The Freshwater Information Platform: a global online network providing data, tools and resources for science and policy support

Freshwaters are among the most complex, dynamic, and diverse ecosystems globally. Despite their small share of the earth’s surface (less than 1%) they are home to over 10% of all known animal species. Biodiversity decrease in general and freshwater biodiversity decline in particular have recently received increasing attention, and various policy instruments are now targeting the conservation, protection and enhancement of biodiversity and associated ecosystem services. Surveillance programs as well as a variety of research projects have been producing a tremendous amount of freshwater-related information. Though there have been various attempts to build infrastructures for online collection of such data, tools and reports, they often provide only limited access to resources that can readily be extracted for conducting large scale analyses. Here, we present the Freshwater Information Platform, an open system of relevant freshwater biodiversity-related information. We provide a comprehensive overview of the platform’s core components, highlight their values, present options for their use, and discuss future developments. This is complemented by information on the platform’s current management structure, options for contributing data and research results and an outlook for the future

Driver-pressure-impact and response-recovery chains in European rivers: observed and predicted effects on BQEs

The report presented in the following is part of the outcome of WISER’s river Workpackage WP5.1 and as such part of the module on aquatic ecosystem management and restoration. The ultimate goal of WP5.1 is to provide guidance on best practice restoration and management to the practitioners in River Basin Management. Therefore, a series of analyses was undertaken, each of which used a part of the WP5.1 database in order to track two major pathways of biological response: 1) the response of riverine biota to environmental pressures (degradation) and 2) the response of biota to the reduction of these impacts (restoration). This report attempts to provide empirical evidence on the environment-biota relationships for both pathways

Base line studies North Sea wind farms: strategy of approach for pelagic fish

The Dutch Government has decided to allow the construction of a Near Shore Wind Farm (NSW) demonstration project under the condition that a monitoring programme on - among other things - the ecological impacts is carried out. The Dutch government is responsible for providing a thorough description of the ecological reference situation in order to evaluate future effects of planned wind farms. This report describes the detailed plan of approach to establish the occurrence, density, population structure and migration patterns of pelagic fish fauna in the Dutch coastal zone. Sampling sites have been selected such that they cover the planned location of the Near Shore Wind Farm, cover reference sites and provide representative data of the pelagic fish community in the Dutch coastal zone

Gene Expression Commons: an open platform for absolute gene expression profiling.

Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000) of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/) which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples

Bioinformatics tools @ NBBNet: online infrastructure for the management and analysis of biological data

The use of informatics tools for the management and analysis of sequences for nucleic acids and proteins has resulted better throughout capability of wet lab research work to infer biological data to functional biological information. The field of computational biological information management and analysis is generally known as bioinformatics. We discuss some tools and processes which have been developed or integrated into a data management and information presentation pipeline by the Malaysian National Biotechnology and Bioinformatics Network. Central to this is the Bioinformatics Tools @ NBBnet online infrastructure system. This infrastructure system utilizes grid computing technology. In addition, the deployment of niche databases and database shells for research applying specific datasets such as a particular protein function, protein family or genomes have been discussed

Security-oriented data grids for microarray expression profiles

Microarray experiments are one of the key ways in which gene activity can be identified and measured thereby shedding light and understanding for example on biological processes. The BBSRC funded Grid enabled Microarray Expression Profile Search (GEMEPS) project has developed an infrastructure which allows post-genomic life science researchers to ask and answer the following questions: who has undertaken microarray experiments that are in some way similar or relevant to mine; and how similar were these relevant experiments? Given that microarray experiments are expensive to undertake and may possess crucial information for future exploitation (both academically and commercially), scientists are wary of allowing unrestricted access to their data by the wider community until fully exploited locally. A key requirement is thus to have fine grained security that is easy to establish and simple (or ideally transparent) to use across inter-institutional virtual organisations. In this paper we present an enhanced security-oriented data Grid infrastructure that supports the definition of these kinds of queries and the analysis and comparison of microarray experiment results

Benchmarking database systems for Genomic Selection implementation

Motivation: With high-throughput genotyping systems now available, it has become feasible to fully integrate genotyping information into breeding programs. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able to collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize it in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs, one would need an efficient genotyping data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems. Results: We found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix