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Tsinghua Science and Technology

Issue 6 • Date Dec. 2012

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Displaying Results 1 - 14 of 14
  • [Front cover]

    Publication Year: 2012, Page(s): c1
    IEEE is not the copyright holder of this material | PDF file iconPDF (1337 KB)
    Freely Available from IEEE
  • Contents

    Publication Year: 2012, Page(s): 1
    IEEE is not the copyright holder of this material | PDF file iconPDF (35 KB)
    Freely Available from IEEE
  • SPECIAL ISSUE ON BIOINFORMATICS AND COMPUTATIONAL BIOLOGY 
  • Guest editorial: Special issue on bioinformatics and computational biology

    Publication Year: 2012, Page(s):607 - 608
    IEEE is not the copyright holder of this material | PDF file iconPDF (85 KB)
    Freely Available from IEEE
  • Recognizing hierarchically related biomedical entities using MeSH-based mapping

    Publication Year: 2012, Page(s):609 - 618
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (196 KB)

    Identifying hierarchically related entities is a critical step towards constructing bio-networks in the field of biomedical text mining. To this end, we adopt a mapping-based approach by first mapping bio-entities to terms in an established ontology Medical Subject Headings (MeSH). We then utilize the hierarchical relationships available in MeSH to recognize hierarchically related entities. Specif... View full abstract»

    Open Access
  • Robust multiclass classification for learning from imbalanced biomedical data

    Publication Year: 2012, Page(s):619 - 628
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (305 KB)

    Imbalanced data is a common and serious problem in many biomedical classification tasks. It causes a bias on the training of classifiers and results in lower accuracy of minority classes prediction. This problem has attracted a lot of research interests in the past decade. Unfortunately, most research efforts only concentrate on 2-class problems. In this paper, we study a new method of formulating... View full abstract»

    Open Access
  • On the edge of web-based multiple sequence alignment services

    Publication Year: 2012, Page(s):629 - 637
    Cited by:  Papers (2)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (366 KB)

    There are many web-based multiple sequence alignment services accessible around the world. However, many researchers working on biological sequence analysis still struggle with inefficient, unfriendly user interface, and limited capability multiple sequence alignment software. In this study, we provide a comprehensive survey of regional and continental facilities that provide web-based alignment s... View full abstract»

    Open Access
  • Protein phosphorylation site prediction via feature discovery support vector machine

    Publication Year: 2012, Page(s):638 - 644
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (870 KB)

    Protein phosphorylation/dephosphorylation is the central mechanism of post-translational modification which regulates cellular responses and phenotypes. Due to the efficiency and resource constraints of the in vivo methods for identifying phosphorylation sites, there is a strong motivation to computationally predict potential phosphorylation sites. In this work, we propose to use a unique set of f... View full abstract»

    Open Access
  • Prediction of essential proteins using topological properties in GO-pruned PPI network based on machine learning methods

    Publication Year: 2012, Page(s):645 - 658
    Cited by:  Papers (5)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1049 KB)

    The prediction of essential proteins, the minimal set required for a living cell to support cellular life, is an important task to understand the cellular processes of an organism. Fast progress in high-throughput technologies and the production of large amounts of data enable the discovery of essential proteins at the system level by analyzing Protein-Protein Interaction (PPI) networks, and repla... View full abstract»

    Open Access
  • Gene selection for classifications using Multiple PCA with Sparsity

    Publication Year: 2012, Page(s):659 - 665
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (241 KB)

    A gene selection algorithm was developed using Multiple Principal Component Analysis with Sparsity (MSPCA). The MSPCA algorithm is used to analyze normal and disease gene expression samples and to set these component loadings to zero if they are smaller than a threshold for sparse solutions. Next, genes with zero loadings across all samples (both normal and disease) are removed before extracting f... View full abstract»

    Open Access
  • Mining and integrating reliable decision rules for imbalanced cancer gene expression data sets

    Publication Year: 2012, Page(s):666 - 673
    Cited by:  Papers (3)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (643 KB)

    There have been many skewed cancer gene expression datasets in the post-genomic era. Extraction of differential expression genes or construction of decision rules using these skewed datasets by traditional algorithms will seriously underestimate the performance of the minority class, leading to inaccurate diagnosis in clinical trails. This paper presents a skewed gene selection algorithm that intr... View full abstract»

    Open Access
  • Mining protein complexes from PPI networks using the minimum vertex cut

    Publication Year: 2012, Page(s):674 - 681
    Cited by:  Papers (6)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1060 KB)

    Evidence shows that biological systems are composed of separable functional modules. Identifying protein complexes is essential for understanding the principles of cellular functions. Many methods have been proposed to mine protein complexes from protein-protein interaction networks. However, the performances of these algorithms are not good enough since the protein-protein interactions detected f... View full abstract»

    Open Access
  • Analysis of gene networks for Arabidopsis flowering

    Publication Year: 2012, Page(s):682 - 690
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (760 KB)

    The flowering time of Arabidopsis is sensitive to climate variability, with lighting conditions being a major determinant of the flowering time. Long-days induce early flowering, while short-days induce late flowering or even no flowers. This study investigates the intrinsic mechanisms for Arabidopsis flowering in different lighting conditions using mutual information networks and logic networks. ... View full abstract»

    Open Access
  • Using folding ensemble and stem probability maximization methods to predict RNA H-type pseudoknots

    Publication Year: 2012, Page(s):691 - 700
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (639 KB)

    We present in this paper an ab initio method, named KnotFold, for RNA H-type pseudoknot prediction. Our method employs an ensemble of RNA folding tools and a filtering heuristic to generate a set of pseudoknot-free stems, and then predicts pseudoknots by utilizing a search technique with a pseudo-probability scoring scheme. Experimental results show that KnotFold achieves higher sensitivity than e... View full abstract»

    Open Access
  • Total contents

    Publication Year: 2012, Page(s):I - IV
    IEEE is not the copyright holder of this material | PDF file iconPDF (63 KB)
    Freely Available from IEEE

Aims & Scope

Tsinghua Science and Technology (Tsinghua Sci Technol) aims to highlight scientific achievements in computer science, electronic engineering, and other IT fields. Contributions all over the world are welcome.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Professor Jiaguang Sun
School of Software
Tsinghua University
Beijing  100084 China
journal@tsinghua.edu.cn
Phone:86-10-62771385