Abstract: One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.

Abstract: One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.

Abstract: One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.

Abstract: One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.

Abstract: One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.

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: Source data is analyzed and visualized for a user. As the user adjusts graphical query devices, the displayed data is filtered and the visualization is updated accordingly. The invention is particularly useful where the data relates to chemical compounds in that a SAR table is preferably generated, presented in the visualization, and updated according to the query device settings. The displayed SAR table entries may also be clustered as a function of similarity with respect to a chosen property, such as molecular weight or some topological characteristic. A hierarchy of similarity may then be indicated in the SAR table using, for example, a dendrogram.

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.