Results for 'Proteomics'

31 found
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  1.  1
    Towards Cracking the Epigenetic Code Using a Combination of High‐Throughput Epigenomics and Quantitative Mass Spectrometry‐Based Proteomics.Hendrik G. Stunnenberg & Michiel Vermeulen - 2011 - Bioessays 33 (7):547-551.
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  2.  5
    Proteomics and Beyond : A Report on the 3rd Annual Spring Workshop of the HUPO-PSI 21-23 April 2006, San Francisco, CA, USA. [REVIEW]Sandra Orchard, Rolf Apweiler, Robert Barkovich, Dawn Field, John S. Garavelli, David Horn, Andy Jones, Philip Jones, Randall Julian, Ruth McNally, Jason Nerothin, Norman Paton, Angel Pizarro, Sean Seymour, Chris Taylor, Stefan Wiemann & Henning Hermjakob - unknown
    The theme of the third annual Spring workshop of the HUPO-PSI was proteomics and beyond and its underlying goal was to reach beyond the boundaries of the proteomics community to interact with groups working on the similar issues of developing interchange standards and minimal reporting requirements. Significant developments in many of the HUPO-PSI XML interchange formats, minimal reporting requirements and accompanying controlled vocabularies were reported, with many of these now feeding into the broader efforts of the Functional Genomics (...)
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  3.  18
    Functional Genomics Studied by Proteomics.Bent Honoré, Morten Østergaard & Henrik Vorum - 2004 - Bioessays 26 (8):901-915.
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  4.  11
    Information-Theoretic Biodescriptors for Proteomics Maps: Development and Applications in Predictive Toxicology.Subhash C. Basak, Brian D. Gute & Frank Witzmann - 2005 - Complexity 1:2.
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  5.  4
    The Dictionary of Genomics, Transcriptomics, and Proteomics.Miguel A. Andrade‐Navarro - 2009 - Bioessays 31 (12):1367-1369.
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  6.  3
    Book Review: Proteins and Proteomics: A Laboratory Manual and Purifying Proteins for Proteomics: A Laboratory Manual. [REVIEW]K. K. Jain - 2004 - Bioessays 26 (12):1366-1367.
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  7. Proteomics Enhances Evolutionary and Functional Analysis of Reproductive Proteins.Geoffrey D. Findlay & Willie J. Swanson - 2010 - Bioessays 32 (1):26-36.
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  8. Towards a Proteomics Meta-Classification.Anand Kumar & Barry Smith - 2004 - In IEEE Fourth Symposium on Bioinformatics and Bioengineering, Taichung, Taiwan. IEEE Press. pp. 419–427.
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  9. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics.Schulze-Kremer Steffen & Smith Barry - 2005 - Wiley.
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  10. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics, Vol. 4.Schulze-Kremer Steffen & Smith Barry - 2005 - Wiley.
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  11. Protein Ontology: A Controlled Structured Network of Protein Entities.A. Natale Darren, N. Arighi Cecilia, A. Blake Judith, J. Bult Carol, R. Christie Karen, Cowart Julie, D’Eustachio Peter, D. Diehl Alexander, J. Drabkin Harold, Helfer Olivia, Barry Smith & Others - 2013 - Nucleic Acids Research 42 (1):D415-21..
    The Protein Ontology (PRO; http://proconsortium.org) formally defines protein entities and explicitly represents their major forms and interrelations. Protein entities represented in PRO corresponding to single amino acid chains are categorized by level of specificity into family, gene, sequence and modification metaclasses, and there is a separate metaclass for protein complexes. All metaclasses also have organism-specific derivatives. PRO complements established sequence databases such as UniProtKB, and interoperates with other biomedical and biological ontologies such as the Gene Ontology (GO). PRO relates to (...)
     
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  12.  29
    Data Without Models Merging with Models Without Data.Ulrich Krohs & Werner Callebaut - 2007 - In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier. pp. 181--213.
    Systems biology is largely tributary to genomics and other “omic” disciplines that generate vast amounts of structural data. “Omics”, however, lack a theoretical framework that would allow using these data sets as such (rather than just tiny bits that are extracted by advanced data-mining techniques) to build explanatory models that help understand physiological processes. Systems biology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. The former are based (...)
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  13.  8
    Toll-Like Receptor Signaling in Vertebrates: Testing the Integration of Protein, Complex, and Pathway Data in the Protein Ontology Framework.Cecilia Arighi, Veronica Shamovsky, Anna Maria Masci, Alan Ruttenberg, Barry Smith, Darren Natale, Cathy Wu & Peter D’Eustachio - 2015 - PLoS ONE 10 (4):e0122978.
    The Protein Ontology (PRO) provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation of experimentally known forms and annotations thereof is expected to expose discrepancies, differences, and gaps in our knowledge. We have annotated the early events of innate immune signaling mediated by Toll-Like Receptor 3 and 4 complexes in human, mouse, and chicken. The resulting ontology and annotation data set (...)
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  14.  76
    The Protein Ontology: A Structured Representation of Protein Forms and Complexes.Darren Natale, Cecilia N. Arighi, Winona C. Barker, Judith A. Blake, Carol J. Bult, Michael Caudy, Harold J. Drabkin, Peter D’Eustachio, Alexei V. Evsikov, Hongzhan Huang, Jules Nchoutmboube, Natalia V. Roberts, Barry Smith, Jian Zhang & Cathy H. Wu - 2011 - Nucleic Acids Research 39 (1):D539-D545.
    The Protein Ontology (PRO) provides a formal, logically-based classification of specific protein classes including structured representations of protein isoforms, variants and modified forms. Initially focused on proteins found in human, mouse and Escherichia coli, PRO now includes representations of protein complexes. The PRO Consortium works in concert with the developers of other biomedical ontologies and protein knowledge bases to provide the ability to formally organize and integrate representations of precise protein forms so as to enhance accessibility to results of protein (...)
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  15.  1
    The Representation of Protein Complexes in the Protein Ontology.Carol Bult, Harold Drabkin, Alexei Evsikov, Darren Natale, Cecilia Arighi, Natalia Roberts, Alan Ruttenberg, Peter D’Eustachio, Barry Smith, Judith Blake & Cathy Wu - 2011 - BMC Bioinformatics 12 (371):1-11.
    Representing species-specific proteins and protein complexes in ontologies that are both human and machine-readable facilitates the retrieval, analysis, and interpretation of genome-scale data sets. Although existing protin-centric informatics resources provide the biomedical research community with well-curated compendia of protein sequence and structure, these resources lack formal ontological representations of the relationships among the proteins themselves. The Protein Ontology (PRO) Consortium is filling this informatics resource gap by developing ontological representations and relationships among proteins and their variants and modified forms. Because (...)
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  16.  7
    What is the Total Number of Protein Molecules Per Cell Volume? A Call to Rethink Some Published Values.Ron Milo - 2013 - Bioessays 35 (12):1050-1055.
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  17.  4
    Hepatocellular Carcinoma: Diagnostics and Screening.Madhvi Patel, Mohamed If Shariff, Nimzing G. Ladep, Andrew V. Thillainayagam, Howard C. Thomas, Shahid A. Khan & Simon D. Taylor‐Robinson - 2012 - Journal of Evaluation in Clinical Practice 18 (2):335-342.
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  18. TGF-Beta Signaling Proteins and the Protein Ontology.Arighi Cecilia, Liu Hongfang, Natale Darren, Barker Winona, Drabkin Harold, Blake Judith, Barry Smith & Wu Cathy - 2009 - BMC Bioinformatics 10 (Suppl 5):S3.
    The Protein Ontology (PRO) is designed as a formal and principled Open Biomedical Ontologies (OBO) Foundry ontology for proteins. The components of PRO extend from a classification of proteins on the basis of evolutionary relationships at the homeomorphic level to the representation of the multiple protein forms of a gene, including those resulting from alternative splicing, cleavage and/or posttranslational modifications. Focusing specifically on the TGF-beta signaling proteins, we describe the building, curation, usage and dissemination of PRO. PRO provides a framework (...)
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  19. Modular Structurality and Emergent Functionality Within Knowledge Representation Systems.Adam Fedyniuk - 2016 - Semina Scientiarum 15:77-87.
    There are various approaches to ontology metamodelling, and the notion of biologically inspired modular knowledge representation systems can provide insight in the workings of such phenomena as emergent properties of network structures. What is more relevant from knowledge engineering standpoint, such approach could provide innovation and enhancement of the level of expression as well as overall functionality of modular ontologies. To do so, one needs to find biological structures that would be the basis for modularity on different levels of hierarchy (...)
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  20. Post-Genomic Musings. [REVIEW]Massimo Pigliucci - 2007 - Science 317:1172-1173.
    Everyone in biology keeps predicting that the next few years will bring answers to some of the major open questions in evolutionary biology, but there seems to be disagreement on what, exactly, those questions are. Enthusiasts of the various “-omics” (genomics, proteomics, transcriptomics, metabolomics, and even phenomics) believe, as Michael Lynch puts it in the final chapter of The Origins of Genome Architecture, that “we can be confident of two things: the basic theoretical machinery for understanding the evolutionary process (...)
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  21.  6
    Ontologies for the Life Sciences.Steffen Schulze-Kremer & Barry Smith - 2005 - In Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics, vol. 4. Wiley.
    Where humans can manipulate and integrate the information they receive in subtle and ever-changing ways from context to context, computers need structured and context-free background information of a sort which ontologies can help to provide. A domain ontology captures the stable, highly general and commonly accepted core knowledge for an application domain. The domain at issue here is that of the life sciences, in particular molecular biology and bioinformatics. Contemporary life science research includes components drawn from physics, chemistry, mathematics, medicine (...)
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  22.  17
    What is Stemness?Yan Leychkis, Stephen R. Munzer & Jessica L. Richardson - 2009 - Studies in History and Philosophy of Science Part C 40 (4):312-320.
    This paper, addressed to both philosophers of science and stem cell biologists, aims to reduce the obscurity of and disagreements over the nature of stemness. The two most prominent current theories of stemness—the entity theory and the state theory—are both biologically and philosophically unsatisfactory. Improved versions of these theories are likely to converge. Philosophers of science can perform a much needed service in clarifying and formulating ways of testing entity and state theories of stemness. To do so, however, philosophers should (...)
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  23.  42
    Group-Based and Personalized Care in an Age of Genomic and Evidence-Based Medicine: A Reappraisal.Koffi N. Maglo - 2012 - Perspectives in Biology and Medicine 55 (1):137-154.
    Individualized care and equality of care remain two imperatives for formulating any scientifically and morally informed public health policy. Yet both continue to be elusive goals, even in the age of genomics, proteomics, and evidence-based medicine. Nonetheless, with the rapid growth and improvement of human biotechnologies, the need to individualize therapies while allocating medical care equally may result partly from our biological constitution. Human beings are all unique, and their biological differences significantly influence variability in disease causation and therapeutic (...)
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  24.  10
    The Ethics of Biobanks.Sven Ove Hansson - 2004 - Cambridge Quarterly of Healthcare Ethics 13 (4):319-326.
    Due to modern biochemistry and, in particular, recent developments in genomics, proteomics, and bioinformatics, human samples have become the most important raw materials for advancement in the health sciences. Such material has been at the center of fundamental biomedical research for a long time. What is new is its increased usefulness in research with direct clinical relevance, such as the development of drugs. Because of the larger commercial involvement in such research, this has also led to greater economic interests (...)
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  25.  2
    Personalized Medicine in a New Genomic Era: Ethical and Legal Aspects.Maria Shoaib, Mansoor Ali Merchant Rameez, Syed Ather Hussain, Mohammed Madadin & Ritesh G. Menezes - 2017 - Science and Engineering Ethics 23 (4):1207-1212.
    The genome of two completely unrelated individuals is quite similar apart from minor variations called single nucleotide polymorphisms which contribute to the uniqueness of each and every person. These single nucleotide polymorphisms are of great interest clinically as they are useful in figuring out the susceptibility of certain individuals to particular diseases and for recognizing varied responses to pharmacological interventions. This gives rise to the idea of ‘personalized medicine’ as an exciting new therapeutic science in this genomic era. Personalized medicine (...)
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  26.  4
    Hopes for Helsinki: Reconsidering "Vulnerability".L. A. Eckenwiler, C. Ells, D. Feinholz & T. Schonfeld - 2008 - Journal of Medical Ethics 34 (10):765-766.
    The Declaration of Helsinki is recognised worldwide as a cornerstone of research ethics. Working in the wake of the Nazi doctors’ trials at Nuremberg, drafters of the Declaration set out to codify the obligations of physician-researchers to research participants. Its significance cannot be overstated. Indeed, it is cited in most major guidelines on research involving humans and in the regulations of over a dozen countries.Although it has undergone five revisions,1 and most recently incorporated language aimed at addressing concerns over research (...)
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  27.  25
    Proteins and Genes, Singletons and Species.Branko Kozulić - unknown
    Recent experimental data from proteomics and genomics are interpreted here in ways that challenge the predominant viewpoint in biology according to which the four evolutionary processes, including mutation, recombination, natural selection and genetic drift, are sufficient to explain the origination of species. The predominant viewpoint appears incompatible with the finding that the sequenced genome of each species contains hundreds, or even thousands, of unique genes - the genes that are not shared with any other species. These unique genes and (...)
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  28.  10
    Biological Models of Security for Virus Propagation in Computer Networks.Sanjay Goel & Stephen F. S. F. Bush - 2004 - Login, December 29 (6):49--56.
    This aricle discusses the similarity between the propagation of pathogens (viruses and worms) on computer networks and the proliferation of pathogens in cellular organisms (organisms with genetic material contained within a membrane-encased nucleus). It introduces several biological mechanisms which are used in these organisms to protect against such pathogens and presents security models for networked computers inspired by several biological paradigms, including genomics (RNA interference), proteomics (pathway mapping), and physiology (immune system). In addition, the study of epidemiological models for (...)
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  29.  6
    Hopes for Helsinki: Reconsidering “Vulnerability”.Lisa A. Eckenwiler, Carolyn Ells, Dafna Feinholz & Toby Schonfeld - 2008 - Journal of Medical Ethics 34 (10):765-766.
    The Declaration of Helsinki is recognised worldwide as a cornerstone of research ethics. Working in the wake of the Nazi doctors’ trials at Nuremberg, drafters of the Declaration set out to codify the obligations of physician-researchers to research participants. Its significance cannot be overstated. Indeed, it is cited in most major guidelines on research involving humans and in the regulations of over a dozen countries.Although it has undergone five revisions,1 and most recently incorporated language aimed at addressing concerns over research (...)
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  30.  6
    Living Multiples: How Large-Scale Scientific Data-Mining Pursues Identity and Differences.A. Mackenzie & R. McNally - 2013 - Theory, Culture and Society 30 (4):72-91.
    This article responds to two problems confronting social and human sciences: how to relate to digital data, inasmuch as it challenges established social science methods; and how to relate to life sciences, insofar as they produce knowledge that impinges on our own ways of knowing. In a case study of proteomics, we explore how digital devices grapple with large-scale multiples – of molecules, databases, machines and people. We analyse one particular visual device, a cluster-heatmap, produced by scientists by mining (...)
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  31. Ontologies for the Life Sciences.Schulze-Kremer Steffen & Smith Barry - 2005 - In Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. Wiley.
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