a result, self-organizing in collective activities can be seen. Community structure is crucial...
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ژورنال
عنوان ژورنال: Tsinghua Science and Technology
سال: 2016
ISSN: 1007-0214
DOI: 10.1109/tst.2016.7442501