Thu, 21 Aug 2008 11:06:29 BST CiteULike: zwangs Lu http://www.citeulike.org/user/zwang/author/Lu CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/zwang/article/2428519 <i>J. Virol., Vol. 82, No. 6. (15 March 2008), pp. 3011-3020.</i><br /><br />Here we report the crystal structure of hemagglutinin (HA) from influenza B/Hong Kong/8/73 (B/HK) virus determined to 2.8 A. At a sequence identity of [~]25% to influenza A virus HAs, B/HK HA shares a similar overall structure and domain organization. More than two dozen amino acid substitutions on influenza B virus HAs have been identified to cause antigenicity alteration in site-specific mutants, monoclonal antibody escape mutants, or field isolates. Mapping these substitutions on the structure of B/HK HA reveals four major epitopes, the 120 loop, the 150 loop, the 160 loop, and the 190 helix, that are located close in space to form a large, continuous antigenic site. Moreover, a systematic comparison of known HA structures across the entire influenza virus family reveals evolutionarily conserved ionizable residues at all regions along the chain and subunit interfaces. These ionizable residues are likely the structural basis for the pH dependence and sensitivity to ionic strength of influenza HA and hemagglutinin-esterase fusion proteins. 10.1128/JVI.02477-07 Crystal Structure of Unliganded Influenza B Virus Hemagglutinin Qinghua Wang Feng Cheng Mingyang Lu Xia Tian Jianpeng Ma doi:10.1128/JVI.02477-07 J. Virol., Vol. 82, No. 6. (15 March 2008), pp. 3011-3020. 2008-02-26T06:08:38-00:00 2008 J. Virol. 82 6 3011 3020 influenza structure virus http://www.citeulike.org/user/zwang/article/1561529 <i>Bioinformatics (10 July 2007), btm348.</i><br /><br />Motivation: To understand transcription regulatory mechanisms, it is indispensable to investigate transcription factor (TF) DNA binding preferences. We noted that the generally acknowledged information of functional annotations of TFs as well as that of their target genes should provide useful hints in determining transcription factor DNA binding preferences. Results: In this contribution, we developed an integrative method based on the Nearest Neighbor Algorithm, to predict DNA binding preferences through integrating both the functional/structural information of transcription factors and the interaction between transcription factors and their targets. The accuracy of cross validation tests on the dataset consisting of 3430 positive samples and 7000 negative samples reaches 87.0% for 10-fold cross-validation and 87.9% for jackknife cross validation test, which is a much better result than that in our previous work (Qian, et al., 2006). The prediction result indicates that the improved method we developed could be a powerful approach to infer the transcription factor DNA preference in silico. 10.1093/bioinformatics/btm348 An Approach to Predict Transcription Factor DNA Binding Site Specificity Based upon Gene and Transcription Factor Functional Categorization Ziliang Qian Lingyi Lu Xiaojun Liu Yu-Dong Cai Yixue Li doi:10.1093/bioinformatics/btm348 Bioinformatics (10 July 2007), btm348. 2007-08-15T02:41:51-00:00 2007 Bioinformatics btm348 binding dna gene prediction site transcription http://www.citeulike.org/user/zwang/article/1232434 <i>Mol Syst Biol, Vol. 3 (17 April 2007)</i> Hubs in biological interaction networks exhibit low changes in expression in experimental asthma Xin Lu Vipul Jain Patricia Finn David Perkins doi:10.1038/msb4100138 Mol Syst Biol, Vol. 3 (17 April 2007) 2007-04-17T16:27:03-00:00 2007 Mol Syst Biol 3 interaction network