To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community.

Recommendations about structuring proteomic biomarker studies should increase the probability that such markers will be clinically useful.

The accurate in silico simulation of metagenomic datasets is of great importance for benchmarking bioinformatics tools as well as for experimental design. Users are dependant on large-scale simulation to not only design experiments and new projects but also for accurate estimation of computational needs within a project. Unfortunately, most current read simulators are either not suited for metagenomics, out of date or relatively poorly documented. In this article, we describe InSilicoSeq, a software package to simulate metagenomic Illumina sequencing data. InsilicoSeq has a simple command-line interface and extensive documentation. InSilicoSeq is implemented in Python and capable of simulating realistic Illumina (meta) genomic data in a parallel fashion with sensible default parameters. Source code and documentation are available under the MIT license at https://github.com/HadrienG/InSilicoSeq and https://insilicoseq.readthedocs.io/. Supplementary data are available at Bioinformatics online.

Eur J Clin Invest 2012; 42 (9): 1027–1036 While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well‐described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare.

Purpose: Urine proteomics is emerging as a powerful tool for biomarker discovery. The purpose of this study is the development of a well‐characterized “real life” sample that can be used as reference standard in urine clinical proteomics studies.Experimental design: We report on the generation of male and female urine samples that are extensively characterized by different platforms and methods (CE‐MS, LC‐MS, LC‐MS/MS, 1‐D gel analysis in combination with nano‐LC MS/MS (using LTQ‐FT ultra), and 2‐DE‐MS) for their proteome and peptidome. In several cases analysis involved a definition of the actual biochemical entities, i.e. proteins/peptides associated with molecular mass and detected PTMs and the relative abundance of these compounds.Results: The combination of different technologies allowed coverage of a wide mass range revealing the advantages and complementarities of the different technologies. Application of these samples in “inter‐laboratory” and “inter‐platform” data comparison is also demonstrated.Conclusions and clinical relevance: These well‐characterized urine samples are freely available upon request to enable data comparison especially in the context of biomarker discovery and validation studies. It is also expected that they will provide the basis for the comprehensive characterization of the urinary proteome.

The Bacillus amyloliquefaciens subsp. plantarum strain UCMB5113 is a Gram-positive rhizobacterium that can colonize plant roots and stimulate plant growth and defense based on unknown mechanisms. This reinforcement of plants may provide protection to various forms of biotic and abiotic stress. To determine the genetic traits involved in the mechanism of plant-bacteria association, the genome sequence of UCMB5113 was obtained by assembling paired-end Illumina reads. The assembled chromosome of 3,889,532 bp was predicted to encode 3,656 proteins. Genes that potentially contribute to plant growth promotion such as indole-3-acetic acid (IAA) biosynthesis, acetoin synthesis and siderophore production were identified. Moreover, annotation identified putative genes responsible for non-ribosomal synthesis of secondary metabolites and genes supporting environment fitness of UCMB5113 including drug and metal resistance. A large number of genes encoding a diverse set of secretory proteins, enzymes of primary and secondary metabolism and carbohydrate active enzymes were found which reflect a high capacity to degrade various rhizosphere macromolecules. Additionally, many predicted membrane transporters provides the bacterium with efficient uptake capabilities of several nutrients. Although, UCMB5113 has the possibility to produce antibiotics and biosurfactants, the protective effect of plants to pathogens seems to be indirect and due to priming of plant induced systemic resistance. The availability of the genome enables identification of genes and their function underpinning beneficial interactions of UCMB5113 with plants.