SELVENTA, INC. Patent applications |
Patent application number | Title | Published |
20140288910 | System, method and apparatus for causal implication analysis in biological networks - Described are methods, systems and apparatus for hypothesizing a biological relationship in a biological system. A database of biological assertions is provided consisting of biological elements, relationships among the biological elements, and relationship descriptors characterizing the properties of the elements and relationships. A biological element may be selected from the database and a logical simulation may be performed within the biological database, from the selected biological element, through relationship descriptors, along a path defined by potentially causative biological elements to discern a biological element hypothetically responsible for the change in the selected biological element. The logical simulation may be either a backward logical simulation, performed upstream through the relationship descriptors to discern a hypothetical responsible biological element, or a forward logical simulation, performed downstream through the relationship descriptors to discern the extent to which the perturbation generates the observed change in the selected biological element. | 09-25-2014 |
20130218581 | Stratifying patient populations through characterization of disease-driving signaling - A method of stratifying a set of disease-exhibiting patients prior to clinical trial of a target therapy begins by using a molecular footprint derived from a knowledgebase and other patient data to identify genes that are differentially expressed in a direction consistent with increase in the target activity. Therapeutic target “signaling strength” in individual patients of the set is then assessed using the genes identified and a strength algorithm. Based on their therapeutic target signaling strength, the set of disease-exhibiting patients are then stratified along a continuum. One or more gene expressions or other biomarkers may be specified for use in categorizing other disease-exhibiting patient populations. Alternative therapeutic targets are analyzed with respect to the likely non-responders, as evidenced by their differential signaling strength. | 08-22-2013 |
20130046726 | Determining whether a measurement signature is specific to a biological process - A “Specificity” statistic (or metric) is computed as a means to identify amplitude scores associated with a signature that can be attributed with high probability to a specific biological entity or process represented by the signature. Preferably, Specificity is computed by assessing a likelihood of a given null hypothesis, namely, that an amplitude score is not representative of the specific signature but, instead, is representative of a general trend in the applicable data set that can be measured by any signature that is comparable to the signature of interest. In a typical implementation, a first step to compute the Specificity metric is to construct a set of comparable signatures. Next, an amplitude score is computed for each of these signatures, preferably using the same data set. Then, the Specificity metric is computed, preferably as a two-tailed p-value, by placing the amplitude score for the signature of interest on a distribution of scores for the comparable signatures. Scores that have Specificity p-values less than a particular value, e.g., 0.05, are considered to be scores that can be attributed with high confidence to the signature of interest. | 02-21-2013 |
20120221506 | Method for quantifying amplitude of a response of a biological network - 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. | 08-30-2012 |
20120030162 | Method for quantifying amplitude of a response of a biological network - 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. | 02-02-2012 |