Literature Lab™ mines PubMed to provide comprehensive and accurate findings from the biomedical literature.
The literature record within PubMed is too vast (>20 million publications to date) to permit comprehensive interrogation and identification of actionable associations through conventional searching. Over 12 million abstracts mention one or more human genes, over 8 million mention one or more pathways, and modern high content genomic technologies are producing data at rates that outpace meaningful interpretation by legacy analysis platforms.
Acumenta Biotech has created Literature Lab™, the only literature mining platform that identifies statistically significant associations between gene lists and key concepts in the literature. At the basic level, Literature Lab™ can explore co-occurrences between term domains, e.g.: diseases versus pathways. At a more rigorous level, Literature Lab™ PLUS interrogates gene lists, including those derived via high content platforms, and scores the strength of each gene set/term association and significance based on 1000 random gene list comparison. It respects the uniqueness of each gene set and returns consistent and unique results accordingly. Literature Lab™ identifies significant associations in a timely manner and reveals concepts and relationships that other gene list analysis platforms cannot.
The base Literature Lab™ application is an easy-to-use query facility that illuminates foundational relationships in clear and actionable formats. You can get started with a free Literature Lab™ database report or data set analysis right aw