htSNPer1.0: software for haplotype block partition and htSNPs selection
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: 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: 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: 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: 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: Extraction and mining of an academic social network
abstract: This paper addresses several key issues in extraction and mining of an academic social network: 1) extraction of a researcher social network from the existing Web; 2) integration of the publications from existing digital libraries; 3) expertise search on a given topic; and 4) association search between researchers. We developed a social network system, called ArnetMiner, based on proposed methods to the above problems. In total, 448,470 researcher profiles and 981,599 publications were extracted/integrated after the system having been in operation for two years. The paper describes the architecture and main features of the system. It also briefly presents the experimental results of the proposed methods.

title: A Computational Framework and Browser for Supporting Automatic Genome Annotation
abstract: We present here a flexible computational framework to complete the large-scale computing tasks involved in automatic annotation of whole-genomes. The characteristics of this framework include a two-level job load system and NFS-based distributed store of replicated data. In addition, the storage structure of annotation results in a relational database system and a Web interface for graphical interactive browsing and searching on the data are also described. The framework has been used to identify a core set of human protein coding genes that are consistently annotated and of high quality, which can be accessed by the browser provided at http://bioinfo.hust.edu.cn/en/database/ben

title: The transient performance analysis of voice/data integrated networks
abstract: Quasi-birth-death (QBD) processes are used as performance models for voice/data integration schemes. It is assumed that voice and data packets of different bandwidths require different numbers of servers for service. Voice packets are lost when there are no available servers; data packets are queued in a buffer when there are not enough servers. A new approach is proposed to find the transient solutions of the QBD processes. The method is applied to a QBD model of a voice/data integration scheme to find time-dependent performance measures such as the expected number of data or voice packets in the system and the voice packet blocking probability.<<ETX>>

title: Application of Immune Classifier Based on Increment of Diversity in the Model Species Genomes Identification
abstract: The model species genomes project has played a very important role in the research of human genomes. By comparing and identifying the genomes' information in the different biological evolution stages with the model species genomes, it is favorable to understand deeply the genomes' structure and function of the advanced species, especially the human being, and to reveal the life's essential law. In the paper, the DNA sequences of three model species including C. elegans, S. cerevisiae and A.thaliana are divided into three types: intron, exon, intergenic DNA at first. The bases of each sequence are given number (1, 2, hellip, N) base by base from the beginning. According to three phases of the codons, we can extract three subsequences which numbers are respectively 3n+1, 3n+2 and 3n+3 (n=0, 1, 2, ...,N/3-1). Calculating respectively the probability of four bases in three subsequence we can attain 12 parameters which are regarded as the state parameters of the diversity sources. Each sequence of intron, exon and intergenic DNA is expressed by a 12-dimension eigenvector. All of these sequences' 12-dimension samples are divided into the training sample set and the testing sample set. Then, according to the immune network theory, a immune classifier based on the diversity increment is constructed, which considers the reciprocal of the diversity increment as affinity function and makes the immune network evolve in the direction of identifying the antigens by submitting unceasingly the antigens one by one, which is a record of the training sample set. Finally, the classifier has high performance and its prediction accuracy is up to 85% by test.

title: Backup reprovisioning to remedy the effect of multiple link failures in WDM mesh networks
abstract: As networks grow in size and complexity, both the probability and the impact of failures increase. The pre-allocated backup bandwidth, which has been widely investigated in the literature, may not be able to provide full protection guarantee when multiple failures occur in a network. In this study, we consider multiple concurrent failures where concurrent means that a new failure occurs before a previous failure is repaired. To combat the effect of multiple concurrent failures, new backups can be reprovisioned after one failure such that the next potential failure can be handled effectively and efficiently. We consider dynamic traffic where a pair of link-disjoint primary and backup paths is provisioned when a new connection request arrives. After a failure occurs, the affected connections switch traffic from their primary paths to backup paths. To protect against next potential failure, we reprovision new backups for connections that become unprotected or vulnerable because of losing their primary or their backup due to the previous failure or due to backup resource sharing. This approach is called Minimal Backup Reprovisioning (MBR). An alternative approach is to globally rearrange backups for all connections after one failure occurs, which is called Global Backup Reprovisioning (GBR). Backup reprovisioning can be performed whenever the network's state changes, e.g., (1) when a new request arrives, (2) when an existing connection terminates, (3) when a network failure occurs, (4) when a failed link/node is repaired, etc., to utilize the available resources more efficiently or to recover quickly from the next failure. In this study, we perform MBR or GBR after one network failure occurs to protect against the next potential failure in a wavelength-convertible WDM mesh network. The link-vector network model which can maximally explore the backup-sharing potential is assumed in this study. We then analyze the complexity of MBR and GBR under such a network model. A reprovisioning algorithm is proposed for MBR which can significantly reduce the connection vulnerability without the knowledge of the location of the next failure. In GBR, both integer linear program (ILP) and heuristic-based approaches are proposed. We compare capacity requirement and computational complexity of MBR to that of GBR through numerical examples. MBR demonstrates a good tradeoff between complexity and capacity efficiency to handle multiple concurrent failures

title: Building XML Data Warehouse Based on Frequent Patterns in User Queries
abstract: With the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users needs in XML data acquirement. In this paper, we propose an approach to materialize XML data warehouses based on frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, the integration approach in the data warehouse is flexible with respect to obtaining and maintaining XML documents. Experiments show that the overall processing of the same queries issued against the global schema become much efficient by using the XML data warehouse built than by directly searching the multiple data sources.