dbNEI2.0: building multilayer network for drug-NEI-disease
The neuro-endocrine-immune (NEI) system plays a critical regulatory role in modulating host homeostasis and optimizing health. We created the dbNEI 2 years ago to collect NEI molecules and interactions. For transferring the conceptual NEI to the systematic NEI network and uncovering the NEI's medical function, we updated the dbNEI 2.0 in three ways: (i) extended NEI molecules to 2242 genes and 7657 chemical compounds by using gene ontology-based (GO-based) data mining strategy, (ii) added multilayer interactions of NEI molecules including KEGG signal transduction and metabolic pathways, HPRD protein-protein interactions (PPI), transcription factor and microRNA regulations and (iii) connected 611 drugs and 823 diseases through multilayer NEI interactions. The reconstructed drug-NEI-disease network will facilitate the systematic study of NEI system.

title: htSNPer1.0: software for haplotype block partition and htSNPs selection
abstract: BackgroundThere is recently great interest in haplotype block structure and haplotype tagging SNPs (htSNPs) in the human genome for its implication on htSNPs-based association mapping strategy for complex disease. Different definitions have been used to characterize the haplotype block structure in the human genome, and several different performance criteria and algorithms have been suggested on htSNPs selection. heuristic algorithm, generalized branch-and-bound algorithm, is applied to the searching of minimal set of haplotype tagging SNPs (htSNPs) according to different htSNPs performance criteria. We develop a software htSNPer1.0 to implement the algorithm, and integrate three htSNPs performance criteria and four haplotype block definitions for haplotype block partitioning. It is a software with powerful Graphical User Interface (GUI), which can be used to characterize the haplotype block structure and select htSNPs in the candidate gene or interested genomic regions. It can find the global optimization with only a fraction of the computing time consumed by exhaustive searching algorithm.ConclusionhtSNPer1.0 allows molecular geneticists to perform haplotype block analysis and htSNPs selection using different definitions and performance criteria. The software is a powerful tool for those focusing on association mapping based on strategy of haplotype block and htSNPs.

title: ArnetMiner: An Expertise Oriented Search System for Web Community
abstract: Expertise Oriented Search aims at providing comprehensive analysis and mining for people from distributed sources. In this paper, we give an overview of the expertise oriented search system (ArnetMiner). The system addresses several key research issues in extraction and mining of a researcher social network. The system is in operation on the internet for more than one year and receives accesses from about 1,500 users per month. Feedbacks from users and system logs indicate that users consider the system can really help people to find and share information in the web community.

title: Computing Exact p-Value for Structured Motif
abstract: Extracting motifs from a set of DNA sequences is important in computational biology. Occurrence probability is a common used statistics to evaluate the statistical significance of a motif. A main problem is how to calculate the occurrence probability of the motif on the random model of DNA sequence efficiently and accurately. In this paper, we are interested in a particular motif model which is useful in transcription process. This motif, which is called structured motif, is composed two motif words on single nucleotide alphabet and with fixed spacers between them. We present an efficient algorithm to calculate the exact occurrence probability of a structured motif on a given sequence. It is the first nontrivial algorithm to calculate the exact p-value for such kind of motifs.

title: MicroRNA identification based on sequence and structure alignment
abstract: MicroRNAs (miRNA) are approximately 22 nt long non-coding RNAs that are derived from larger hairpin RNA precursors and play important regulatory roles in both animals and plants. The short length of the miRNA sequences and relatively low conservation of pre-miRNA sequences restrict the conventional sequence-alignment-based methods to finding only relatively close homologs. On the other hand, it has been reported that miRNA genes are more conserved in the secondary structure rather than in primary sequences. Therefore, secondary structural features should be more fully exploited in the homologue search for new miRNA genes.



In this paper, we present a novel genome-wide computational approach to detect miRNAs in animals based on both sequence and structure alignment. Experiments show this approach has higher sensitivity and comparable specificity than other reported homologue searching methods. We applied this method on Anopheles gambiae and detected 59 new miRNA genes.



This program is available at http://bioinfo.au.tsinghua.edu.cn/miralign.



Supplementary information is available at http://bioinfo.au.tsinghua.edu.cn/miralign/supplementary.htm.

title: ArnetMiner: extraction and mining of academic social networks
abstract: This paper addresses several key issues in the ArnetMiner system, which aims at extracting and mining academic social networks. Specifically, the system focuses on: 1) Extracting researcher profiles automatically from the Web; 2) Integrating the publication data into the network from existing digital libraries; 3) Modeling the entire academic network; and 4) Providing search services for the academic network. So far, 448,470 researcher profiles have been extracted using a unified tagging approach. We integrate publications from online Web databases and propose a probabilistic framework to deal with the name ambiguity problem. Furthermore, we propose a unified modeling approach to simultaneously model topical aspects of papers, authors, and publication venues. Search services such as expertise search and people association search have been provided based on the modeling results. In this paper, we describe the architecture and main features of the system. We also present the empirical evaluation of the proposed methods.

title: Addressing mobility issues in mobile environment
abstract: In this paper we present an approach to overcome some of the mobility based challenges in the utilization of a mobile environment. As mobile devices utilize external resources in the mobile environment to overcome their limited capacity or performance, new challenges arise due to the mobility. In our approach the mobile device utilizing the resources moves in the mobile environment resulting connection loss. Unlike in task migration approaches our solution keeps the task execution in its original place and only the result is routed back to the mobile device. As we are using our previously implemented PeerHood middleware for the experiments the main challenge is in extending its operations to support routing in the mobile environment. This is done by extending the existing device discovery and by implementing routing service on top of PeerHood.

title: The Application of Cultural Algorithm in Load Balancing of Hybrid P2P Network
abstract: This paper analyses the defect of the designing model of load balancing in hybrid P2P network, and proposes a new strategy of scheduling for load balancing, which based on culture algorithm of multilayer belief spaces. According to the current load status of each super-node in the system, it can calculate its load weight of the next time section by using the cultural algorithm, and assign the current requests of login with weighted round-robin. The extracted knowledge which is got by selecting the best belief space from the multilayer belief space is used to optimize the constrains of the evolutionary, in order to accelerate the optimization process of the calculation of load weight. Simulation experiments show that the allocation of login request to each node is to be balance much faster through using of cultural algorithm based on multilayer belief spaces.

title: Modular verification of dynamically adaptive systems
abstract: Cyber-physical systems increasingly rely on dynamically adaptive programs to respond to changes in their physical environment; examples include ecosystem monitoring and disaster relief systems. These systems are considered high-assurance since errors during execution could result in injury, loss of life, environmental impact, and/or financial loss. In order to facilitate the development and verification of dynamically adaptive systems, we separate functional concerns from adaptive concerns. Specifically, we model a dynamically adaptive program as a collection of (non-adaptive) steady-state programs and a set of adaptations that realize transitions among steady state programs in response to environmental changes. We use Linear Temporal Logic (LTL) to specify properties of the non-adaptive portions of the system, and we use A-LTL (an adapt-operator extension toLTL) to concisely specify properties that hold during the adaptation process. Model checking offers an attractive approach to automatically analyzing models for adherence to formal properties and thus providing assurance. However, currently, model checkers are unable to verify properties specified using A-LTL. Moreover, as the number of steady-state programs and adaptations increase, the verification costs (in terms of space and time) potentially become unwieldy. To address these issues, we propose a modular model checking approach to verifying that a formal model of an adaptive program satisfies its requirements specified in LTL and A-LTL, respectively.

title: A Case Study: A Model-Based Approach to Retrofit a Network Fault Management System with Self-Healing Functionality
abstract: Adding self-healing capabilities to network management systems holds great promise for delivering important goals, such as QoS, while simultaneously lowering capital expenditure, operation cost, and maintenance cost. In this paper, we present a model-based approach to add self-healing capabilities to a fault management system for cellular networks. We propose a generic modeling framework to categorize software failures and specify their dispositions at the model level for the target system. This facilitates the deployment of a control loop for adding autonomic capabilities into the system architecture, which include self-monitoring, self-healing, and self-adjusting functionality. While self- monitoring oversees the environmental conditions and system behavior, self-healing is accomplished by instrumenting the system with self-adjusting operations. We include a case study on a prototype intelligent network fault management system to illustrate this approach by showing how these autonomic capabilities can be added and deployed. Specifically, these autonomic capabilities are derived from self-model specifications, and are used to mitigate the risk of specified failures and maintain the health of the system in response to different types of faults encountered.

title: The Intelligent Reconfigurable Measuring Node Based on Wireless Access Network
abstract: An instance of measuring node of service life measuring and control system of household appliances using FPGA and nRF2401 is present. FPGA is the core of the system which is embedded with E-MAC IP core to realize the remote monitor system replying on the TCP/IP communication protocol, and nRF2401 is wireless periphery that realizes the wireless data acquisition. How to design and implement the hardware and software on the platform of FPGA is expatiated, including constructing the hardware system in the FPGA, designing the software and analyzing the wireless module. The system uses wireless network technology and LabView software, connecting the traditional monitoring system with Internet together, and realizing automatization and informatization of household appliances measuring and control system. Result shows that it’ s a highly integrated and reconfigurable system with great flexibility.