Methods in molecular biology
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In the past decade, proteomics and mass spectrometry have taken tremendous strides forward, particularly in the life sciences, spurred on by rapid advances in technology resulting in generation and conglomeration of vast amounts of data. Though this has led to tremendous advancements in biology, the interpretation of the data poses serious challenges for many practitioners due to the immense size and complexity of the data. Furthermore, the lack of annotation means that a potential gold mine of relevant biological information may be hiding within this data. ⋯ We then integrate a suite of freely available bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology and biochemical pathways. We also provide an example of the functional annotation of missing proteins in human chromosome 7 data from the NeXtProt database, where no evidence is available at the proteomic, antibody, or structural levels. We give examples of protocols, tools and detailed flowcharts that can be extended or tailored to interpret and annotate the proteome of any novel organism.
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DNA methylation is a major epigenetic modification that regulates gene expression, genome imprinting, and development and has a role in diseases including cancer. There are various methods for whole-genome methylation profiling that differ in cost and resolution. ⋯ In this chapter, we provide detailed protocols for whole-genome bisulfite sequencing (WGBS), which captures the complete methylome. Using WGBS, we are able to generate a reference DNA methylome for normal or malignant hematopoietic cells.
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Multiplex assays that allow the simultaneous measurement of multiple analytes in small sample quantities have developed into a widely used technology. Their implementation spans across multiple assay systems and can provide readouts of similar quality as the respective single-plex measures, albeit at far higher throughput. Multiplex assay systems are therefore an important element for biomarker discovery and development strategies but analysis of the derived data can face substantial challenges that may limit the possibility of identifying meaningful biological markers. This chapter gives an overview of opportunities and challenges of multiplexed biomarker analysis, in particular from the perspective of machine learning aimed at identification of predictive biological signatures.
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Network analysis methods are increasing in popularity. An approach commonly applied to analyze proteomics data involves the use of protein-protein interaction (PPI) networks to explore the systems-level cooperation between proteins identified in a study. ⋯ Here we describe a method for calculating robust empirical p-values for protein interaction networks. We also provide a worked example with python code demonstrating the implementation of this methodology.
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Whole-genome bisulfite sequencing (WGBS) has become a powerful tool to dissect genome-wide methylation profiles at single-base resolution. In this chapter we describe in detail the bioinformatics pipeline used for the analysis of ARGONAUTE-dependent DNA methylation in Arabidopsis thaliana. We provide tools and command lines used for mapping bisulfite sequencing reads, for estimating methylation levels at individual cytosine sites, for identifying differentially methylated regions (DMRs), and for calculating methylation levels of DMRs.