Koninklijke Philips Corporation N.v.

Innosign B.v.

Pace Micro Technology Plc

Philips Intellectual Property & Standards Gmbh

Wilhelmus Franciscus Johannes Verhaegh

Anja Van De Stolpe

Hendrik Jan Van Ooijen

Srinivas Gutta

Pieter Jan Van Der Zaag

Serverius Petrus Paulus Pronk

Marcia Alves De Inda

Petrus Gerardus Meuleman

Rick Velter

Meng Dou

Mauro Barbieri

Maarten Peter Bodlaender

Jochen Keupp

Steffen Clarence Pauws

Ralf Hoffmann

Rene Van Den Ham

Anne Godefrida Catharina Van Brussel

Paul Arnold Van De Wiel

Janneke Wrobel

Robert Van Gog

Nevenka Dimitrova

Ralf Dieter Hoffmann

Steven Paulus Lambertus Kuijpers

Hussam Nachabe

Arnout Michiel De Mooij

Martijn Theodorus Lambert Akse

Marcus Petrus Hendrica Vossen

Herman Sontrop

Kalyana Chakravarthi Dulla

Rene Boettcher

Peter Beyerlein

Ronny Amberg

Jan Hendrik Van Ooijen

Anja Vande Stolpe

Márcia Alves De Inda

Laurentius Henricus Franciscus Maria Holtzer

Yee Him Cheung

A method for determining functional status of at least one immune cell type in at least one sample of a subject comprises determining the functional status of the at least one immune cell type based on activity of at least one signaling pathway in the at least one immune cell type in the at least one sample of the subject; and optionally providing the functional status of the at least one immune cell type in the at least one sample of the subject.

Determining functional status of immune cells types and immune response

The present invention relates to an apparatus () for diagnostic image acquisition, comprising: an input unit (); a processing unit (); and an output unit (). The input unit is configured to receive a data value relating to at least one biomarker in a measurement blood sample of a patient. The processing unit is configured to determine a time to acquire a diagnostic image of the patient, wherein the determination comprises utilization of the data value. The output unit is configured to output an indication of the time to acquire the diagnostic image of the patient.

Apparatus for diagnostic image acquisition determination

A bioinformatics process which provides an improved means to detect a JAK-STAT3 cellular signaling pathway in a subject, such as a human, based on the expression levels of at least three unique target genes of the JAK-STAT3 cellular signaling pathway measured in a sample. The invention includes an apparatus comprising a digital processor configured to perform such a method, a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such a method, and a computer program comprising program code means for causing a digital processing device to perform such a method. Kits are also provided for measuring expression levels of unique sets of JAK-STAT3 cellular signaling pathway target genes.

Determination of JAK-STAT3 pathway activity using unique combination of target genes

The invention relates to a computer-implemented Bayesian inference method for performing Bayesian inference in a Bayesian network, which includes a continuous child node () and its discrete parent node () having two states. Being provided with a calibrated continuous probability distribution of the observations of the child node () for each of the two states of the parent node (), the inferring for a new observation of the child node () for which the state of the parent node () is not known of the probability of at least a first state of the parent node () makes use of masses of portions of the probability distributions that depend on a locational relationship of the probability distributions and the value of the new observation. This may ensure that the inferred probability of the first state of the parent node () monotonically changes with monotonically changing values of the new observation.

Bayesian inference

The present application mainly relates to a method for determining a prognosis for a subject diagnosed with high-grade serous ovarian cancer. The method comprises determining the prognosis based on activities of at least two cellular signaling pathways including a phosphatidylinositide 3-kinase (PI3K) pathway and a nuclear factor-kappa B (NFkB or NF&#x3ba;B) pathway in a sample of the subject. The present application also relates to a method for identifying a subject diagnosed with high-grade serous ovarian cancer that will be suitable for a PI3K pathway targeting therapy or an NFkB pathway targeting therapy. The method comprises identifying the subject based on activities of at least two cellular signaling pathways including a PI3K pathway and an NFkB pathway in a sample of the subject. The present application further relates to corresponding apparatuses, non-transitory storage media, computer programs and kits.

Methods of prognosis in high-grade serous ovarian cancer

A bioinformatics process which provides an improved means to detect a JAK-STAT1/2 cellular signaling pathway in a subject, such as a human, based on the expression levels of at least three unique target genes of the JAK-STAT1/2 cellular signaling pathway measured in a sample. The invention includes an apparatus comprising a digital processor configured to perform such a method, a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such a method, and a computer program comprising program code means for causing a digital processing device to perform such a method. Kits are also provided for measuring expression levels of unique sets of JAK-STAT1/2 cellular signaling pathway target genes.

Determination of JAK-STAT1/2 pathway activity using unique combination of target genes

A bioinformatics method for determining a risk score that indicates a risk that a subject will experience a negative clinical event within a certain period of time. The risk score is based on a combination of activities of two or more cellular signaling pathways in a subject, such as a human, wherein the specific cellular signaling pathways are the PI3K pathway and one or more of a Wnt pathway, an ER pathway, and an HH pathway. The invention also includes an apparatus with a digital processor configured to perform such a method, to a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such a method, and to a computer program comprising program code means for causing a digital processing device to perform such a method. The invention achieves advanced prognosis of negative clinical events, for example, disease progression, recurrence, development of metastasis, or even death.

Bioinformatics process for identifying at risk subject populations

The present application mainly relates to specific methods for inferring activity of one or more cellular signaling pathway(s) in tissue of a medical subject based at least on the expression level(s) of one or more target gene(s) of the cellular signaling pathway(s) measured in an extracted sample of the tissue of the medical subject, an apparatus comprising a digital compressor configured to perform such methods and a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such methods.

Assessment of cellular signaling pathway activity using probabilistic modeling of target gene expression

The present application mainly relates to specific methods for inferring activity of a cellular signaling pathway in tissue and/or cells of a medical subject based at least on expression levels of one or more target gene(s) of the cellular signaling pathway measured in an extracted sample of the tissue and/or cells of the medical subject, an apparatus comprising a digital compressor configured to perform such methods and a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such methods.

Assessment of cellular signaling pathway activity using linear combination(s) of target gene expressions

A method for determining a risk score that indicates a risk that a clinical event will occur within a certain period of time. The risk score is based at least in part on a combination of inferred activities of two or more cellular signaling pathways in a tissue and/or cells and/or a body fluid of a subject. The cellular signaling pathways comprise a Wnt pathway, an ER pathway, an HH pathway, and/or an AR pathway. The risk score is defined such that the indicated risk that the clinical event will occur within the certain period of time decreases with an increasing PER and increases with an increasing max(PWnt, PHH), wherein PER, PWnt, and PHH denote the inferred activity of the ER pathway, the Wnt pathway, and the HH pathway, respectively.

Medical prognosis and prediction of treatment response using multiple cellular signalling pathway activities

The present invention relates to a method comprising inferring activity of a PI3K cellular signaling pathway in a tissue and/or cells and/or a body fluid of a medical subject based at least on expression levels of one or more target gene(s) of the PI3K cellular signaling pathway measured in an extracted sample of the tissue and/or the cells and/or the body fluid of the medical subject. The present invention further relates to an apparatus comprising a digital processor configured to perform such a method, a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such a method, and a computer program comprising program code means for causing a digital processing device to perform such a method.

Assessment of the PI3K cellular signaling pathway activity using mathematical modelling of target gene expression

A sequencer device generates basic nucleotide sequence datacomprising probe dataof a capture probe in the sequencer deviceand a determined sequence of identifiersof a fragment of nucleic acids captured by the probe. The sequencer device outputs enriched nucleotide sequence datathat is enriched with data comprising a reference to a sequencethat is expected for the fragment of nucleic acids.

Providing nucleotide sequence data

A method for generating a recommendation is provided. The method includes the steps of: receiving at least one of a negative and positive example from one or more other users; and determining a recommendation for a user based on at least one of the negative and positive examples. The method can further include the step of generating a user profile for the user based on previous behavior of the user, in which case the determining step can include determining the recommendation based on the negative example and the user profile. The determining step can also include the step of determining the recommendation based on both of the negative and positive examples.

Collaborative sampling for implicit recommenders

The invention relates to a data processing device () enabling a user to input characters, the device comprising a touch-sensitive member () arranged to function as a virtual keyboard, said member including at least one touch sensor () for detecting touched zones on said member. The device further comprises key allocation means () for allocating at least two reference keys () of the virtual keyboard in response to said detection of the touched zones. The device comprises at least one pressure sensor () for sensing a finger () causing a force on the touch-sensitive member higher than other fingers when more than one finger touches said member. A recognition of a key stroke may be realized. The reference keys may be reallocated upon a user's request or detection of a predetermined condition. The invention also relates to a method of enabling a user to input characters.

Automatically adaptable virtual keyboard

A classification system () for classification of bio molecular data is provided. An input of the system receives a plurality of features () of a sample to be classified and a plurality of respective error estimates (). A statistical module () associates probability density functions () with the features, wherein variances of the probability density functions depend on the error estimates. A replication module () produces a plurality of perturbed replicas () of the sample, wherein the features are randomly perturbed according to the corresponding respective probability density functions. A classifier () classifies the perturbed replicas based on the perturbed features. An analyzer () classifies the sample to be classified based on a statistical analysis of the classified replicas () to obtain a sample classification ().

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Eindhoven, Netherlands

Wilhelmus Franciscus Johannes Verhaegh