Intra-Exon Motif Correlations as a Proxy Measure for Mean Per-Tile Sequence Quality Data in RNA-Seq.

Given the wide variability in the quality of next-generation sequencing data submitted to public repositories, it is essential to identify methods that can perform quality control on these data sets when additional quality control data, such as mean tile data, are missing from public repositories. In this study, we present evidence that correlating counts of reads corresponding to pairs of motifs separated over specific distances on individual exons can be used as a proxy mean tile data in the data sets we analyzed and hence could be used when mean tile data are not available. As test data sets we use the in vitro transcribed (IVT) data set, and a data set comprising wild and mutant types.

The application of Hadoop in structural bioinformatics.

The paper reviews the use of the Hadoop platform in structural bioinformatics applications. For structural bioinformatics, Hadoop provides a new framework to analyse large fractions of the Protein Data Bank that is key for high-throughput studies of, for example, protein-ligand docking, clustering of protein-ligand complexes and structural alignment. Specifically we review in the literature a number of implementations using Hadoop of high-throughput analyses and their scalability.

A Novel Method to Detect Bias in Short Read NGS Data.

Detecting sources of bias in transcriptomic data is essential to determine signals of Biological significance. We outline a novel method to detect sequence specific bias in short read Next Generation Sequencing data. This is based on determining intra-exon correlations between specific motifs.

Investigation into the annotation of protocol sequencing steps in the sequence read archive.

Background: The workflow for the production of high-throughput sequencing data from nucleic acid samples is complex. There are a series of protocol steps to be followed in the preparation of samples for next-generation sequencing. The quantification of bias in a number of protocol steps, namely DNA fractionation, blunting, phosphorylation, adapter ligation and library enrichment, remains to be determined.

Bioinformatics on the cloud computing platform Azure.

We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress.

Dissecting the chromatin interactome of microRNA genes.

Our knowledge of the role of higher-order chromatin structures in transcription of microRNA genes (MIRs) is evolving rapidly. Here we investigate the effect of 3D architecture of chromatin on the transcriptional regulation of MIRs. We demonstrate that MIRs have transcriptional features that are similar to protein-coding genes.

Normalized Affymetrix expression data are biased by G-quadruplex formation.

Probes with runs of four or more guanines (G-stacks) in their sequences can exhibit a level of hybridization that is unrelated to the expression levels of the mRNA that they are intended to measure. This is most likely caused by the formation of G-quadruplexes, where inter-probe guanines form Hoogsteen hydrogen bonds, which probes with G-stacks are capable of forming. We demonstrate that for a specific microarray data set using the Human HG_U133A Affymetrix GeneChip and RMA normalization there is significant bias in the expression levels, the fold change and the correlations between expression levels.

Identifying DNA-binding proteins using structural motifs and the electrostatic potential.

Robust methods to detect DNA-binding proteins from structures of unknown function are important for structural biology. This paper describes a method for identifying such proteins that (i) have a solvent accessible structural motif necessary for DNA-binding and (ii) a positive electrostatic potential in the region of the binding region. We focus on three structural motifs: helix-turn-helix (HTH), helix-hairpin-helix (HhH) and helix-loop-helix (HLH).

Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins.

A method to detect DNA-binding sites on the surface of a protein structure is important for functional annotation. This work describes the analysis of residue patches on the surface of DNA-binding proteins and the development of a method of predicting DNA-binding sites using a single feature of these surface patches. Surface patches and the DNA-binding sites were initially analysed for accessibility, electrostatic potential, residue propensity, hydrophobicity and residue conservation.