Knowledge.bio (LWAS)

Knowledge.bio extracts and analyzes explicit and implicit gene-disease associations from biomedical literature using concept profile technology to expand and contextualize gene-disease relationship data.

Key Features:

• Explicitome Analysis: Identifies explicit gene-disease relations directly stated in scientific publications.
• Implicitome Discovery: Uncovers implied gene-disease associations not explicitly asserted by original authors, termed the implicitome.
• Integration with Experimental Data: Integrates literature-derived associations with high-throughput experimental datasets such as medical sequencing and genome-wide association studies (GWAS) to rationalize associations.
• Nanopublication-based Data Publication: Publishes findings as nanopublications in accordance with FAIR Data Publishing recommendations to ensure findability, accessibility, interoperability, and reusability.

Scientific Applications:

• Prioritization of Candidate Relations: Prioritizes and rationalizes potential gene-disease relations within the context of complex biological data.
• Interpretation of GWAS and Sequencing Results: Aids interpretation of genome-wide association studies (GWAS) and medical sequencing datasets by linking variants and genes to literature-derived associations.
• Hypothesis Generation: Supports identification of novel gene-disease hypotheses by revealing implicit associations from the biomedical literature.
• FAIR Data Sharing: Enables publication of assertions as nanopublications to support reproducibility and data reuse.

Methodology:

Applies concept profile technology to systematically extract and analyze explicit (explicitome) and implicit (implicitome) gene-disease relationships from biomedical literature, integrates results with high-throughput datasets such as medical sequencing and GWAS, and publishes findings as nanopublications.