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With the development of high-throughput technique, protein-protein interactions (PPIs) are increasing fast and available conveniently, which make it possible to identify protein complexes in PPI networkf 1–7]. Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks[8–9], which requires protein complex detection methods can identify both...
In anisotropic wireless sensor networks, range-free multilateration-based localization (RFML) protocols severely suffer from large error in node-anchor distance estimations or the bad geometry of anchors involved in the localization process. In this paper, we propose selective multilateration (SM), a RFML protocol in which a node adaptively selects a subset of anchor nodes with accurate distance estimates...
Identification of essential proteins is key to understanding the minimal requirements for cellular life and important for drug design. The rapid increase of available protein-protein interaction (PPI) data has made it possible to detect protein essentiality on network level. A series of centrality measures have been proposed to discover essential proteins based on network topology. However, most of...
Nowadays, the research of software homologous detection is especially important in the flourishing software market while the existing detection techniques based on text, token, abstract syntax tree always get the real similarity inaccurately. In this paper, a synthesis algorithm based on Analytic Hierarchy Process(AHP) is proposed, which analyzes text, token, syntax tree three comparison algorithms...
Distance estimation is a key issue in range-free localization algorithms for wireless sensor networks. Approaches that assume isotropy of networks, such as Dv-hop and Gradient, cannot obtain accurate distance estimations in anisotropic sensor networks thus are not applicable to such networks. The anisotropy of sensor networks comes from two aspects: uneven nodal distribution and irregularity of deployment...
The homologous software detection technology plays a very important role in the work of intellectual property protection by identifying code plagiarism. Plagiarism mainly happens as copy-and-paste of the code, replacing the name of functions or variables, reordering the sequence of the statement, type redefinition, and so on. At present, there are three homologous software detection technology methods...
The performance of support vector machines (SVM) drops significantly while facing imbalanced datasets, though it has been extensively studied and has shown remarkable success in many applications. Some researchers have pointed out that it is difficult to avoid such decrease when trying to improve the efficient of SVM on imbalanced datasets by modifying the algorithm itself only. Therefore, as the...
Various researches have shown that machine learning approaches can be successfully used to detect and classify cancer tissue samples by their gene expression patterns. In this paper, an entropy-based improved k-TSP method (Ik-TSP) is proposed. We calculate the entropy for each gene based on the gene expression profile, and then find the best threshold of entropy depending on LOOCV accuracy for each...
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