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	1. A Novel Measure of Node Importance in Social Networks with user ranking
	GUO Xiaoli,GE Hongwei
	Computer Science and Technology 25 June 2014
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	Abstract:How to measure the importance of nodes or find out the important nodes in networks has become a hot focus of research. In order to find important nodes in social networks effectively, this paper propose an user ranking algorithm and a novel measure of node importance based on node centrality, intimacy, criticality and user ranking. As known, in the social network, closer the node is to the center of the network, more important it is; and at the same time, more times the node is recommended by users, more top ranking of the node, more important the node is to its neighborhood nodes. Our new measure takes both the two factors into account, combines the local and global importance of a node. Using this measure of node importance, this paper proposed an important node discovery algorithm. The experimental results in real networks demonstrate that the measure is effective.
	TO cite this article:GUO Xiaoli,GE Hongwei. A Novel Measure of Node Importance in Social Networks with user ranking[OL].[25 June 2014] http://en.paper.edu.cn/en_releasepaper/content/4601332


	2. Enriched Kernel for Protein Function Prediction
	Qianli Ma,Jiajun Jiang,Guoxian Yu
	Computer Science and Technology 21 June 2014
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	Abstract:Protein function prediction is one of the hottest research areas in biotech. According to different similarities characteristics of proteins, scientists construct more than one relationship between proteins, which can be called kernels. Different kernels have different domain-related information of proteins' relationship. Generally speaking, due to the complementarity of these information, multiple kernel learning (MKL) can overcome the heterogeneity between the kernels data to some extent and improve the protein function prediction precision. However, the existing domain-related kernels may contain some isolated proteins. Furthermore, the similarities between proteins may be considerably affected by noises. In this paper, we propose a fully connected kernel to enrich the available kernels. Based on the label propagation algorithm, the enriched kernels can not only propagate information to the isolated protein, but also can reduce the noises influences and improve the protein function prediction accuracy. We tested the method on the benchmark protein datasets, and the MKL algorithms with enriched kernel have a better performance.
	TO cite this article:Qianli Ma,Jiajun Jiang,Guoxian Yu. Enriched Kernel for Protein Function Prediction[OL].[21 June 2014] http://en.paper.edu.cn/en_releasepaper/content/4600760

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	3. SFAPS:anRpackage for Structure/Function Analysis of Protein Sequences based on Informational Spectrum Method
	Su-Ping Deng,De-Shuang Huang
	Computer Science and Technology 05 June 2014
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	Abstract:The R package SFAPS has been developed for structure/function analysis of protein sequences based on information spectrum method. The informational spectrum method employs the electron-Ion interaction potential parameter as the numerical representation for the protein sequence, and obtains the characteristic frequency of a particular protein interaction after computing the Discrete Fourier Transform for protein sequences. The informational spectrum method is often used to analyze protein sequences, so we developed this software tool, which is implemented as an add-on package to the freely available and widely used statistical language R. Our package is distributed as open source code for Linux, Unix and Microsoft Windows. It is released under the GNU General Public License. The R package along with its source code and additional material are freely available at http://mlsbl.tongji.edu.cn/DBdownload.asp.
	TO cite this article:Su-Ping Deng,De-Shuang Huang. SFAPS:anRpackage for Structure/Function Analysis of Protein Sequences based on Informational Spectrum Method[OL].[ 5 June 2014] http://en.paper.edu.cn/en_releasepaper/content/4596118


	4. An Integrated Strategy for Functional Analysis of Microbial Communities Based on Gene Ontology and 16S rRNA Gene
	Su-Ping Deng,De-Shuang Huang
	Computer Science and Technology 22 May 2014
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	Abstract:In order to analyze the similarity among microbial communities on functional state after assigning 16S rRNA sequences from all microbial communities to species. It's an important addition to the species-level relationship between two compared communities, and can quantify their differences in function. We downloaded all functional annotation data of several microbiotas. It's developed to identify the functional distribution and the significantly enriched functional categories of microbial communities. We analyzed the similarity between two microbial communities on functional state. In the experimental results, it shows that the semantic similarity can quantify the difference between two compared species on function level. It can analyze the function of microbial communities by Gene Ontology based on 16S rRNA gene. Exploration of the function relationship between two sets of species assemblages will be a key result of microbiome studies and may provide new insights into assembly of a wide range of ecosystems.
	TO cite this article:Su-Ping Deng,De-Shuang Huang. An Integrated Strategy for Functional Analysis of Microbial Communities Based on Gene Ontology and 16S rRNA Gene[OL].[22 May 2014] http://en.paper.edu.cn/en_releasepaper/content/4596115


	5. A Novel Edge Detection Operator Based On Fractional Gaussian Differential
	HAN Qirui,LIU Ke
	Computer Science and Technology 08 May 2014
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	Abstract:This paper presents an improved algorithm for edge detection. The algorithm combines the Gaussian average operator with 1-2 order fractional differential.Gaussian average operatorhas outstanding performance in image denoising and 1-2 order fractional differential retain more detailed imageinformation during sharping. It has been proved by theoretical analysis and experimental verificationsthat this method could extract image edge information effectively and reserve partial near edgedetails, and shows better noise immunity in edge detection.
	TO cite this article:HAN Qirui,LIU Ke. A Novel Edge Detection Operator Based On Fractional Gaussian Differential[OL].[ 8 May 2014] http://en.paper.edu.cn/en_releasepaper/content/4595118


	6. NetCompare: A Visualization Tool for Network Alignment on Galaxy
	Xie Jiang,Xiang Chaojuan,Zhou Zhonghua,Dai Dongbo,Zhang Huiran
	Computer Science and Technology 28 March 2014
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	Abstract:Network alignment has made great progress and provides new insights into protein function. To visualize the results effectively is difficult because of the large scale network. In this paper, a simple tool named Network Compare (NetCompare) is proposed to visualize and analyze the network alignment results. Firstly, multi-hierarchical clustering method is used to cluster the large aligned networks. Secondly, at each clustering level, users can select the layout method which they prefer to display the results. NetCompare offers both the global and the local views. The global views briefly regard one subnet as one "node", and the local views display the details including node information. When users submit the matched nodes of aligned networks, the matched subnets can be described as well. Both the clustering and the drawing processes are parallelized on GPU which offers short response time in the analysis of very huge protein interaction networks. NetCompare is implemented on the local version of Galaxy platform.
	TO cite this article:Xie Jiang,Xiang Chaojuan,Zhou Zhonghua, et al. NetCompare: A Visualization Tool for Network Alignment on Galaxy[J].


	7. A Parallel Algorithm for DNA Sequences Alignment Based on MPI
	Xue Qianfei,Xie Jiang,Shu Junhui,Zhang Huiran,Dai Dongbo,Wu Xing,Zhang Wu
	Computer Science and Technology 24 March 2014
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	Abstract:DNA sequences have the fundamental information for each species and a comparison between DNA sequences is one of the basic biological problems. There are a large number of algorithms applied in sequence alignment. Some are for approximate alignment, and others are for exact alignment, which also plays an important role in biology research. In this paper, a new parallel algorithm based on FED algorithm for exact sequences alignment with MPI is proposed. The experimental results indicate that the proposed algorithm can report the matched positions in the specific sequence and improve the matching speed with MPI, as well as reduce the storage requirement.
	TO cite this article:Xue Qianfei,Xie Jiang,Shu Junhui, et al. A Parallel Algorithm for DNA Sequences Alignment Based on MPI[J].


	8. A Simple Rule for the Evolution of Social Networks: Attraction and Repulsion between Individuals
	CHEN Zhaodi
	Computer Science and Technology 05 March 2014
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	Abstract:Modeling the evolution of networks is important to understand complex systems. Considering network structure and individual attributes, a force-based model is proposed to simulate the evolution of social networks. Each node is endowed with a series of attributes. We construct a multi-dimensional space as the evolution environment. An attribute vector represents a position in the space. Individuals interact with each other obeying a simple rule that each node tends to move to a low energy position driven by attraction from its immediate neighbors and repulsion from all other nodes. So the evolution can be viewed as interaction among nodes, moving close or far away. A new position means a change of attributes. Network structure updates at last of each round. Edge exists only when its two endpoints' similarity distance is lower than a threshold. We validate the model and simulations show that though individual attributes change, the network keeps the power-law degree distribution and clusters emerge in the process of evolution.
	TO cite this article:CHEN Zhaodi. A Simple Rule for the Evolution of Social Networks: Attraction and Repulsion between Individuals[OL].[ 5 March 2014] http://en.paper.edu.cn/en_releasepaper/content/4587432


	9. An Opposition Effective GSA Based Memetic Algorithm for Permutation Flow Shop Scheduling
	ZHOU Junping,WANG Huixian,SU Weihua
	Computer Science and Technology 25 February 2014
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	Abstract:The permutation flow shop problem (PFSSP) is a well-known difficult combinatorial optimization problem. In this paper, we present a new hybrid optimization algorithm named OHGSA to solve the PFSSP. First, to make GSA suitable for PFSSP, a new LRV rule based on random key is introduced to convert the continuous position in GSA to the discrete job permutation. Second, The NEH heuristic was combined the random initialization to initialize the population with certain quality and diversity. Third, to improve the convergence rate of GSA, the opposition-based DE employs opposition-based learning for the initialization and for generation jumping to enhance the global optimal solution. Fourth, the fast local search is used for enhancing the individuals with a certain probability. Additional-ly, Comparison with other results in the literature shows that the OHGSA is an ef-ficient and effective approach for the PFSSP.
	TO cite this article:ZHOU Junping,WANG Huixian,SU Weihua. An Opposition Effective GSA Based Memetic Algorithm for Permutation Flow Shop Scheduling[OL].[25 February 2014] http://en.paper.edu.cn/en_releasepaper/content/4587358


	10. Gait Correlation Analysis Based Human Identification
	Chen Jinyan
	Computer Science and Technology 17 January 2014
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	Abstract:Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification the most important advantage of gait identification is that it can be done in a distance. In this paper silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis(x), vertical axis(y) and temporal axis(t). By moving every pixel in the silhouette image along these three dimensions we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features' dimensions. Experiment based on CASIA database shows this method has an encouraging recognition performance.
	TO cite this article:Chen Jinyan. Gait Correlation Analysis Based Human Identification[OL].[17 January 2014] http://en.paper.edu.cn/en_releasepaper/content/4582336

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