Filters








74 Hits in 1.3 sec

Phylogenetics of rat inbred strains

Michael A. Thomas, Chin-Fu Chen, Michael I. Jensen-Seaman, Peter J. Tonellato, Simon N. Twigger
2003 Mammalian Genome  
Twigger et al. 2001 ). The Genome Scanner uses the ACP dataset in combination with various genetic and RH maps.  ...  In the case of SHRSP/Riv and MNR/N, that distance would be measured to the point where the BN strains join the dendrogram (30 for MNR/N and 35 for SHRSP/Riv) for a total distance of 65. developed from  ... 
doi:10.1007/s00335-002-2204-5 pmid:12532268 fatcat:46rtvecvlnczzi4l2sogns4vg4

A high frequency boundary element method for scattering by a class of nonconvex obstacles [article]

David P. Hewett and Simon N. Chandler-Wilde and Stephen Langdon and Ashley Twigger
2014 arXiv   pre-print
Indeed, noting that ∂ 2 G k (x, y) ∂n(x)∂n(y) = 2 ∂ 2 Φ k (x, y) ∂n(x)∂n(y) − 2 ∂ 2 Φ k (x, y ) ∂n(x)∂n(y) , x ∈ Γ nc , y ∈ γ, where y := (−y 1 , y 2 ), we find that, for x ∈ Γ nc , γ ∂ 2 G k (x, y) ∂n  ...  (x)∂n(y) u(y) ds(y) = 2 γ ∂ 2 Φ k (x, y) ∂n(x)∂n(y) u(y) ds(y) − 2 γ ∂ 2 Φ k (x, y) ∂n(x)∂n(y) u(y ) ds(y), (23) withγ := {(x 1 , −L nc ) : x 1 > L nc }.  ... 
arXiv:1401.2817v1 fatcat:2jzki5b4fncblf5ove5og4fl6e

Using the NCBO Web Services for Concept Recognition and Ontology Annotation of Expression Datasets

Simon N. Twigger, Joey Geiger, Jennifer R. Smith
2009 Workshop on Semantic Web Applications and Tools for Life Sciences  
To provide enhanced access to expression datasets housed in the NCBI's Gene Expression Omnibus database and to enable new opportunities for data mining we are using the NCBO's Open Biomedical Annotator service to identify concepts and ontology terms in GEO records. Based on this first pass annotation we are curating these datasets using a variety of ontologies covering concepts of relevance to rat researchers, these include anatomy, rat strains, phenotypes and disease. We have built Gminer
more » ... ://gminer.mcw.edu) as a data exploration and curation tool for this work. Data from this project and the Rat Genome Database are available as RDF via the GMiner website for integration with other semantic web tools.
dblp:conf/swat4ls/TwiggerGS09 fatcat:b2w6ct2nmjdqvonik3op57kzk4

ZoomQuant: An application for the quantitation of stable isotope labeled peptides

Brian D. Halligan, Ronit Y. Slyper, Simon N. Twigger, Wayne Hicks, Michael Olivier, Andrew S. Greene
2005 Journal of the American Society for Mass Spectrometry  
Labeling can take place biosynthetically, using media containing 15 N amino acids for example [1] , after sample isolation by introducing a chemical modification using the ICAT reagent [2] [3] [4] ,  ... 
doi:10.1016/j.jasms.2004.11.014 pmid:15734322 pmcid:PMC2793075 fatcat:365626xoxrhbpdqsjcghrp32ii

Low Cost, Scalable Proteomics Data Analysis Using Amazon's Cloud Computing Services and Open Source Search Algorithms

Brian D. Halligan, Joey F. Geiger, Andrew K. Vallejos, Andrew S. Greene, Simon N. Twigger
2009 Journal of Proteome Research  
One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of
more » ... tributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site (http://proteomics.mcw.edu/vipdac).
doi:10.1021/pr800970z pmid:19358578 pmcid:PMC2691775 fatcat:rykxikfg65advfmzfvqg67mxru

What everybody should know about the rat genome and its online resources

Simon N Twigger, Kim D Pruitt, Xosé M Fernández-Suárez, Donna Karolchik, Kim C Worley, Donna R Maglott, Garth Brown, George Weinstock, Richard A Gibbs, Jim Kent, Ewan Birney, Howard J Jacob
2008 Nature Genetics  
Aitman, N. Hübner and A. Kwitek for helpful comments during the preparation of this manuscript.  ...  The European STAR consortium, together with Japanese colleagues, has identified 2.9 million SNPs from genomic DNA of six strains (S Sprague-Dawley, SS/Jr, C O M M E N TA R Y GK/Ox, WKY/Mdc, F344 and  ...  The three most recent rat assemblies from the Baylor Human Genome Sequencing Center are featured on the main Genome Browser C O M M E N TA R Y website; an older release is archived at http:// genome-rn1  ... 
doi:10.1038/ng0508-523 pmid:18443589 pmcid:PMC2505193 fatcat:k5rnfgkj6ngzpkieh27xgwkgpa

The Rat Genome Database Curators: Who, What, Where, Why

Mary Shimoyama, G. Thomas Hayman, Stanley J. F. Laulederkind, Rajni Nigam, Timothy F. Lowry, Victoria Petri, Jennifer R. Smith, Shur-Jen Wang, Diane H. Munzenmaier, Melinda R. Dwinell, Simon N. Twigger, Howard J. Jacob (+1 others)
2009 PLoS Computational Biology  
doi:10.1371/journal.pcbi.1000582 pmid:19956751 pmcid:PMC2775909 fatcat:3uyifumxofel3axr3fcbhlop4m

Simultaneous quantification and identification using 18O labeling with an ion trap mass spectrometer and the analysis software application "ZoomQuant"

Wayne A. Hicks, Brian D. Halligan, Ronit Y. Slyper, Simon N. Twigger, Andrew S. Greene, Michael Olivier
2005 Journal of the American Society for Mass Spectrometry  
In-vivo labeling methods, such as metabolic labeling relying on the incorporation of isotopically labeled specific amino acids [1], or complete substitution of 14 N with 15 N [2], cannot be used for many  ...  Yates et al. have reported success with in-vivo metabolic labeling of rat proteins by providing them with a diet enriched in 15 N labeled amino acids [3] .  ...  In-vivo labeling methods, such as metabolic labeling relying on the incorporation of isotopically labeled specific amino acids [1] , or complete substitution of 14 N with 15 N [2] , cannot be used for  ... 
doi:10.1016/j.jasms.2005.02.024 pmid:15907706 pmcid:PMC2771642 fatcat:yctxmgv7pzha3dbzpwrfllyg7q

InterMOD: integrated data and tools for the unification of model organism research

Julie Sullivan, Kalpana Karra, Sierra A. T. Moxon, Andrew Vallejos, Howie Motenko, J. D. Wong, Jelena Aleksic, Rama Balakrishnan, Gail Binkley, Todd Harris, Benjamin Hitz, Pushkala Jayaraman (+12 others)
2013 Scientific Reports  
Model organisms are widely used for understanding basic biology, and have significantly contributed to the study of human disease. In recent years, genomic analysis has provided extensive evidence of widespread conservation of gene sequence and function amongst eukaryotes, allowing insights from model organisms to help decipher gene function in a wider range of species. The InterMOD consortium is developing an infrastructure based around the InterMine data warehouse system to integrate genomic
more » ... nd functional data from a number of key model organisms, leading the way to improved cross-species research. So far including budding yeast, nematode worm, fruit fly, zebrafish, rat and mouse, the project has set up data warehouses, synchronized data models, and created analysis tools and links between data from different species. The project unites a number of major model organism databases, improving both the consistency and accessibility of comparative research, to the benefit of the wider scientific community. M odel organism research in biological sciences is widespread and essential. From the classic cell cycle studies in yeast 1 , to the regulation of the basic body plan in Drosophila 2 and a wide range of medically relevant research in rats and mice, model organisms have led to many of the major biological discoveries of the last century. The acceleration of data collection due to the technological transformation of recent years has both significantly contributed to the pool of knowledge about individual model organisms and helped confirm the belief that many of the underlying genetic principles are shared across eukaryotes 3 . This conservation of function combined with the rapidly increasing availability of new genome sequences and functional genomic data means that cross-species research promises to contribute to the molecular genetic understanding of a wide range of eukaryotic species. Such cross-organism comparative analysis is powerful for a number of reasons. Making analogous observations in different species can strengthen evidence for a hypothesis, systematically remove gaps in knowledge, and also lead to novel findings, such as a detailed understanding of evolutionary principles and the differences between organisms 4 . Furthermore, specific model organisms have historically been used for advancing different fields of biology, and so by nature tend to provide complementary information. Uniting multiple lines of evidence promises to help the translation of model organism research to medical practice and should have a significant impact on clinical and personalized medicine, as well as health-related genomics. Although cross-species studies are extremely powerful 5 , translating research across organisms is time consuming and requires highly specialized knowledge. Specifically, matching identifiers and coordinates across datasets, followed by collecting relevant (e.g. functional and phenotypic) data from the organisms of interest often requires collation of data from multiple different sources, specialist tools, and manual curation. One of the principal aims of the work described here is to improve the infrastructure for cross-species analysis and make analysis tools more widely accessible to researchers.
doi:10.1038/srep01802 pmid:23652793 pmcid:PMC3647165 fatcat:ylyyacmxdbeclgtk6u5jzqsizy

Tools and strategies for physiological genomics: the Rat Genome Database

Simon N. Twigger, Dean Pasko, Jeff Nie, Mary Shimoyama, Susan Bromberg, Dan Campbell, Jiali Chen, Norberto dela Cruz, Chunyu Fan, Cindy Foote, Glenn Harris, Brian Hickmann (+20 others)
2005 Physiological Genomics  
The broad goal of physiological genomics research is to link genes to their functions using appropriate experimental and computational techniques. Modern genomics experiments enable the generation of vast quantities of data, and interpretation of this data requires the integration of information derived from many diverse sources. Computational biology and bioinformatics offer the ability to manage and channel this information torrent. The Rat Genome Database (RGD; http://rgd. mcw.edu) has
more » ... ped computational tools and strategies specifically supporting the goal of linking genes to their functional roles in rat and, using comparative genomics, to human and mouse. We present an overview of the database with a focus on these unique computational tools and describe strategies for the use of these resources in the area of physiological genomics. Article published online before print. See web site for date of publication
doi:10.1152/physiolgenomics.00040.2005 pmid:16106031 pmcid:PMC4505745 fatcat:a5aranpv5feflcbwjqeddqxg4m

Page 3558 of Psychological Abstracts Vol. 78, Issue 12 [page]

1991 Psychological Abstracts  
Eugene, 32948 Thomas, Philip, 34089 hombs, Barry, 33618 Thompson, an Amy, 324 ed Thompson, B Thompson, Any O41 Thompson, Bruce, = ™ * Garrie B , Mark ¢: Prsir 34273 ’ Michael L., 32476 , Simon G., 32135  ...  T., 32795 Tury, “erenc, 33788 Twigger, Daryll, 34636 Tyagi, Pradee; K., 34856 Tyano, S., Tyler, * nw W., 32743 Tyler, Forrest B., 32962 Tymchuk, Alexander J., 33619 Tynkkynen, Pasi, 3395 52 Tyrer, Peter  ... 

Acknowledgement to Reviewers of Nutrients in 2018

Nutrients Editorial Office
2019 Nutrients  
Eda, Shigetoshi Edurne, Simón Magro Edwards, Adrianne N. Edwards, Cathrina Edwards, Joshua R. Edwards, Sarah Efird, Jimmy Egger, Garry Eiby, Yvonne Eilertsen, Karl-Erik Eisenga, Michele F.  ...  Costello, Rebecca Bortz Coughlan, Melinda Coulson, Samantha Cox Sullivan, Sheila Cox, David N.  ... 
doi:10.3390/nu11010145 fatcat:fcrvhxpqk5epxlje2dex6lujta

A High-Density Integrated Genetic Linkage and Radiation Hybrid Map of the Laboratory Rat

Robert G. Steen, Anne E. Kwitek-Black, Christopher Glenn, Jo Gullings-Handley, William Van Etten, O. Scott Atkinson, Diane Appel, Simon Twigger, Melanie Muir, Tim Mull, Mary Granados, Mushira Kissebah (+19 others)
1999 Genome Research  
Tonellato (Director), Jian Lu, and Simon Twigger. CuraGen Corporation: Project leaders, Jonathan Rothberg and Steve Colman; RH mapping, Chris Glenn (team leader), Michael Popp, and Marc Peden.  ...  cancer, nephritis, immunology IS/Kyo IS/Kyo congenital malformations WN WN/N cancer, severe chronic nephritis LH LH blood pressure LE LE/Mol metabolic disorders LEW LEW/Pit autoimmunity, blood pressure  ... 
doi:10.1101/gr.9.6.ap1 fatcat:hi7ajz42fjecreuqf6xlga7dda

Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry

Shama P. Mirza, Michael Olivier
2008 Physiological Genomics  
Hicks WA, Halligan BD, Slyper RY, Twigger SN, Greene AS, Olivier M.  ...  Chemically, the only difference in these reagents is the substitution of 12 C, 14 N, or 16 O with their heavy isotopes 13 C, 15 N, or 18 O, but since their molecular weights remain unchanged, the chromatographic  ... 
doi:10.1152/physiolgenomics.00292.2007 pmid:18162499 pmcid:PMC2771641 fatcat:kwpqxwd5qre5fmahjiqc423vjm

Meeting Highlights: Genome Informatics

Jo Wixon, Jennifer Ashurst
2003 Comparative and Functional Genomics  
Simon Twigger (Medical College of Wisconsin, USA) and Fredrik Ståhl (Göteborg University, Sweden) described the two official rat databases, both of which are involved in distributing rat gene nomenclature  ...  Their tool can also be used to look for binding sites of dimers, by looking for two sequences (allowing for incomplete conservation) separated by n nucleotides (n = 0-12).  ... 
doi:10.1002/cfg.300 pmid:18629014 pmcid:PMC2447296 fatcat:7rggsgwr5nfs7pc2ptw7qf3ape
« Previous Showing results 1 — 15 out of 74 results