Abstract: Method and system for managing and evaluating life science data. Life Science data is placed in a knowledge base, that may be used for a variety of analysis tasks. Creating a knowledge base from the life science data involves generating two or more nodes indicative of life science data, assigning to one or more pairs of nodes a representation descriptor that corresponds to a relationship between the nodes, and assembling the nodes and the relationship descriptor into a database, such that at least one of the nodes is joined to another node by a representation descriptor. In some embodiments, the representation descriptor includes a case frame that describes the relationships between elements of life science data.

Abstract: Method and system for managing and evaluating life science data. Life Science data is placed in a knowledge base, that may be used for a variety of analysis tasks. Creating a knowledge base from the life science data involves generating two or more nodes indicative of life science data, assigning to one or more pairs of nodes a representation descriptor that corresponds to a relationship between the nodes, and assembling the nodes and the relationship descriptor into a database, such that at least one of the nodes is joined to another node by a representation descriptor. In some embodiments, the representation descriptor includes a case frame that describes the relationships between elements of life science data.

Abstract: Disclosed are methods, systems and apparatus for constructing assemblies of biological knowledge constituting a biological knowledge base, and for subsetting and transforming life sciences-related data and information into biological models to facilitate computation and electronic reasoning on biological information. A subset of data is extracted from a global knowledge base or repository to reconstruct a more specialized sub-knowledge base or assembly designed specifically for the purpose at hand. Assemblies generated by the invention permit selection and rational organization of seemingly diverse data into a model of any selected biological system, as defined by any desired biological criteria. These assemblies can be mined easily and can be logically reasoned with great productivity and efficiency.

Abstract: A method and system for ordering treatment or transport of victims of a mass casualty incident, prior to the incident, by establishing simulated casualty severity scores for each of the victims and considering the casualty severity scores and simulated resource availability. The order of treatment is provided on a card, chart, table or graph. Ordering treatment occurs through an analysis of triage simulations using analytical or mathematical programming techniques considering the severity scores, time periods of treatment delay resulting from constrained resources, estimated survival probabilities, and/or deterioration rates applied to the severity scores due to treatment delay.

Abstract: An epistemic engine system and methods are provided, which accept biological data from experiments or other sources, and automatically produce a model, such as a genomic and protein interaction network, which attempts to explain the operation of a biological system. The system and methods identify interrelationships among components of a biological system, consistent with the biological data and other life science knowledge. In preferred embodiments, evolutionary algorithms are used, in combination with information from a life science knowledge base and experimental data, to generate models that may identify these interrelationships. The output of an epistemic engine permits scientists to better understand biological systems, to propose hypotheses, to build more complete models, and to propose new experiments to test the validity of their hypotheses.