Abstract: The invention relates to computational methods, systems and apparatus useful in the analysis of sets of biomolecules in an accessible body fluid or tissue sample from a patient, which biomolecules collectively or individually are candidates to serve as biomarkers, i.e., biomolecules which together or individually upon detection or change are indicative that the patient is in some biological state, such as a diseased state. The methods permit one to examine such potential biological markers to determine whether each one is indeed present as a consequence of the biological state, or as an artifact of the biomarker search protocol.

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: The present invention relates to computational methods, systems and apparatus useful in the identification of similarities and/or differences between a plurality of biological states, such as altered biological states in an animal (e.g., a mammal or human). Particularly, the invention relates to comparing two or more causal system models (“CSMs”) which each are indicative of a biological state, such as a disease state, a toxic state, or a drug- or therapy-induced state. The present invention also relates to generating a general CSM from a comparison of two or more other CSMs, and subsequently comparing one or more of the other CSMs to the general CSM. Either of these techniques, or a combination of the two techniques, can be used to identify unique and common features in each CSM.

Abstract: The invention relates to computational methods, systems and apparatus useful in the analysis of sets of biomolecules in an accessible body fluid or tissue sample from a patient, which biomolecules collectively or individually are candidates to serve as biomarkers, i.e., biomolecules which together or individually upon detection or change are indicative that the patient is in some biological state, such as a diseased state. The methods permit one to examine such potential biological markers to determine whether each one is indeed present as a consequence of the biological state, or as an artifact of the biomarker search protocol.

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.