Article
From proteins to proteomes: large scale protein identification by two-dimensional electrophoresis and amino acid analysis.
Macquarie University Centre for Analytical Biotechnology, Macquarie University, Sydney, NSW, Australia.
Bio/Technolgy
02/1996;
14(1):61-5.
pp.61-5
Source: PubMed
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Citations (0)
- Cited In (22)
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Article: Proteomics Tackling Schizophrenia as a Pathway Disorder.
Schizophrenia Bulletin 07/2012; · 8.80 Impact Factor -
Article: Proteomics Databases and Websites
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ABSTRACT: Information avalanche (overload or expansion) in various scientific fields is a novel issue turned out by a number of factors considered necessary to facilitate their record and registration. Though, the biological science and its diverse fields like proteomics are not immune of this event and even may be as the event‟s herald. On the other hand, time as the most valued anxiety of human has encountered a huge mass of information. Therefore, in order to maintain access and ease the understanding of information in several fields some emprises have been prepared. Bioinformatics is an upshot of this anxiety and emprise. Interestingly, proteomics through studying proteins collection in alive things has covered a great portion of bioinformatics. Consequently, a noteworthy outlook on proteomics related databases (DBs) and websites not only can help investigators to face the upcoming archive of databases but also estimate the volume of the needed facilitates. Furthermore, enrichment of the DBs or related websites must be the priority of researchers. Herein, by covering the major proteomics related databases and websites, we have presented a comprehensive classification to simplify and clarify their understanding and applications.Journal of Paramedical Sciences. 09/2012; 3(3). -
Article: Mathematical modelling of the MAP kinase pathway using proteomic datasets.
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ABSTRACT: The advances in proteomics technologies offer an unprecedented opportunity and valuable resources to understand how living organisms execute necessary functions at systems levels. However, little work has been done up to date to utilize the highly accurate spatio-temporal dynamic proteome data generated by phosphoprotemics for mathematical modeling of complex cell signaling pathways. This work proposed a novel computational framework to develop mathematical models based on proteomic datasets. Using the MAP kinase pathway as the test system, we developed a mathematical model including the cytosolic and nuclear subsystems; and applied the genetic algorithm to infer unknown model parameters. Robustness property of the mathematical model was used as a criterion to select the appropriate rate constants from the estimated candidates. Quantitative information regarding the absolute protein concentrations was used to refine the mathematical model. We have demonstrated that the incorporation of more experimental data could significantly enhance both the simulation accuracy and robustness property of the proposed model. In addition, we used the MAP kinase pathway inhibited by phosphatases with different concentrations to predict the signal output influenced by different cellular conditions. Our predictions are in good agreement with the experimental observations when the MAP kinase pathway was inhibited by phosphatase PP2A and MKP3. The successful application of the proposed modeling framework to the MAP kinase pathway suggests that our method is very promising for developing accurate mathematical models and yielding insights into the regulatory mechanisms of complex cell signaling pathways.PLoS ONE 01/2012; 7(8):e42230. · 4.09 Impact Factor
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Keywords
27 proteins
amino acid composition
computer program
correct identifications
disease states
distinctive score patterns
identities
incorrect protein identifications
large-scale screening
molecular weight
normal
polyvinylidene difluoride blots
protein-based gene expression analysis
proteins
report single protein spots
score patterns
simple organisms
SWISS-PROT database
URL address
World Wide Web