Current protocols in bioinformatics最新文献

Biological processes are regulated at a cellular level by tightly controlled molecular interaction networks, which are collectively known as the interactome. The interactome is not a static entity, but instead is dynamically reorganized or “rewired” under varying temporal, spatial, and environmental conditions. Most network analysis and visualization tools have, to date, been developed for static representations of molecular interaction data. Here, we describe a protocol that provides a step-by-step guide to DyNet, a Cytoscape 3 application that facilitates the visualization and analysis of dynamic molecular interaction networks. DyNet represents a dynamic network as a set of state graphs that are synchronized in their layout. This synchronization is managed in real time and is automatically updated when a graph is manipulated by a user (e.g., dragging, zooming, moving a node). DyNet also provides several statistical tools enabling users to quickly identify and analyze the most ‘rewired’ nodes across many network states. © 2018 by John Wiley & Sons, Inc.

Rfam is a database of non-coding RNA families in which each family is represented by a multiple sequence alignment, a consensus secondary structure, and a covariance model. Using a combination of manual and literature-based curation and a custom software pipeline, Rfam converts descriptions of RNA families found in the scientific literature into computational models that can be used to annotate RNAs belonging to those families in any DNA or RNA sequence. Valuable research outputs that are often locked up in figures and supplementary information files are encapsulated in Rfam entries and made accessible through the Rfam Web site. The data produced by Rfam have a broad application, from genome annotation to providing training sets for algorithm development. This article gives an overview of how to search and navigate the Rfam Web site, and how to annotate sequences with RNA families. The Rfam database is freely available at http://rfam.org. © 2018 by John Wiley & Sons, Inc.

Public availability of biological sequences is essential for their widespread access and use by the research community. The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and functional data. While most protein sequences entering UniProt are imported from other source databases containing nucleotide or 3-D structure data, protein sequences determined at the protein level can be submitted directly to UniProt. To this end, UniProt provides a Web interface called SPIN. This service enables researchers to make their de novo–sequenced proteins available to the scientific community and acquire UniProt accession numbers for use in publications. This unit explains the process of submitting a protein sequence to UniProt using SPIN. The basic protocol describes all the necessary steps for a single sequence. A support protocol gives guidance on how best to deal with exceptionally large datasets. © 2018 by John Wiley & Sons, Inc.

GWIPS-viz is a publicly available browser that provides Genome Wide Information on Protein Synthesis through the visualization of ribosome profiling data. Ribosome profiling (Ribo-seq) is a high-throughput technique which isolates fragments of messenger RNA that are protected by the ribosome. The alignment of the ribosome-protected fragments or footprint sequences to the corresponding reference genome and their visualization using GWIPS-viz allows for unique insights into the genome loci that are expressed as potentially translated RNA. The GWIPS-viz browser hosts both Ribo-seq data and corresponding mRNA-seq data from publicly available studies across a number of genomes, avoiding the need for computational processing on the user side. Since its initial publication in 2014, over 1885 tracks have been produced across 24 genomes. This unit describes the navigation of the GWIPS-viz genome browser, the uploading of custom tracks, and the downloading of the Ribo-seq/mRNA-seq alignment data. © 2018 by John Wiley & Sons, Inc.

The reconstruction of cancer phylogeny trees and quantifying the evolution of the disease is a challenging task. LICHeE and BAMSE are two computational tools designed and implemented recently for this purpose. They both utilize estimated variant allele fraction of somatic mutations across multiple samples to infer the most likely cancer phylogenies. This unit provides extensive guidelines for installing and running both LICHeE and BAMSE. © 2018 by John Wiley & Sons, Inc.

Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed. © 2015 by John Wiley & Sons, Inc.

miRWalk2.0 (http://zmf.umm.uni-heidelberg.de/mirwalk2) is a freely accessible, regularly updated comprehensive archive supplying the largest available collection of predicted and experimentally verified miRNA-target interactions, with various novel and unique features to assist the scientific community. Approximately 949 million interactions between 11,748 miRNAs, 308,700 genes, and 68,460 lncRNAs are documented in miRWalk2.0 with 5,146,217 different kinds of identifiers to offer a one-stop site to collect an abundance of information. This article describes a schematic workflow on how to obtain miRNA-target interactions from miRWalk2.0. © 2016 by John Wiley & Sons, Inc.

The Electron Microscopy Data Bank (EMDB) is a global, openly accessible archive of biomolecular and cellular 3-D reconstructions derived from electron microscopy (EM) data. EMBL-EBI develops Web-based resources to facilitate the reuse of EMDB data. Here we provide protocols for how these resources can be used for searching EMDB, visualizing EMDB structures, statistically analyzing EMDB content, and checking the validity of EMDB structures. Protocols for searching include quick link categories from the main page, links to latest entries released during the weekly cycle, filtered browsing of the entire archive, and a form-based search. For visualization, the ‘volume slicer’ enables slices of EMDB entries to be visualized interactively and in three orthogonal directions. The EMstats Web service provides up-to-date interactive statistical charts analyzing EMDB. All EMDB entries have ‘Visual Analysis’ pages that provide basic validation information for the entry. © 2018 by John Wiley & Sons, Inc.

The IUPHAR/BPS Guide to PHARMACOLOGY is an expert-curated, open-access database of information on drug targets and the substances that act on them. This unit describes the procedures for searching and downloading ligand-target binding data and for finding detailed annotations and the most relevant literature. The database includes concise overviews of the properties of 1,700 data-supported human drug targets and related proteins, divided into families, and 9,000 small molecule and peptide experimental ligands and approved drugs that bind to those targets. More detailed descriptions of pharmacology, function, and pathophysiology are provided for a subset of important targets. The information is reviewed regularly by expert subcommittees of the IUPHAR Committee on Receptor Nomenclature and Drug Classification. A new immunopharmacology portal has recently been added, drawing together data on immunological targets, ligands, cell types, processes and diseases. The data are available for download and can be accessed computationally via Web services. © 2018 by John Wiley & Sons, Inc.

MetaboSignal is an R/Bioconductor package designed to explore the relationships between genes and metabolites, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) as its primary database. It is a network-based approach that allows overlaying metabolic and signaling pathways and exploring the topological relationship between genes (signaling or metabolic genes) and metabolites. MetaboSignal is ideally suited to identify candidate genes in metabolome genome-wide association studies (mGWAS), particularly in the case of trans-acting associations. It can also be used to provide mechanistic explanations of perturbed metabolic patterns observed in genetic models, as well as to identify novel target metabolic pathways of signaling genes. © 2018 by John Wiley & Sons, Inc.