Background. Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to...
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Background. Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions. We provide a computat
Facial expression recognition is one of the most popular topics in emotion analysis. Most facial expression recognition systems are implemented by general expression models. Since facial expressions may be expressed d...
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User authentication is one of the fundamental procedures to ensure secure communications and share system resources over an insecure public network channel. Especially, the purpose of the one-time password is to make ...
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Recently, the resource sharing systems apply the P2P technique to provide scalable multi-attribute range queries. However, due to the heterogeneity of resources and the variation of sharing policies in different provi...
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In this paper, we propose an information hiding scheme to embed secret information into the compression code of an index table. First, the codewords neighboring the current processed index along with their closest cod...
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We present in this paper the experience of the authors in solving very large problems of computational mechanics on a supercomputer. The authors are researchers of the Barcelona Supercomputing Center-Centro Nacional d...
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Identifying the behavior patterns is the main goal for a dynamical system. It provides the useful information in behavior prediction of a dynamical system. On the other hand, measuring the orderliness of a dynamical s...
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For the various applications in home automation, the service system requires to precisely estimate user’s locations by certain sensors. It is considered as a challenge to automatically serve a mobile user in the hous...
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This paper describes an update mechanism for large wireless ad-hoc sensor networks (WASNs). In wireless sensor networks, the nodes may have to be reprogrammed, especially for design-implement-test iterations. Manually...
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The users to search the required information on the Web extensively use the search engines. These, search engines maintain the index of billions of pages for efficient searching. The crawlers of these search engines h...
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The users to search the required information on the Web extensively use the search engines. These, search engines maintain the index of billions of pages for efficient searching. The crawlers of these search engines have to retrieve the pages continuously to keep the index up-to-date. It is reported in the literature that the 40% of the current Internet traffic and bandwidth consumption is due to these crawlers. These crawlers also cause load on the remote server by using its CPU cycles and memory. The authors of this paper address this problem by proposing a novel indexing system based on mobile crawlers. The proposed approach employs mobile agents to crawl the pages. These mobile crawlers identify the modified pages at the remote site without downloading them. The proposed mobile crawler downloads those pages only, which have actually been modified since last crawl. The simulated results of the proposed mobile crawler have shown the reduction in the Internet traffic and load on the remote site considerably.
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