Advances in high-throughput omic technologies allow for assaying a growing compendium of molecular layers, ranging from genome and epigenome profiling and transcriptomics to proteomics and ...

Quantitative data analysis is important for any single-molecule localization microscopy (SMLM) workflow to extract biological insights from the coordinates of the single fluorophores. However, current ...

Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Even as large language models have ...

The OMOP Oncology Module provides a platform for standardization of cancer data enabling the conduct of observational cancer studies and identifying patient cohorts in a distributed research network.

An enterprise conceptual data model is often seen as a high mountain to be climbed, a journey that will last a lifetime. People have visions of 10 feet or more of wall in the corporate offices ...

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...

When a conversation turns to analytics or big data, the terms structured, semi-structured and unstructured might get bandied about. These are classifications of data that are now important to ...

Back in the 1970s, the ANSI SPARC three-tiered model arose, foreshadowing a smooth intertwining of data and architectural design. The three tiers concept isolated the physical storage needs of data ...