Methods in molecular biology
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Phosphoproteomics, the systematic study of protein phosphorylation events and cell signaling networks in cells and tissues, is a rapidly evolving branch of functional proteomics. Current phosphoproteomics research provides a large toolbox of strategies and protocols that may assist researchers to reveal key regulatory events and phosphorylation-mediated processes in the cell and in whole organisms. ⋯ We then discuss various tandem mass spectrometry approaches for phosphopeptide sequencing and quantification, and we consider aspects of phosphoproteome data analysis and interpretation. Efficient integration of these stages of phosphoproteome analysis is highly important to ensure a successful outcome of large-scale experiments for studies of phosphorylation-mediated protein regulation.
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In the past decades, a variety of publicly available data repositories and resources have been developed to support protein related information management, data-driven hypothesis generation and biological knowledge discovery. However, there is also an increasing confusion for the researchers who are trying to quickly find the appropriate resources to help them solve their problems. In this chapter, we present a comprehensive review (with categorization and description) of major protein bioinformatics databases and resources that are relevant to comparative proteomics research. We conclude the chapter by discussing the challenges and opportunities for developing new protein bioinformatics databases.
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G-quadruplexes are noncanonical secondary structures formed in DNA sequences containing consecutive runs of guanines. DNA G-quadruplexes have recently emerged as attractive cancer therapeutic targets. It has been shown that the 3' G-rich single-stranded overhangs of human telomeres can form G-quadruplex structures. ⋯ Nuclear magnetic resonance (NMR) spectroscopy has been shown to be a powerful method in determining the G-quadruplex structures under physiologically relevant conditions. We present the NMR methodology used in our research group for structure determination of G-quadruplexes in solution and their interactions with small molecule compounds. An example of a G-quadruplex structure formed in the human telomere sequence recently solved in our laboratory is used as an example.
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Human pluripotent stem cells (PSCs), which include human embryonic stem cells (ESCs) as well as induced pluripotent stem cells (iPSCs), represent an important source of cellular therapies in regenerative medicine and the study of early human development. As such, it is becoming increasingly important to develop methods for the large-scale banking of human PSC lines. There are several well-established methods for the propagation of human PSCs. ⋯ Nevertheless, as the field develops, it will no doubt become increasingly important to produce a bank of cells for clinical use without xenogeneic reagents, particularly nonhuman feeder cells which might harbor viruses with potential risk to human health or cell product integrity. Thus, even for cell lines previously exposed to xenogeneic reagents, it is important to minimize any subsequent exposure of the cell lines to additional adventitious agents. We have specifically described procedures for the growth of hESCs on Matrigel, an animal-matrix, and CELLstart, an animal-free matrix, and these can be used to produce hESCs as part of a clinical manufacturing process.
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This chapter gives a brief overview of text-mining techniques to extract knowledge from large text collections. It describes the basis pipeline of how to come from text to relationships between biological concepts and the problems that are encountered at each step in the pipeline. We first explain how words in text are recognized as concepts. ⋯ This we call implicit information extraction. Fourth, the validation techniques to evaluate a text-mining system such as ROC curves and retrospective studies are discussed. We conclude by examining how text information can be combined with other non-textual data sources such as microarray expression data and what the future directions are for text-mining within the Internet.