Seven complementary modules that mirror researchers’ process

Explore an Entity

Holistically search scientific abstracts for genes, proteins, target chemical compounds, or other entities. Enter the genes, diseases, or drugs to locate documents and structured information. View structured data about your searched entities, such as their co-occurrence in articles about other compounds or entities. Filter the documents returned based on source, date, content elements and other factors. Use visualizations to view all supporting documents that include your inputs.

Post-translational Modification Summary

Learn how proteins modify each other. Find post translational modification (PTM) events that act on the protein you specify. Enter a gene and choose a relationship to view the amino acid location on the protein. Discover amino acid locations of your input, along with associated agents and supporting documents. Select an amino acid to view its agents and drill down into supporting documents.

Co-occurrence

In early research stages, discover affinities among entities and see how several concepts relate to other entities. Affinities are based on the statistical significance of the frequency with which different entities are mentioned in the same text.

Choose to search on genes, drugs, diseases or other terms that can co-occur with your input entities in the knowledge base. View or download a table displaying the counts of documents co-occurring with your inputs and other entities. Select a table cell of two intersecting entities to view their co-occurring documents, guided by color-coding indicating higher than expected document counts.

Predict Relationships

Identify potential research targets by exploring features related to both the input entity and ranked targets. Explore predictions for new entity relationships by applying predictive algorithms to existing relationship networks.

Enter an entity of interest for which you would like to see ranked relationships and links to evidence. Investigate and understand the criteria used in the ranking. Adjust the criteria and curate the output. View all supporting evidence Watson has found that includes your inputs and their relationships.

Explore a Chemical

Find chemical compounds that are the same or similar to a compound that you specify by drug name, chemical composition, or molecular structure. Choose the range of similarity to match with your entered chemical. Discover resulting compounds and information about them supported by documents. Drill down into the documents associated with one of the resulting compounds.

Explore a Network

Discover a network of relationships between drugs, targets, and diseases including sentence-level evidence supporting the connections. Enter genes, drugs, or diseases you’d like to research. Narrow the network that returns to results supported by a range of documents and other criteria. Select a node or link to view the supporting material.

Predictive Analytics

Use semantic fingerprinting to expand your research targets by discovering potentially unknown similarities between two sets of biological or chemical entities with known similar characteristics.

Enter a set of genes, drugs, or diseases you know to be similar. Fill a second search field with candidate entities you want to compare to the known effect. View your candidate entities ranked by their similarity to your known entity set. Choose to validate the results by including known entities among your candidate set. Compare individual entities to see evidence of their similarity as determined by other terms that appear most often with them in the literature. Drill down to see a term’s supporting documentation.

How customers use it

IBM and Barrow: Faster progress in the fight against ALS

IBM and Barrow: Faster progress in the fight against ALS

Pfizer to Accelerate Research with Watson for Drug Discovery

Pfizer to Accelerate Research with Watson for Drug Discovery