BioDWH is a novel bioinformatics data warehouse software kit that integrates biological information from multiple public life science data sources into a local database management system.
To bring forward spatial information, data and mapping applications were developed to serve regional biological and oceanographic data from multiple sources (Figure 3B).
As a whole, ArrayAnalysis.org is continuously being improved, evolving into a one-step solution for pre-processing, statistical analysis, and biological interpretation of data from multiple technological platforms.
Data-reuse provides tremendous opportunity to extract new knowledge from existing experiments, and offers a unique opportunity for robust, multi-'omics analyses by merging metadata (information about experimental design, biological samples, protocols) and data from multiple experiments.
In summary, cellPACK unites existing and novel packing algorithms to generate, visualize and analyze comprehensive 3D models of complex biological environments that integrate data from multiple experimental sources.
We take advantage of the success of the Open Biomedical Ontologies Foundry project (Smith et al., 2007), which aims to standardize and create controlled vocabularies across multiple biological domains, and utilize data from multiple ontologies to facilitate computational analysis of natural language descriptions.
In high-throughput biological data analysis, multiple hypothesis testing is employed to address certain biological problems.
This is demonstrated in the next section, where we used real biological data with multiple biological and technical replicates.
Testing for rhythmicity in time series of biological data presents multiple challenges [ 27, 28].
In this manuscript, we consider not only microarray data but also high-throughput data from multiple biological levels.
