Brain Radiation Information Data Exchange (BRIDE): integration of experimental data from low-dose ionising radiation research for pathway discovery

BRIDE v2: A Validated Collection of Genes Involved in the Mammalian Brain Response to Low-Dose Ionizing Radiation

There is significant interest in the response of the mammalian brain to low-dose ionizing radiation (LDIR), mainly examined by gene or protein expression, with applications in radiation safety on Earth, the atmosphere and outer space. Potential associations of molecular-level responses with sensory or cognitive defects and neurodegenerative diseases are currently under investigation. Previously, we have described a light-weight approach for the storage, analysis and distribution of relevant datasets, with the platform BRIDE. We have re-implemented the platform as BRIDE v2 on the cloud, using the bioinformatics infrastructure ELIXIR. We connected the annotated list of 3174 unique gene records with modern omics resources for downstream computational analysis. BRIDE v2 is a cloud-based platform with capabilities that enable researchers to extract, analyze, visualize as well as export the gene collection. The resource is freely available online at <http://bride-db.eu>.

The Coming of Age for Big Data in Systems Radiobiology, an Engineering Perspective

As high-throughput approaches in biological and biomedical research are transforming the life sciences into information-driven disciplines, modern analytics platforms for big data have started to address the needs for efficient and systematic data analysis and interpretation. We observe that radiobiology is following this general trend, with -omics information providing unparalleled depth into the biomolecular mechanisms of radiation response-defined as systems radiobiology. We outline the design of computational frameworks and discuss the analysis of big data in low-dose ionizing radiation (LDIR) responses of the mammalian brain. Following successful examples and best practices of approaches for the analysis of big data in life sciences and health care, we present the needs and requirements for radiation research. Our goal is to raise awareness for the radiobiology community about the new technological possibilities that can capture complex information and execute data analytics on a large scale. The production of large data sets from genome-wide experiments (quantity) and the complexity of radiation research with multidimensional experimental designs (quality) will necessitate the adoption of latest information technologies. The main objective was to translate research results into applied clinical and epidemiological practice and understand the responses of biological tissues to LDIR to define new radiation protection policies. We envisage a future where multidisciplinary teams include data scientists, artificial intelligence experts, DevOps engineers, and of course radiation experts to fulfill the augmented needs of the radiobiology community, accelerate research, and devise new strategies.

Developing computational biology at meridian 23° E, and a little eastwards

Modern biology is experiencing a deep transformation by the expansion of molecular-level measurements at all scales, using omics technologies. A key element in this transformation is the field of bioinformatics, that has—in the meanwhile—permeated pretty much all of biological and biomedical research and is now emerging as a key inter-disciplinary area that connects the natural sciences, chemical and electrical engineering, science education and science policy, on a number of science and technology fronts. The strong tradition of open access for large volumes of raw data, collections of complex results and high-quality algorithm implementations in bioinformatics makes the field a unique, special case of open science. We report on our recent research activities, the development of training initiatives in the wider region during the past years, and the lessons learned regarding our efforts away from major epicenters, within the general context of open science.