BioAsk identifies important biological concepts inside literature abstracts, patents, and clinical records, helping researchers move from unstructured text to structured biomedical knowledge.
Entity recognition helps researchers quickly locate the most important terms, biological concepts, and scientific signals inside large collections of biomedical records.
Detect gene symbols, gene names, genomic concepts, mutations, and gene families inside biomedical text.
Gene extraction helps connect genetic terms to diseases, pathways, protein products, biomarkers, and therapeutic targets.
Identify proteins, enzymes, receptors, antibodies, signaling molecules, and protein complexes.
Protein recognition supports discovery of protein interactions, signaling pathways, target biology, and antibody-related research.
Detect disease names, disorders, syndromes, pathological conditions, cancer types, and clinical indications.
Disease extraction helps group search results by indication, clinical context, biomarker relevance, and therapeutic area.
Identify biological pathways, molecular mechanisms, signaling cascades, metabolic processes, and cellular functions.
Pathway extraction helps connect genes, proteins, and diseases to broader biological mechanisms.
Detect small molecules, inhibitors, therapeutic agents, biologics, antibodies, and chemical compound names.
Drug and compound extraction supports target discovery, patent review, therapeutic mapping, and clinical trial exploration.
Identify species, model organisms, pathogens, viruses, bacteria, human samples, animal models, and experimental systems.
Organism recognition helps researchers understand experimental context, model systems, host-pathogen relationships, and translational relevance.
Detect diagnostic, prognostic, predictive, and pharmacodynamic biomarkers mentioned in biomedical records.
Biomarker extraction supports diagnostic research, patient stratification, assay selection, and clinical-development analysis.
Identify interventions, outcomes, trial phases, patient populations, clinical endpoints, and therapeutic areas.
Clinical entity detection helps connect biomedical research to trials, interventions, outcomes, and translational medicine.
BioAsk scans abstracts, patents, clinical records, and other biomedical text sources.
The system identifies biological terms such as genes, proteins, diseases, pathways, drugs, and biomarkers.
Detected terms are grouped into entity types to make results easier to browse and interpret.
Entities are linked to relationships, themes, categories, and source records.
Paste a short biomedical sentence. This simple demo highlights possible genes, proteins, diseases, pathways, and clinical terms.
| Entity Type | Examples | Research Value |
|---|---|---|
| Genes | TP53, BRCA1, EGFR, KRAS | Genetic association, mutation biology, disease mapping |
| Proteins | p53, HER2, IL-6, EGFR | Protein function, interactions, signaling, targets |
| Diseases | Cancer, Alzheimer’s disease, inflammation | Indication mapping, clinical context, biomarker research |
| Pathways | Apoptosis, DNA repair, MAPK signaling | Mechanism discovery and biological interpretation |
| Drugs & Compounds | Inhibitors, antibodies, biologics, small molecules | Therapeutic target discovery and patent exploration |
| Clinical Concepts | Phase II, endpoints, intervention, patient cohort | Clinical trial analysis and translational research |
Use BioAsk to identify genes, proteins, diseases, pathways, drugs, organisms, biomarkers, and clinical concepts from scientific records.
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