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      Comprehensive viral oligonucleotide probe design using conserved protein regions

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          Abstract

          Oligonucleotide microarrays have been applied to microbial surveillance and discovery where highly multiplexed assays are required to address a wide range of genetic targets. Although printing density continues to increase, the design of comprehensive microbial probe sets remains a daunting challenge, particularly in virology where rapid sequence evolution and database expansion confound static solutions. Here, we present a strategy for probe design based on protein sequences that is responsive to the unique problems posed in virus detection and discovery. The method uses the Protein Families database (Pfam) and motif finding algorithms to identify oligonucleotide probes in conserved amino acid regions and untranslated sequences. In silico testing using an experimentally derived thermodynamic model indicated near complete coverage of the viral sequence database.

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          Most cited references39

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          Profile hidden Markov models.

          S. Eddy (1998)
          The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available. HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise.
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            Pfam: clans, web tools and services

            Pfam is a database of protein families that currently contains 7973 entries (release 18.0). A recent development in Pfam has enabled the grouping of related families into clans. Pfam clans are described in detail, together with the new associated web pages. Improvements to the range of Pfam web tools and the first set of Pfam web services that allow programmatic access to the database and associated tools are also presented. Pfam is available on the web in the UK (), the USA (), France () and Sweden ().
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              A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics.

              A unified view of polymer, dumbbell, and oligonucleotide nearest-neighbor (NN) thermodynamics is presented. DNA NN DeltaG degrees 37 parameters from seven laboratories are presented in the same format so that careful comparisons can be made. The seven studies used data from natural polymers, synthetic polymers, oligonucleotide dumbbells, and oligonucleotide duplexes to derive NN parameters; used different methods of data analysis; used different salt concentrations; and presented the NN thermodynamics in different formats. As a result of these differences, there has been much confusion regarding the NN thermodynamics of DNA polymers and oligomers. Herein I show that six of the studies are actually in remarkable agreement with one another and explanations are provided in cases where discrepancies remain. Further, a single set of parameters, derived from 108 oligonucleotide duplexes, adequately describes polymer and oligomer thermodynamics. Empirical salt dependencies are also derived for oligonucleotides and polymers.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2008
                13 December 2007
                13 December 2007
                : 36
                : 1
                : e3
                Affiliations
                1Center for Infection and Immunity, Mailman School of Public Health, Columbia University, 722 West 168th Street, Room 1801, New York, NY 10032, 2Sigma-Aldrich, Research Biotech, 2909 Laclede Ave, St. Louis, MO 63103, USA, 3Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, H-1518 Budapest, PO Box 7, Hungary and 4Center for Biomedical Informatics, Department of Medicine, Section of Genetic Medicine, University of Chicago, 5841 South Maryland Ave, AMB N660B, Chicago, IL 60637, USA
                Author notes
                *To whom correspondence should be addressed. +1 212 342 9031+1 212 342 9044 wil2001@ 123456columbia.edu
                Article
                10.1093/nar/gkm1106
                2248741
                18079152
                ab437967-b28c-4ced-b6c9-cf932e397f26
                © 2007 The Author(s)

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 October 2007
                : 26 November 2007
                : 27 November 2007
                Categories
                Methods Online

                Genetics
                Genetics

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