SUMMARY: Modern bioimaging and related areas such as sensor technology have undergone tremendous development over the last few years. As a result, contemporary imaging techniques, particularly electron microscopy (EM) and light sheet microscopy, can frequently generate datasets attaining sizes of several terabytes (TB). As a consequence, even seemingly simple data operations such as cropping, chromatic- and drift-corrections and even visualisation, poses challenges when applied to thousands of time points or tiles. To address this we developed BigDataProcessor2-a Fiji plugin facilitating processing workflows for TB sized image datasets. AVAILABILITY AND IMPLEMENTATION: BigDataProcessor2 is available as a Fiji plugin via the BigDataProcessor update site. The application is implemented in Java and the code is publicly available on GitHub (https://github.com/bigdataprocessor/bigdataprocessor2). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: We have developed a Web-based tool named 'Harvester' that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. The information on every single protein is assembled on a single HTML page as a combination of database screen-shots and plain text. A full text meta search engine, similar to Google trade mark, allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. A feedback forum allows users to comment on Harvester and to report database inconsistencies. AVAILABILITY: The service is freely available to the academic community at http://harvester.embl.de.