In a recent study posted to the bioRxiv* preprint server, researchers developed and elucidated a ‘bridge integration’ method to harmonize single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) ...

In the digital world, companies often have data stored across multiple platforms and systems. They must then be able to successfully integrate and analyze this data if they want to make informed ...

Technologies for analyzing proteome, metabolome, transcriptome, and epigenome data at both spatial and single-cell levels have come a long way. Taken together, these methods provide a holistic view of ...

Scientists from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...

Even as bioprocessors collect ever more data and analyze it with AI-based methods, the industry continues to face a crucial hurdle—data integration. “In most industrial biotech companies or CDMOs with ...

Data integration vs. data ingestion: What are the differences? Your email has been sent With the increasing amount of data being produced, businesses need better ways to handle and use the information ...

Real-world data (RWD) is transforming clinical research, augmenting existing randomized controlled trial (RCT) data to de-risk studies and improve generalizability. With regulators setting clearer ...