306 results about "Expression pattern" patented technology

This invention relates to an array, including a universal micro-array, for the analysis of nucleic acids, such as DNA. The devices and methods of the invention can be used for identifying gene expression patterns in any organism. More specifically, all possible oligonucleotides (n-mers) necessary for the identification of gene expression patterns are synthesized. According to the invention, n is large enough to give the specificity to uniquely identify the expression pattern of each gene in an organism of interest, and is small enough that the method and device can be easily and efficiently practiced and made. The invention provides a method of analyzing molecules, such as polynucleotides (e.g., DNA), by measuring the signal of an optically-detectable (e.g., fluorescent, ultraviolet, radioactive or color change) reporter associated with the molecules. In a polynucleotide analysis device according to the invention, levels of gene expression are correlated to a signal from an optically-detectable (e.g. fluorescent) reporter associated with a hybridized polynucleotide. The invention includes an algorithm and method to interpret data derived from a micro-array or other device, including techniques to decode or deconvolve potentially ambiguous signals into unambiguous or reliable gene expression data.

Coupling of excitation to neurogenesis in proliferating post-natal NPCs is demonstrated in vitro and in vivo. Neurogenesis is potently enhanced by excitatory stimuli, and involves Cav1.2 / 1.3 channels and NMDA receptors. These Ca2+ influx pathways are located on the proliferating NPCs, allowing them to directly sense and process excitatory stimuli. Excitation increases the fraction of NPC progeny that are neurons, and increases total neuron number. Signaling in this pathway leads to rapid induction of a proneural gene expression pattern involving the bHLH genes HES1, Id2, and NeuroD, and the resulting cells become fully functional neurons defined by neuronal morphology, expression of neuronal structural proteins, expression of neuronal TTX-sensitive voltage gated Na+ channels, and synaptic incorporation into active neural circuits.

The invention relates generally to the field of cancer prognosis and treatment. More particularly, the present invention relates to methods and compositions that utilize a particular panel of gene products (“biomarkers”) and their differential expression patterns (“expression signatures”), wherein the expression patterns correlate with responsiveness, or lack thereof, to chemotherapy treatment. The invention is based on the identification of a specific set of biomarkers that are differentially expressed in chemotherapy-treated tumors and which are useful in predicting the likelihood of a therapeutic response, including residual disease persistence and subsequent tumor recurrence in cancer patients receiving chemotherapy. The gene panel is also useful in designing specific adjuvant modalities with improved therapeutic efficiency. Also disclosed are methods for characterizing tumors according to expression of the biomarkers described herein.

Systems and processes for rule-based natural language processing are provided. In accordance with one example, a method includes, at an electronic device with one or more processors, receiving a natural-language input; determining, based on the natural-language input, an input expression pattern; determining whether the input expression pattern matches a respective expression pattern of each of a plurality of intent definitions; and in accordance with a determination that the input expression pattern matches an expression pattern of an intent definition of the plurality of intent definitions: selecting an intent definition of the plurality of intent definitions having an expression pattern matching the input expression pattern; performing a task associated with the selected intent definition; and outputting an output indicating whether the task was performed.

The present invention is directed to promoters of flax conlinin and ω-3 desaturase genes. The promoters guide high levels of the expression exclusively in flax developing seeds. This specific expression pattern concomitant with the biosynthesis of storage lipids and proteins make these promoters particularly useful for seed-specific modification of fatty acid and protein compositions in plant seeds.

The present invention provides methods and compositions for the construction of custom cDNA microarrays. In particular, the methods involve the selection of relevant clusters based on knowledge and expression patterns using public database information and the identification of the best representative cDNA clones within the selected cluster. The methods facilitate the construction of custom microarrays suitable for use in any biotechnological art. In preferred embodiments, the present invention provides the the ImmunoChip.

The present invention uses peripheral blood monocyte-lymphocyte for the early diagnosis of pancreatic cancer, as well as other conditions of the pancreas and other organs. The peripheral blood lymphocytes recognize the new neoplasm in the pancreas, as well as disease processes in other organ systems. The evaluation of this specific recognition of the disease process by the peripheral blood monocyte-lymphocyte through gene microarray expression patterns constitute a successful method for the early detection of pancreatic cancer and other organ disease processes. This document describes the process used in this method of early diagnosis.

The invention provides methods of analyzing genes for differential relative allelic expression patterns. Haplotype blocks throughout the genomes of individuals are analyzed to identify haplotype patterns that are associated with specific differential relative allelic expression patterns. Haplotype blocks that contain associated haplotype patterns may be further investigated to identify genes or variants of genes involved in differential relative allelic expression patterns.

On the basis of an artificial mental model, the invention researches a behavioral expression mode and a method of a robot from the view of psychology, and provides an intelligent emotional robot multi-modal behavioral associative expression system. The system accepts the unified driving of emotional signal output by the artificial mental model and is provided with a unified behavioral driving mechanism; therefore, the behavioral expressions are more harmonious. The intelligent emotional robot multi-modal behavioral associative expression system comprises three modules, namely a language expression module, a facial expression module and an action expression module; the three modules accept the unified driving of an emotional signal output by the artificial mental model; and to the expression of the language, face and action of the intelligent emotional robe, the expression of language, face and action are executed synchronously on time sequence, and the unified driving of the emotionalsignal is accepted logically, thereby having consistency.

Objective methods for detecting and diagnosing breast cancer (BRC) are described herein. In one embodiment, the diagnostic method involves determining the expression level of a BRC-associated gene that discriminates between BRC cells and normal cells. In another embodiment, the diagnostic method involves determining the expression level of a BRC-associated gene that discriminates among BRC cells, between DCIS and IDC cells. The present invention further provides means for predicting and preventing breast cancer metastasis using BRC-associated genes having unique altered expression patterns in breast cancer cells with lymph-node metastasis. Finally, the present invention provides methods of screening for therapeutic agents useful in the treatment of breast cancer, methods of treating breast cancer and method for vaccinating a subject against breast cancer.

The present study demonstrates that brimonidine tartrate, an alpha-2 adrenergic receptor agonist, can prevent photoreceptor cell degeneration and the associated Muller cell degenerative signs in an in vitro model of retinal degeneration and retinal detachment (separation of the neuroretina from the retinal pigment epithelium). Similar to control conditions, brimonidine allowed for the formation of highly structured photoreceptor outer segments, prevented the expression of stress markers in Müller cells and preserved the expression patterns of Muller cell markers of proper cell-cell contact and differentiation. Ultrastructural studies also indicated that brimonidine favored the formation of cell-cell junctions between photoreceptor cells and Müller cells, indicating that this phenomenon is associated with the exertion of the neuroprotective effect. The results suggest that brimonidine compounds may be utilized as an effective therapeutic agent for early and late onset retinal degenerations caused by defects in photoreceptor cells, Müller cells or both, and as an adjuvant to therapeutic success in retinal detachment surgery or macular translocation surgery for age-related macular degeneration.

The present invention provides a method for preparing a reference model for cancer relapse prediction that provides higher resolution grading than Gleason score alone. The method encompasses obtaining from different individuals a plurality of prostate carcinoma tissue samples of known clinical outcome representing different Gleason scores; selecting a set of signature genes having an expression pattern that correlates positively or negatively in a statistically significant manner with the Gleason scores; independently deriving a prediction score that correlates gene expression of each individual signature gene with Gleason score for each signature gene in said plurality of prostate carcinoma tissue samples; deriving a prostate cancer gene expression (GEX) score that correlates gene expression of said set of signature genes with the Gleason score based on the combination of independently derived prediction scores in the plurality of prostate cancer tissue samples; and correlating said GEX score with the clinical outcome for each prostate carcinoma tissue sample. A set of signature genes is provided that encompasses all or a sub-combination of GI_2094528, KIP2, NRG1, NBL1, Prostein, CCNE2, CDC6, FBP1, HOXC6, MKI67, MYBL2, PTTG1, RAMP, UBE2C, Wnt5A, MEMD, AZGP1, CCK, MLCK, PPAP2B, and PROK1. Also provided a methods for predicting the probability of relapse of cancer in an individual and methods for deriving a prostate cancer gene expression (GEX) score for a prostate carcinoma tissue sample obtained from an individual.

Provided are methods of diagnosis, prognosis, and monitoring of aging using biomarkers that have been discovered to be linked to biological aging process. Methods for increasing neural cell regeneration and cognitive function are also provided. The methods are, at least in part, based on a discovery that altered expression patterns of certain biological markers are associated with biological aging processes. These markers comprise at least Eotaxin / CCL11, β2-microglobulin, MCP-1 and Haptoglobulin, increased expression of which has been shown to be associated with increase in biological aging process.

There is a pressing need for computer-implemented tools that can summarize and present the enormous amounts of public literature to facilitate analysis of gene expression data. The present invention provides techniques and systems for efficiently integrating public literature regarding gene function with data from gene expression profiling experiments. Information from literature databases relating to a particular set of DNA sequences of known expression pattern is retrieved, processed, cross-referenced and viewed to provide further information about a particular DNA sequence to facilitate its identification as a candidate gene.

To gain a better understanding of tumor angiogenesis, new techniques for isolating endothelial cells (ECs) and evaluating gene expression patterns were developed. When transcripts from ECs derived from normal and malignant colorectal tissues were compared with transcripts from non-endothelial cells, over 170 genes predominantly expressed in the endothelium were identified. Comparison between normal- and tumor-derived endothelium revealed 79 differentially expressed genes, including 46 that were specifically elevated in tumor-associated endothelium. Experiments with representative genes from this group demonstrated that most were similarly expressed in the endothelium of primary lung, breast, brain, and pancreatic cancers as well as in metastatic lesions of the liver. These results demonstrate that neoplastic and normal endothelium in humans are distinct at the molecular level, and have significant implications for the development of anti-angiogenic therapies in the future.

The statistical analysis described and claimed is a predictive statistical tree model that overcomes several problems observed in prior statistical models and regression analyses, while ensuring greater accuracy and predictive capabilities. Although the claimed use of the predictive statistical tree model described herein is directed to the prediction of a disease in individuals, the claimed model can be used for a variety of applications including the prediction of disease states, susceptibility of disease states or any other biological state of interest, as well as other applicable non-biological states of interest. This model first screens genes to reduce noise, applies k-means correlation-based clustering targeting a large number of clusters, and then uses singular value decompositions (SVD) to extract the single dominant factor (principal component) from each cluster. This generates a statistically significant number of cluster-derived singular factors, that we refer to as metagenes, that characterize multiple patterns of expression of the genes across samples. The strategy aims to extract multiple such patterns while reducing dimension and smoothing out gene-specific noise through the aggregation within clusters. Formal predictive analysis then uses these metagenes in a Bayesian classification tree analysis. This generates multiple recursive partitions of the sample into subgroups (the “leaves” of the classification tree), and associates Bayesian predictive probabilities of outcomes with each subgroup. Overall predictions for an individual sample are then generated by averaging predictions, with appropriate weights, across many such tree models. The model includes the use of iterative out-of-sample, cross-validation predictions leaving each sample out of the data set one at a time, refitting the model from the remaining samples and using it to predict the hold-out case. This rigorously tests the predictive value of a model and mirrors the real-world prognostic context where prediction of new cases as they arise is the major goal.

Methods of injury assessment in an individual include the steps of determining a pattern of expression exhibited by blood cells obtained from an individual and comparing the pattern of expression exhibited by the obtained blood cells to an injury database to assess the injury.