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Mass spectrometry (MS) is the most versatile and comprehensive method in “OMICS” sciences (i.e. in proteomics, genomics, metabolomics and lipidomics). The applications of MS and tandem MS (MS/MS or MSn) provide sequence information of the full complement of biological samples in order to understand the importance of the sequences on their precise and specific functions. Nowadays, the control of polymer sequences and their accurate characterization is one of the significant challenges of current polymer science. Therefore, a similar approach can be very beneficial for characterizing and understanding the complex structures of synthetic macromolecules. MS-based strategies allow a relatively precise examination of polymeric structures (e.g. their molar mass distributions, monomer units, side chain substituents, end-group functionalities, and copolymer compositions). Moreover, tandem MS offer accurate structural information from intricate macromolecular structures; however, it produces vast amount of data to interpret. In “OMICS” sciences, the software application to interpret the obtained data has developed satisfyingly (e.g. in proteomics), because it is not possible to handle the amount of data acquired via (tandem) MS studies on the biological samples manually. It can be expected that special software tools will improve the interpretation of (tandem) MS output from the investigations of synthetic polymers as well. Eventually, the MS/MS field will also open up for polymer scientists who are not MS-specialists. In this review, we dissect the overall framework of the MS and MS/MS analysis of synthetic polymers into its key components. We discuss the fundamentals of polymer analyses as well as recent advances in the areas of tandem mass spectrometry, software developments, and the overall future perspectives on the way to polymer sequencing, one of the last Holy Grail in polymer science.  相似文献   
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Proteomic profiling and biomarker search are analytical tools as many other. Nevertheless, in the proteomic discovery phase considerable sample fractionation is inevitable before readout. Since these procedures are of notable complexity, proteomic tools need in particular analytical quality validation standards as prevail for other analytical methods. With acceptance of the rule of error propagation the values of imprecision and yield of each preparation step determine overall reproducibility and therewith information harvest of a propagated method series. Thereto, we examined recent proteomic reports with reproducibility data and with parallelization, and automation approaches. Based on the data available from literature it is highly probable, that at least a part of current proteomic platforms actually suffer from high technical variance.  相似文献   
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