Identifying differentially coexpressed module during HIV disease progression: A multiobjective approach
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[1] Vipin Kumar,et al. Subspace Differential Coexpression Analysis: Problem Definition and a General Approach , 2010, Pacific Symposium on Biocomputing.
[2] Jun Wang,et al. Deep Sequencing of HIV-Infected Cells: Insights into Nascent Transcription and Host-Directed Therapy , 2014, Journal of Virology.
[3] S. Bandyopadhyay,et al. Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes , 2009, BMC Bioinformatics.
[4] Nitin K Saksena,et al. Why are the neurodegenerative disease-related pathways overrepresented in primary HIV-infected peripheral blood mononuclear cells: a genome-wide perspective , 2012, Virology Journal.
[5] Ujjwal Maulik,et al. Multiobjective Genetic Algorithms for Clustering - Applications in Data Mining and Bioinformatics , 2011 .
[6] H. Ozcelik,et al. Correlation matrix distance, a meaningful measure for evaluation of non-stationary MIMO channels , 2005, 2005 IEEE 61st Vehicular Technology Conference.
[7] Leonardo Calza,et al. Systemic and discoid lupus erythematosus in HIV-infected patients treated with highly active antiretroviral therapy , 2003, International journal of STD & AIDS.
[8] Cavan S Reilly,et al. Microarray Analysis of Lymphatic Tissue Reveals Stage-Specific, Gene Expression Signatures in HIV-1 Infection1 , 2009, The Journal of Immunology.
[9] Sanghamitra Bandyopadhyay,et al. Discovering Condition Specific Topological Pattern Changes in Coexpression Network: An Application to HIV-1 Progression , 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[10] S. Elena,et al. Computational design of host transcription-factors sets whose misregulation mimics the transcriptomic effect of viral infections , 2012, Scientific Reports.
[11] Ju Han Kim,et al. Identifying set-wise differential co-expression in gene expression microarray data , 2009, BMC Bioinformatics.
[12] M. Işık. Thyroid Medullary Carcinoma in a Patient with HIV/AIDS , 2012 .
[13] V. Scaria,et al. Human cellular microRNA hsa-miR-29a interferes with viral nef protein expression and HIV-1 replication , 2008, Retrovirology.
[14] Ujjwal Maulik,et al. A review of in silico approaches for analysis and prediction of HIV-1-human protein-protein interactions , 2015, Briefings Bioinform..
[15] M. Ostrowski,et al. Distinct Transcriptional Profiles in Ex Vivo CD4+ and CD8+ T Cells Are Established Early in Human Immunodeficiency Virus Type 1 Infection and Are Characterized by a Chronic Interferon Response as Well as Extensive Transcriptional Changes in CD8+ T Cells , 2007, Journal of Virology.
[16] Casey S Greene,et al. Predicting targeted drug combinations based on Pareto optimal patterns of coexpression network connectivity , 2013, Genome Medicine.
[17] Rainer Spang,et al. Finding disease specific alterations in the co-expression of genes , 2004, ISMB/ECCB.
[18] Hsien-Da Huang,et al. miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions , 2013, Nucleic Acids Res..
[19] H. Günthard,et al. Role of MicroRNA Modulation in the Interferon-α/Ribavirin Suppression of HIV-1 In Vivo , 2014, PloS one.
[20] Jialing Huang,et al. Cellular microRNAs contribute to HIV-1 latency in resting primary CD4+ T lymphocytes , 2007, Nature Medicine.
[21] J. Margolick,et al. Studies in subjects with long-term nonprogressive human immunodeficiency virus infection. , 1995, The New England journal of medicine.
[22] Sanghamitra Bandyopadhyay,et al. PuTmiR: A database for extracting neighboring transcription factors of human microRNAs , 2010, BMC Bioinformatics.
[23] T. Brown,et al. Thyroid function abnormalities in HIV-infected patients. , 2007, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.
[24] T. Ideker,et al. Differential network biology , 2012, Molecular systems biology.
[25] E. C. Snow,et al. Faculty Opinions recommendation of HIV-1 evades virus-specific IgG2 and IgA responses by targeting systemic and intestinal B cells via long-range intercellular conduits. , 2009 .
[26] Tse-Yi Wang,et al. Associations between HIV and Human Pathways Revealed by Protein-Protein Interactions and Correlated Gene Expression Profiles , 2012, PloS one.
[27] Ker-Chau Li,et al. Genome-wide coexpression dynamics: Theory and application , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[28] Michael Watson,et al. CoXpress: differential co-expression in gene expression data , 2006, BMC Bioinformatics.
[29] Robert I. Jennrich,et al. An Asymptotic χ2 Test for the Equality of Two Correlation Matrices , 1970 .
[30] Ron Shamir,et al. Dissection of Regulatory Networks that Are Altered in Disease via Differential Co-expression , 2013, PLoS Comput. Biol..
[31] Lothar Thiele,et al. A systematic comparison and evaluation of biclustering methods for gene expression data , 2006, Bioinform..
[32] Rainer Breitling,et al. DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules , 2010, BMC Bioinformatics.
[33] Ron Shamir,et al. CLICK and EXPANDER: a system for clustering and visualizing gene expression data , 2003, Bioinform..
[34] A. Riva,et al. Systemic lupus erythematosus and HIV infection: a whimsical relationship. Reports of two cases and review of the literature , 2013, Clinical Rheumatology.
[35] Rui Luo,et al. Is My Network Module Preserved and Reproducible? , 2011, PLoS Comput. Biol..
[36] Guihua Sun,et al. Interplay between HIV-1 infection and host microRNAs , 2011, Nucleic acids research.
[37] Ujjwal Maulik,et al. Incorporating the type and direction information in predicting novel regulatory interactions between HIV-1 and human proteins using a biclustering approach , 2014, BMC Bioinformatics.
[38] Guanming Wu,et al. A network module-based method for identifying cancer prognostic signatures , 2012, Genome Biology.