BioXplor has developed a unique and powerful Protein Discovery Engine for academics and industry scientists to rapidly discover published protein-related information up 25x faster than standard search engines. The engine combines 50 ontologies with a semantic layer to rank relevant sentences, and advanced features for trend analysis, novel predictions, text mining, and interactive charts and graphs.

Scientists can navigate published literature for experimental methods to identify optimal protocol conditions, together with the product recommendations to execute the experiment successfully by matching the most referenced reagents and instruments. Suppliers can access the search engine to extract sentences and figure images as references for their research products, and to understand the protein and application-specific literature trends to help with new product development.

Data scientists and bioinformaticians can integrate BioXplor’s highly annotated knowledgebase into their genomics workflow via BioXpor’s API.  Users can also access BioXplor’s advanced text mining tool with over 50 integrated ontologies for rapid text mining.

BioXplor’s proprietary ABC-Dimensions distant supervision and feature engineering technology is used to predict novel disease biomarkers, by combining BioXplor’s knowledgebase with genomics data repositories. Many hypotheses are generated from literature and then matched with differential expression profiles from disease-specific gene expression databases to rank the hypotheses.

Discovery partnerships combining proprietary clinical trials data with BioXplor’s unique knowledgebase and ABC-Dimensions technology (machine learning and feature engineering) to identify patient super-responders by SNP and clinical measurements. This approach, applying secondary use of clinical trials data, is powerful for patient stratification.

Identifying protein trends and patterns for an immunoassay protein signature, and designing the assays including the optimal commercial antibodies and conditions to develop the assay. BioXplor has developed a powerful literature-based engine optimized for this purpose, and as part of a discovery partnership, clinical trial or gene expression data can be integrated for further validation.

BioXplor’s ABC-Dimensions technology and protein knowledgebase are applied to predict novel indications for existing drugs, based on the drug target, and predict adverse events for novel indications. BioXplor has also developed a powerful semantic literature search engine for teams who need to regularly keep up to date on the latest literature trends for drug target-based insights on indications.

Discovery of novel drug and disease pathways using BioXplor’s proprietary ABC-Dimensions technology to identify protein-protein relationships.  The algorithm uses validation databases of known pathways together with literature-based hypotheses generation to find novel therapeutic and disease pathway proteins.

Discovery partnerships to identifying novel disease-related proteins, pathways and druggable targets using BioXplor’s ABC-Dimensions technology and knowledgebase together with patient genomics data. This approach is very powerful for novel target ID and pathway elucidation in orphan/rare diseases. Scientists can also access BioXplor’s powerful literature-based discovery engine for Target ID.