Embedding machine-readable proteins interactions data in scientific articles for easy access and retrieval

Extraction of protein-protein interactions data from scientific literature remains a hard, time- and resource-consuming task. This task would be greatly simplified by embedding in the source, i.e. research articles, a standardized, synthetic, machine-readable codification for protein-protein interactions data description, to make the identification and the retrieval of such very valuable information easier, faster, and more reliable than now.
We shortly discuss how this information can be easily encoded and embedded in research papers with the collaboration of authors and scientific publishers, and propose an online demonstrative tool that shows how to help and allow authors for the easy and fast conversion of such valuable biological data into an embeddable, accessible, computer-readable codification

Charting the NF-kB pathway interactome map

One of the phenomena observed in human aging is the progressive increase of a systemic inflammatory state, a condition referred to as “inflammaging”, negatively correlated with longevity. The five components of the Nuclear Factor kB (NF-kB) family are prominent mediators of inflammation. Several different signaling pathways activated by very diverse stimuli converge on NF-kB, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of this analysis is to provide a wider, systemic picture of such intricate signaling system

Encoding the states of interacting proteins to facilitate biological pathways reconstruction

<p>Abstract</p> <p>Background</p> <p>In a systems biology perspective, protein-protein interactions (PPI) are encoded in machine-readable formats to avoid issues encountered in their retrieval for the reconstruction of comprehensive interaction maps and biological pathways. However, the information stored in electronic formats currently used doesn't allow a valid automatic reconstruction of biological pathways.</p> <p>Results</p> <p>We propose a logical model of PPI that takes into account the "state" of proteins before and after the interaction. This information is necessary for proper reconstruction of the pathway.</p> <p>Conclusions</p> <p>The adoption of the proposed model, which can be easily integrated into existing machine-readable formats used to store the PPI data, would facilitate the automatic or semi-automated reconstruction of biological pathways.</p> <p>Reviewers</p> <p>This article was reviewed by Dr. Wen-Yu Chung (nominated by Kateryna Makova), Dr. Carl Herrmann (nominated by Dr. Purificación López-García) and Dr. Arcady Mushegian.</p

The Histone Methyltransferase Wbp7 Controls Macrophage Function through GPI Glycolipid Anchor Synthesis

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Charting the NF-κB Pathway Interactome Map

Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of the present analysis is to provide a wider, systemic picture of the NF-κB signaling system. Data from different sources such as literature, functional enrichment web resources, protein-protein interaction and pathway databases have been gathered, curated, integrated and analyzed in order to reconstruct a single, comprehensive picture of the proteins that interact with, and participate to the NF-κB activation system. Such a reconstruction shows that the NF-κB interactome is substantially different in quantity and quality of components with respect to canonical representations. The analysis highlights that several neglected but topologically central proteins may play a role in the activation of NF-κB mediated responses. Moreover the interactome structure fits with the characteristics of a bow tie architecture. This interactome is intended as an open network resource available for further development, refinement and analysis

Fish the ChIPs: a pipeline for automated genomic annotation of ChIP-Seq data

<p>Abstract</p> <p>Background</p> <p>High-throughput sequencing is generating massive amounts of data at a pace that largely exceeds the throughput of data analysis routines. Here we introduce Fish the ChIPs (FC), a computational pipeline aimed at a broad public of users and designed to perform complete ChIP-Seq data analysis of an unlimited number of samples, thus increasing throughput, reproducibility and saving time.</p> <p>Results</p> <p>Starting from short read sequences, FC performs the following steps: 1) quality controls, 2) alignment to a reference genome, 3) peak calling, 4) genomic annotation, 5) generation of raw signal tracks for visualization on the UCSC and IGV genome browsers. FC exploits some of the fastest and most effective tools today available. Installation on a Mac platform requires very basic computational skills while configuration and usage are supported by a user-friendly graphic user interface. Alternatively, FC can be compiled from the source code on any Unix machine and then run with the possibility of customizing each single parameter through a simple configuration text file that can be generated using a dedicated user-friendly web-form. Considering the execution time, FC can be run on a desktop machine, even though the use of a computer cluster is recommended for analyses of large batches of data. FC is perfectly suited to work with data coming from Illumina Solexa Genome Analyzers or ABI SOLiD and its usage can potentially be extended to any sequencing platform.</p> <p>Conclusions</p> <p>Compared to existing tools, FC has two main advantages that make it suitable for a broad range of users. First of all, it can be installed and run by wet biologists on a Mac machine. Besides it can handle an unlimited number of samples, being convenient for large analyses. In this context, computational biologists can increase reproducibility of their ChIP-Seq data analyses while saving time for downstream analyses.</p> <p>Reviewers</p> <p>This article was reviewed by Gavin Huttley, George Shpakovski and Sarah Teichmann.</p