Systems biology research demands the availability of tools and technologies that span a
comprehensive range of computational capabilities, including data management, transfer …

Data and process management are among the biggest problems that the Life Sciences face
today, particularly in the areas of Genomics, Proteomics, and Metabolomics. This paper …

Today, scientific data is inevitably digitized, stored in a variety of heterogeneous formats,
and is accessible over the Internet. Scientists need to access an integrated view of multiple …

Knowledge discovery and data correlation require a unified approach to basic data
management. However, achieving such an approach is nearly impossible with hundreds of …

Data from biological research is proliferating rapidly and advanced data storage and
analysis methods are required to manage it. We introduce the main sources of biological …

Conducting bioinformatic analyses involves biologists in expressing requests over a range
of heterogeneous information sources. The TAMBIS (Transparent Access to Multiple …

Research activity in the life science area is becoming increasingly data intensive. Huge
amounts of highly heterogeneous data, including high throughput experiment results …

Cyberinfrastructure makes the development and deployment of bioinformatics applications
easier by providing the framework and components that may be loosely coupled using …

Biological data analysis is typically implemented using a pipeline that combines many data
analysis tools and meta-databases. These pipelines must scale to very large datasets, and …

Systems biology is characterized by a large community of scientists who use a wide variety
of fragmented and competing data sets and computational tools of all scales to support their …