Abstract: Identifying pathways that are significantly impacted in a given condition is a crucial step in the understanding of the underlying biological phenomena. All approaches currently available for this purpose calculate a p-value that aims to quantify the significance of the involvement of each pathway in the given phenotype. These p-values were previously thought to be independent. Here, we show that this is not the case, and that pathways can affect each other's p-values through a “crosstalk” phenomenon that affects all major categories of existing methods. We describe a novel technique able to detect, quantify, and correct crosstalk effects, as well as identify novel independent functional modules. We assessed this technique on data from four real experiments coming from three phenotypes involving two species.

Abstract: The present disclosure provides a method for identifying targeted treatments for treatment of a phenotype in a human or non-human subject. The method may include providing data relating to a plurality of affected biomolecules to one or more processors; the one or more processors, using a first probability, to identifying one or more biological pathways impacted be the affected biomolecules; the one or more processors identifying one or more biological processes affected by the phenotype; the one or more processors, identifying one or more upstream regulators; and the one or more processors, using a second probability, determining at least one targeted treatment configured to reverse expressions of at least two of the affected biomolecules on the one or more biological pathways impacted by the phenotype.

Abstract: A fetal scalp monitor is disclosed that enables a medical professional to monitor the well-being of a fetus in utero. The fetal scalp monitor has a main body, with a central core having a temperature sensor, conductive dome, grounding ring, and tocodynamometer. The main body also has at least one adhesive portion to facilitate the attachment of the device onto the scalp of a fetus, and a plurality of concentric rings to militate against amniotic fluids from entering the adhesive portion. The vital signs of the infant and conditions inside the uterus are then transmitted, either wired or wirelessly, to a fetus monitoring device.

Abstract: Disease subtyping is accomplished by a computer-implemented algorithm that manipulates a first genetic dataset to construct a set of first connectivity matrices. To this set of matrices Gaussian noise is introduced to generate a perturbed dataset. The computer-implemented algorithm assesses which of the set of first connectivity matrices was least affected by introduction of noise and that matric is used to define the optimal clustering. Once the optimal clustering is determined, computer-implemented supervised classification is performed to determine, for a particular patient, with which disease subtype cluster that person's genetic data most closely aligns. Armed with this knowledge, the treatment regimen is specified with much higher likelihood of success.

Abstract: Disease subtyping is accomplished by a computer-implemented algorithm that manipulates a first genetic dataset to construct a set of first connectivity matrices. To this set of matrices Gaussian noise is introduced to generate a perturbed dataset. The computer-implemented algorithm assesses which of the set of first connectivity matrices was least affected by introduction of noise and that matric is used to define the optimal clustering. Once the optimal clustering is determined, computer-implemented supervised classification is performed to determine, for a particular patient, with which disease subtype cluster that person's genetic data most closely aligns. Armed with this knowledge, the treatment regimen is specified with much higher likelihood of success.

Abstract: Identifying pathways that are significantly impacted in a given condition is a crucial step in the understanding of the underlying biological phenomena. All approaches currently available for this purpose calculate a p-value that aims to quantify the significance of the involvement of each pathway in the given phenotype. These p-values were previously thought to be independent. Here, we show that this is not the case, and that pathways can affect each other's p-values through a “crosstalk” phenomenon that affects all major categories of existing methods. We describe a novel technique able to detect, quantify, and correct crosstalk effects, as well as identify novel independent functional modules. We assessed this technique on data from four real experiments coming from three phenotypes involving two species.

Abstract: Identifying pathways that are significantly impacted in a given condition is a crucial step in the understanding of the underlying biological phenomena. All approaches currently available for this purpose calculate a p-value that aims to quantify the significance of the involvement of each pathway in the given phenotype. These p-values were previously thought to be independent. Here, we show that this is not the case, and that pathways can affect each other's p-values through a “crosstalk” phenomenon that affects all major categories of existing methods. We describe a novel technique able to detect, quantify, and correct crosstalk effects, as well as identify novel independent functional modules. We assessed this technique on data from four real experiments coming from three phenotypes involving two species.

Abstract: Systems, methods, devices, and kits are described that can be used to distinguish cystic fibrosis patients from healthy individuals and from lung cancer patients. The systems, methods, devices, and kits utilize one or more serum biomarkers.

Abstract: A biosensor for use in detecting the presence of diseases, the biosensor comprising a detector for detecting a presence of at least one marker indicative of a specific disease. A method of determining efficacy of a pharmaceutical for treating a disease or staging disease by administering a pharmaceutical to a sample containing markers for a disease, detecting the amount of at least one marker of the disease in the sample, and analyzing the amount of the marker in the sample, whereby the amount of marker correlates to pharmaceutical efficacy or disease stage. Markers for gynecological disease. An immune-imaging agent comprising labeled antibodies, whereby the labeled antibodies are isolated and reactive to proteins overexpressed in vivo. Informatics software for analyzing the arrays, the software including analyzing means for analyzing the arrays.

Abstract: Methods and devices for integrating a plurality of data types are provided. The methods include obtaining, via a processor, a plurality of datasets of a given type including measurements of one or more quantitative variables related to a phenotype comparison, and a plurality of datasets of a different type including measurements of one or more quantitative variables related to the same phenotype comparison; calculating, via the processor, effect sizes of the variables of the first type, effect sizes of the variables of the second type, and global p-values for the first and second data types; and combining, via the processor, the effect sizes and/or the global p-values to identify the variables of either type that are relevant in the given phenotype comparison.

Abstract: Identifying pathways that are significantly impacted in a given condition is a crucial step in the understanding of the underlying biological phenomena. All approaches currently available for this purpose calculate a p-value that aims to quantify the significance of the involvement of each pathway in the given phenotype. These p-values were previously thought to be independent. Here, we show that this is not the case, and that pathways can affect each other's p-values through a “crosstalk” phenomenon that affects all major categories of existing methods. We describe a novel technique able to detect, quantify, and correct crosstalk effects, as well as identify novel independent functional modules. We assessed this technique on data from four real experiments coming from three phenotypes involving two species.

Abstract: A fetal scalp monitor is disclosed that enables a medical professional to monitor the well-being of a fetus in utero. The fetal scalp monitor has a main body, with a central core having a temperature sensor, conductive dome, grounding ring, and tocodynamometer. The main body also has at least one adhesive portion to facilitate the attachment of the device onto the scalp of a fetus, and a plurality of concentric rings to militate against amniotic fluids from entering the adhesive portion. The vital signs of the infant and conditions inside the uterus are then transmitted, either wired or wirelessly, to a fetus monitoring device.

Abstract: A diagnostic device for and method of detecting the presence of head and neck squamous cell carcinoma (HNSCC) in a patient including a detector device for detecting a presence of at least one marker indicative of HNSCC, the detector device including a panel of markers for HNSCC. A diagnostic device for and method of staging HNSCC in a patient including a detector device for detecting a presence of at least one marker indicative of stages of HNSCC, the detector device including a panel of markers for HNSCC. Markers for head and neck squamous cell carcinoma selected from the markers listed in Table 5. Methods of personalized immunotherapy, making a personalized anti-cancer vaccine, and predicting a clinical outcome in a HNSCC patient. A method of making a panel of HNSCC markers.

Abstract: Disease subtyping is accomplished by a computer-implemented algorithm that manipulates a first genetic dataset to construct a set of first connectivity matrices. To this set of matrices Gaussian noise is introduced to generate a perturbed dataset. The computer-implemented algorithm assesses which of the set of first connectivity matrices was least affected by introduction of noise and that matric is used to define the optimal clustering. Once the optimal clustering is determined, computer-implemented supervised classification is performed to determine, for a particular patient, with which disease subtype cluster that person's genetic data most closely aligns. Armed with this knowledge, the treatment regimen is specified with much higher likelihood of success.

Abstract: A biosensor for use in detecting the presence of diseases, the biosensor comprising a detector for detecting a presence of at least one marker indicative of a specific disease. A method of determining efficacy of a pharmaceutical for treating a disease or staging disease by administering a pharmaceutical to a sample containing markers for a disease, detecting the amount of at least one marker of the disease in the sample, and analyzing the amount of the marker in the sample, whereby the amount of marker correlates to pharmaceutical efficacy or disease stage. Markers for gynecological disease. An immuno-imaging agent comprising labeled antibodies, whereby the labeled antibodies are isolated and reactive to proteins overexpressed in vivo. Informatics software for analyzing the arrays, the software including analyzing means for analyzing the arrays.

Abstract: A biosensor for use in detecting the presence of diseases, the biosensor comprising a detector for detecting a presence of at least one marker indicative of a specific disease. A method of determining efficacy of a pharmaceutical for treating a disease or staging disease by administering a pharmaceutical to a sample containing markers for a disease, detecting the amount of at least one marker of the disease in the sample, and analyzing the amount of the marker in the sample, whereby the amount of marker correlates to pharmaceutical efficacy or disease stage. Markers for gynecological disease. An immuno-imaging agent comprising labeled antibodies, whereby the labeled antibodies are isolated and reactive to proteins overexpressed in vivo. Informatics software for analyzing the arrays, the software including analyzing means for analyzing the arrays.

Abstract: Identifying pathways that are significantly impacted in a given condition is a crucial step in the understanding of the underlying biological phenomena. All approaches currently available for this purpose calculate a p-value that aims to quantify the significance of the involvement of each pathway in the given phenotype. These p-values were previously thought to be independent. Here, we show that this is not the case, and that pathways can affect each other's p-values through a “crosstalk” phenomenon that affects all major categories of existing methods. We describe a novel technique able to detect, quantify, and correct crosstalk effects, as well as identify novel independent functional modules. We assessed this technique on data from four real experiments coming from three phenotypes involving two species.

Abstract: Identifying pathways that are significantly impacted in a given condition is a crucial step in the understanding of the underlying biological phenomena. All approaches currently available for this purpose calculate a p-value that aims to quantify the significance of the involvement of each pathway in the given phenotype. These p-values were previously thought to be independent. Here, we show that this is not the case, and that pathways can affect each other's p-values through a “crosstalk” phenomenon that affects all major categories of existing methods. We describe a novel technique able to detect, quantify, and correct crosstalk effects, as well as identify novel independent functional modules. We assessed this technique on data from four real experiments coming from three phenotypes involving two species.

Abstract: A biosensor for use in detecting the presence of diseases, the biosensor comprising a detector for detecting a presence of at least one marker indicative of a specific disease. A method of determining efficacy of a pharmaceutical for treating a disease or staging disease by administering a pharmaceutical to a sample containing markers for a disease, detecting the amount of at least one marker of the disease in the sample, and analyzing the amount of the marker in the sample, whereby the amount of marker correlates to pharmaceutical efficacy or disease stage. Markers for gynecological disease selected from the list in Table 6. An immuno-imaging agent comprising labeled antibodies, whereby the labeled antibodies are isolated and reactive to proteins overexpressed in vivo. Informatics software for analyzing the arrays of claim 4, the software including analyzing means for analyzing the arrays.

Abstract: A biosensor for use in detecting the presence of diseases, the biosensor comprising a detector for detecting a presence of at least one marker indicative of a specific disease. A method of determining efficacy of a pharmaceutical for treating a disease or staging disease by administering a pharmaceutical to a sample containing markers for a disease, detecting the amount of at least one marker of the disease in the sample, and analyzing the amount of the marker in the sample, whereby the amount of marker correlates to pharmaceutical efficacy or disease stage. Markers for gynecological disease. An immune-imaging agent comprising labeled antibodies, whereby the labeled antibodies are isolated and reactive to proteins overexpressed in vivo. Informatics software for analyzing the arrays, the software including analyzing means for analyzing the arrays.