Text mining into various content elements that enable multifaceted exploration

Integrated Text mining and other data ranked Disease from target


Equipped with mining results of a wide variety of documents

Contains the results of text mining of ontology such as genes, diseases, tissues, compounds, functions, and species not only for PubMed but also for various databases. Efficient search for known and unknown information


Multi-step text mining and ranking using known information

Objectively rank diseases from genes and targets based on data obtained by searching various databases for ontology of genes, diseases, tissues, compounds, etc.


Multi-faceted use of pathways, ontology, and phenotypic data

Utilizing data analyzed by text mining with pathways and phenotypes as ontology, and ranking the importance as a target together with other information


Narrowing down assay information by text mining such as experimental methods and background information

A wide range of assay data can be found using text mined data of various background information such as assay experimental methods and descriptions.


Ranking targets from diseases by multi-step text mining

As a means of disease-related information, we add information from multi-step text mining of the literature and provide ranking and evidence of disease-related targets.


Coming Soon

Next minor change

Use for text mining data and workflow analysis

Analysis using text mining data will be added to the new workflow in sequence (coming soon)

Next minor change

Utilization of fusion data of text mining data and activity data

Utilize text mining results including literature and known assays to verify events and predictions obtained from experiments. (Coming soon)