Publications
343 results found
Shun M-C, Raghavendra NK, Vandegraaff N, et al., 2007, LEDGF/p75 functions downstream from preintegration complex formation to effect gene-specific HIV-1 integration, GENES & DEVELOPMENT, Vol: 21, Pages: 1767-1778, ISSN: 0890-9369
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- Citations: 364
Ogilvie EM, Khan A, Hubank M, et al., 2007, Specific gene expression profiles in systemic juvenile idiopathic arthritis, ARTHRITIS AND RHEUMATISM, Vol: 56, Pages: 1954-1965, ISSN: 0004-3591
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- Citations: 106
Burns S, Cameron S, Cane P, et al., 2007, Evidence of a decline in transmitted HIV-1 drug resistance in the United Kingdom, AIDS, Vol: 21, Pages: 1035-1039, ISSN: 0269-9370
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- Citations: 60
Kerr JR, Christian P, Hodgetts A, et al., 2007, Current research priorities in chronic fatigue syndrome/myalgic encephalomyelitis: disease mechanisms, a diagnostic test and specific treatments, JOURNAL OF CLINICAL PATHOLOGY, Vol: 60, Pages: 113-116, ISSN: 0021-9746
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- Citations: 17
Fraser K, Wang Z, Li Y, et al., 2007, Noise filtering and microarray image reconstruction via chained fouriers, 7th International Symposium on Intelligent Data Analysis, Publisher: SPRINGER-VERLAG BERLIN, Pages: 308-+, ISSN: 0302-9743
Fraser K, Wang Z, Li Y, et al., 2007, Improving microarray expressions with recalibration, 3rd International Symposium on Computational Life Science, Publisher: AMER INST PHYSICS, Pages: 3-+, ISSN: 0094-243X
Gifford R, de Oliveira T, Rambaut A, et al., 2006, Assessment of automated genotyping protocols as tools for surveillance of HIV-1 genetic diversity, AIDS, Vol: 20, Pages: 1521-1529, ISSN: 0269-9370
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- Citations: 24
Myers R, Clark C, Khan A, et al., 2006, Genotyping <i>Hepatitis B virus</i> from whole- and sub-genomic fragments using position-specific scoring matrices in HBVSTAR, JOURNAL OF GENERAL VIROLOGY, Vol: 87, Pages: 1459-1464, ISSN: 0022-1317
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- Citations: 45
Kellam P, Weiss RA, 2006, Infectogenomics: Insights from the host genome into infectious diseases, Cell, Vol: 124, Pages: 695-697, ISSN: 0092-8674
Five years into the human postgenomic era, we are gaining considerable knowledge about host-pathogen interactions through host genomes. This “infectogenomics” approach should yield further insights into both diagnostic and therapeutic advances, as well as normal cellular function.
Kellam P, 2006, Attacking pathogens through their hosts., Genome Biology, Vol: 7, ISSN: 1474-7596
Through understanding the intricacies of host-pathogen interactions, it is now possible to inhibit the growth of microbes, especially viruses, by targeting host-cell proteins and functions. This new antimicrobial strategy has proved effective in the laboratory and in the clinic, and it has great potential for the future.
Hidvegi NC, Sales KM, Izadi D, et al., 2006, A low temperature method of isolating normal human articular chondrocytes, OSTEOARTHRITIS AND CARTILAGE, Vol: 14, Pages: 89-93, ISSN: 1063-4584
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- Citations: 18
Vinciotti V, Tucker A, Kellam P, et al., 2006, Robust Selection of Predictive Genes via a Simple Classifier., Appl Bioinformatics, Vol: 5, Pages: 1-11, ISSN: 1175-5636
Identifying genes that direct the mechanism of a disease from expression data is extremely useful in understanding how that mechanism works. This in turn may lead to better diagnoses and potentially could lead to a cure for that disease. This task becomes extremely challenging when the data are characterised by only a small number of samples and a high number of dimensions, as is often the case with gene expression data. Motivated by this challenge, we present a general framework that focuses on simplicity and data perturbation. These are the keys for robust identification of the most predictive features in such data. Within this framework, we propose a simple selective naive Bayes classifier discovered using a global search technique, and combine it with data perturbation to increase its robustness for small sample sizes. An extensive validation of the method was carried out using two applied datasets from the field of microarrays and a simulated dataset, all confounded by small sample sizes and high dimensionality. The method has been shown to be capable of selecting genes known to be associated with prostate cancer and viral infections.
Mirkin B, Camargo R, Fenner T, et al., 2006, Aggregating homologous protein families in evolutionary reconstructions of herpesviruses, IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, Publisher: IEEE, Pages: 255-+
Hirsch M, Tucker A, Swift S, et al., 2006, Improved robustness in time series analysis of gene expression data by polynomial model based clustering, 2nd International Symposium on Computational Life Sciences, Publisher: SPRINGER-VERLAG BERLIN, Pages: 1-10, ISSN: 0302-9743
Pillay D, Green H, Matthias R, et al., 2005, Estimating HIV-1 drug resistance in antiretroviral-treated individuals in the United Kingdom, 13th International HIV Drug Resistance Workshop, Publisher: OXFORD UNIV PRESS INC, Pages: 967-973, ISSN: 0022-1899
Myers RE, Gale CV, Harrison A, et al., 2005, A statistical model for HIV-1 sequence classification using the subtype analyser (STAR), BIOINFORMATICS, Vol: 21, Pages: 3535-3540, ISSN: 1367-4803
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- Citations: 33
Kaushik N, Fear D, Richards SCM, et al., 2005, Gene expression in peripheral blood mononuclear cells from patients with chronic fatigue syndrome, JOURNAL OF CLINICAL PATHOLOGY, Vol: 58, Pages: 826-832, ISSN: 0021-9746
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- Citations: 104
Blackham J, Burns S, Cameron S, et al., 2005, Long term probability of detection of HIV-1 drug resistance after starting antiretroviral therapy in routine clinical practice, AIDS, Vol: 19, Pages: 487-494, ISSN: 0269-9370
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- Citations: 81
Vinciotti V, Khanin R, D'Alimonte D, et al., 2005, An experimental evaluation of a loop versus a reference design for two-channel microarrays, BIOINFORMATICS, Vol: 21, Pages: 492-501, ISSN: 1367-4803
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- Citations: 73
O'Neill P, Fraser K, Kellam P, et al., 2005, Pyramidic clustering of large-scale microarray images, COMPUTER JOURNAL, Vol: 48, Pages: 466-479, ISSN: 0010-4620
Swift S, Tucker A, Vinciotti V, et al., 2004, Consensus clustering and functional interpretation of gene-expression data., Genome Biology, Vol: 5, Pages: R94-R94, ISSN: 1474-760X
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus set of clusters from a number of clustering methods should improve confidence in gene-expression analysis. Here we introduce consensus clustering, which provides such an advantage. When coupled with a statistically based gene functional analysis, our method allowed the identification of novel genes regulated by NFkappaB and the unfolded protein response in certain B-cell lymphomas.
Gale CV, Myers R, Tedder RS, et al., 2004, Development of a novel human immunodeficiency virus type 1 subtyping tool, subtype analyzer (STAR): Analysis of subtype distribution in London, AIDS RESEARCH AND HUMAN RETROVIRUSES, Vol: 20, Pages: 457-464, ISSN: 0889-2229
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- Citations: 14
Gubser C, Hué S, Kellam P, et al., 2004, Poxvirus genomes:: a phylogenetic analysis, JOURNAL OF GENERAL VIROLOGY, Vol: 85, Pages: 105-117, ISSN: 0022-1317
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- Citations: 277
Jenner RG, Maillard K, Cattini N, et al., 2003, Kaposi's sarcoma-associated herpesvirus-infected primary effusion lymphoma has a gene expression profile, Proceedings of the National Academy of Sciences of USA, Vol: 100, Pages: 10399-10404, ISSN: 0027-8424
Kaposi's sarcoma-associated herpesvirus is associated with three human tumors: Kaposi's sarcoma, and the B cell lymphomas, plasmablastic lymphoma associated with multicentric Castleman's disease, and primary effusion lymphoma (PEL). Epstein-Barr virus, the closest human relative of Kaposi's sarcoma-associated herpesvirus, mimics host B cell signaling pathways to direct B cell development toward a memory B cell phenotype. Epstein-Barr virus-associated B cell tumors are presumed to arise as a consequence of this virus-mediated B cell activation. The stage of B cell development represented by PEL, how this stage relates to tumor pathology, and how this information may be used to treat the disease are largely unknown. In this study we used gene expression profiling to order a range of B cell tumors by stage of development. PEL gene expression closely resembles that of malignant plasma cells, including the low expression of mature B cell genes. The unfolded protein response is partially activated in PEL, but is fully activated in plasma cell tumors, linking endoplasmic reticulum stress to plasma cell development through XBP-1. PEL cells can be defined by the overexpression of genes involved in inflammation, cell adhesion, and invasion, which may be responsible for their presentation in body cavities. Similar to malignant plasma cells, all PEL samples tested express the vitamin D receptor and are sensitive to the vitamin D analogue drug EB 1089 (Seocalcitol).
Voisset C, Myers RE, Carne A, et al., 2003, Rabbit endogenous retrovirus-H encodes a functional protease, JOURNAL OF GENERAL VIROLOGY, Vol: 84, Pages: 215-225, ISSN: 0022-1317
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- Citations: 8
Kellam P, Holzerlandt R, Gramoustianou E, et al., 2003, Viral bioinformatics: computational views of host and pathogen., Novartis Found Symp, Vol: 254, Pages: 234-247, ISSN: 1528-2511
Wherever cellular life occurs, viruses are also found. As a result, complex organism and cellular antiviral responses co-evolve with virally encoded countermeasures. Since viruses co-opt or interfere with specific cellular pathways during their replication, knowledge of viral genome sequences has helped fundamental understanding of host biology. During viral infection, shifts in the balance between host and viral biological processes result in acute or chronic viral disease pathology accompanied with either active viral replication, viral containment/persistence or viral clearance. Studying host-virus interactions at the level of single gene effects, however, fails to produce a global systems-level understanding. This should now be achievable in the context of complete host and pathogen genome sequences. New experimental methods and computational approaches are rapidly developing, allowing global views of dynamic viral and cellular molecular mechanisms. Systems level virology using DNA microarrays and specific viral data resources will reveal the detailed cellular context in which viruses replicate, highlighting common and distinct antiviral mechanisms, the effect of different host cell gene expression programs, and the response of cells to similar or diverse virus types. Ultimately, microbiology and immunology will tend towards a systems-level view of how host and pathogen interact.
Shepherd AJ, Martin NJ, Johnson RG, et al., 2002, PFDB: a generic protein family database integrating the CATH domain structure database with sequence based protein family resources, BIOINFORMATICS, Vol: 18, Pages: 1666-1672, ISSN: 1367-4803
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- Citations: 8
Holzerlandt R, Orengo C, Kellam P, et al., 2002, Identification of new herpesvirus gene homologs in the human genome, GENOME RESEARCH, Vol: 12, Pages: 1739-1748, ISSN: 1088-9051
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- Citations: 81
Ahn JW, Powell KL, Kellam P, et al., 2002, Gammaherpesvirus lytic gene expression as characterized by DNA array, JOURNAL OF VIROLOGY, Vol: 76, Pages: 6244-6256, ISSN: 0022-538X
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- Citations: 46
Kellam P, Liu X, Martin N, et al., 2002, A framework for modelling virus gene expression data, Pages: 267-279, ISSN: 1088-467X
Short, high-dimensional, Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would be beneficial. Nowhere is this truer than functional genomics where effective ways of analysing gene expression data are urgently needed. Progress in this area could help obtain a "global" view of biological processes, and ultimately lead to a great improvement in the quality of human life. We present a computational framework for modelling this type of data, and report experimental results of applying this framework to the analysis of gene expression data in the virology domain. The framework contains a three-step modelling strategy: correlation search, variable grouping, and short MTS modelling. Novel research is involved in each step which has been individually tested on different real-world datasets in engineering and medicine. This is the first attempt to integrate all these components into a coherent computational framework, and test the framework on a very challenging application area, producing promising results. © 2002-IOS Press. All rights reserved.
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