Key factors for successful data integration in biomarker research.

Integrating a wide range of biomedical data such as that rapidly emerging from the use of next-generation sequencing is expected to have a key role in identifying and qualifying new biomarkers to support precision medicine. Here, we highlight some of the challenges for biomedical data integration and approaches to address them.

Circular RNAs are a large class of animal RNAs with regulatory potency.

Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression.

Large-scale de novo prediction of physical protein-protein association.

Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding.

Accounting for redundancy when integrating gene interaction databases.

During the last years gene interaction networks are increasingly being used for the assessment and interpretation of biological measurements. Knowledge of the interaction partners of an unknown protein allows scientists to understand the complex relationships between genetic products, helps to reveal unknown biological functions and pathways, and get a more detailed picture of an organism's complexity. Being able to measure all protein interactions under all relevant conditions is virtually impossible.

The GNB3 C825T polymorphism and essential hypertension: a meta-analysis of 34 studies including 14,094 cases and 17,760 controls.

Objectives: The C825T single nucleotide polymorphism of the G-protein beta3 (GNB3) has been implicated in susceptibility to essential hypertension, through the expression of an alternatively spliced truncated variant. In an effort to clarify earlier inconclusive results, we performed a meta-analysis of population-based case-control genetic association studies.

Methods: Random-effects methods were applied on summary data in order to combine the results of the individual studies.

A database for G proteins and their interaction with GPCRs.

Background: G protein-coupled receptors (GPCRs) transduce signals from extracellular space into the cell, through their interaction with G proteins, which act as switches forming hetero-trimers composed of different subunits (alpha,beta,gamma). The alpha subunit of the G protein is responsible for the recognition of a given GPCR. Whereas specialised resources for GPCRs, and other groups of receptors, are already available, currently, there is no publicly available database focusing on G Proteins and containing information about their coupling specificity with their respective receptors.