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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Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for bridging the gap between soybean translational genomics and molecular breeding. It provides information for six entities including genes/proteins, microRNAs (miRNAs)/small interfering RNAs (sRNA), metabolites, single nucleotide polymorphisms (SNPs), and plant introduction lines and traits. It has a user-friendly web interface publicly available at http://soykb.org , which integrates and presents data in an intuitive manner to the soybean researchers, breeders, and consumers. It incorporates several informatics and analytical tools for integrating and merging various multi-omics datasets.
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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.
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High resolution mass spectrometry has revolutionized proteomics over the past decade, resulting in tremendous amounts of data in the form of mass spectra, being generated in a relatively short span of time. The mining of this spectral data for analysis and interpretation though has lagged behind such that potentially valuable data is being overlooked because it does not fit into the mold of traditional database searching methodologies. ⋯ In this chapter, we propose a methodology to integrate de novo peptide sequencing using three commonly available software solutions in tandem, complemented by homology searching, and manual validation of spectra. This simplified method would allow greater use of de novo sequencing approaches and potentially greatly increase proteome coverage leading to the unearthing of valuable insights into protein biology, especially of organisms whose genomes have been recently sequenced or are poorly annotated.