5797results about "Biostatistics" patented technology

“In silico” nucleic acid recombination methods, related integrated systems utilizing genetic operators and libraries made by in silico shuffling methods are provided.

The information management system disclosed enables caregivers to make better decisions, faster, using aggregated genetic and phenotypic data. The system enables the integration, validation and analysis of genetic, phenotypic and clinical data from multiple subjects who may be at distributed facilities. A standardized data model stores a range of patient data in standardized data classes that encompass patient profile information, patient symptomatic information, patient treatment information, and patient diagnostic information including genetic information. Data from other systems is converted into the format of the standardized data classes using a data parser, or cartridge, specifically tailored to the source system. Relationships exist between standardized data classes that are based on expert rules and statistical models. The relationships are used both to validate new data, and to predict phenotypic outcomes based on available data. The prediction may relate to a clinical outcome in response to a proposed intervention by a caregiver. The statistical models may be inhaled into the system from electronic publications that define statistical models and methods for training those models, according to a standardized template. Methods are described for selecting, creating and training the statistical models to operate on genetic, phenotypic and clinical data, in particular for underdetermined data sets that are typical of genetic information. The disclosure also describes how security of the data is maintained by means of a robust security architecture, and robust user authentication such as biometric authentication, combined with application-level and data-level access privileges.

The invention provides a molecular marker set that can be used for prognosis of colorectal cancer in a colorectal cancer patient. The invention also provides methods and computer systems for evaluating prognosis of colorectal cancer in a colorectal cancer patient based on the molecular marker set. The invention also provides methods and computer systems for determining chemotherapy for a colorectal cancer patient and for enrolling patients in clinical trials.

The present disclosure provides methods for determining the ploidy status of a chromosome in a gestating fetus from genotypic data measured from a mixed sample of DNA comprising DNA from both the mother of the fetus and from the fetus, and optionally from genotypic data from the mother and father. The ploidy state is determined by using a joint distribution model to create a plurality of expected allele distributions for different possible fetal ploidy states given the parental genotypic data, and comparing the expected allelic distributions to the pattern of measured allelic distributions measured in the mixed sample, and choosing the ploidy state whose expected allelic distribution pattern most closely matches the observed allelic distribution pattern. The mixed sample of DNA may be preferentially enriched at a plurality of polymorphic loci in a way that minimizes the allelic bias, for example using massively multiplexed targeted PCR.

A new method for genomic analysis, termed “Sequence-Based Karyotyping,” is described. Sequence-Based Karyotyping methods for the detection of genomic abnormalities, for diagnosis of hereditary disease, or for diagnosis of spontaneous genomic mutations are also described.

A method for screening individuals at risk for prostate cancer progression is disclosed. The method is useful for evaluating cells from patients at risk for recurrence of prostate cancer following surgery for prostate cancer. Specifically, the method uses specific Markovian nuclear texture factors, alone or in combination with other biomarkers, to determine whether the cancer will progress or lose organ confinement. In addition, methods of predicting the development of fatal metastatic disease by statistical analysis of selected biomarkers is also disclosed. The invention also contemplates a method that uses a neural network to analyze and interpret cell morphology data. Utilizing Markovian factors and other biomarkers as parameters, the network is first trained with a sets of cell data from known progressors and known non-progressors. The trained network is then used to predict prostate cancer progression in patient samples.

Described herein are methods and systems useful for characterizing clinical outcomes of a subject. Provided herein includes computer-assessed methods, medical information systems, and computer-readable instructions that can aid an end-user in diagnosis, prognosis, and treatment of a clinical outcome.

The invention describes a process for determining a biological state through the discovery and analysis of hidden or non-obvious, discriminatory biological data patterns. The biological data can be from health data, clinical data, or from a biological sample, (e.g., a biological sample from a human, e.g., serum, blood, saliva, plasma, nipple aspirants, synovial fluids, cerebrospinal fluids, sweat, urine, fecal matter, tears, bronchial lavage, swabbings, needle aspirantas, semen, vaginal fluids, pre-ejaculate.), etc. which is analyzed to determine the biological state of the donor. The biological state can be a pathologic diagnosis, toxicity state, efficacy of a drug, prognosis of a disease, etc. Specifically, the invention concerns processes that discover hidden discriminatory biological data patterns (e.g., patterns of protein expression in a serum sample that classify the biological state of an organ) that describe biological states.

The present invention provides methods for analyzing a combination of biomarkers to individualize tyrosine kinase inhibitor therapy in patients who have been diagnosed with cancer. In particular, the assay methods of the present invention are useful for predicting, identifying, or monitoring the response of a tumor, tumor cell, or patient to treatment with a tyrosine kinase inhibitor using an algorithm based upon biomarker profiling. The assay methods of the present invention are also useful for predicting whether a patient has a risk of developing toxicity or resistance to treatment with a tyrosine kinase inhibitor. In addition, the assay methods of the present invention are useful for monitoring tyrosine kinase inhibitor therapy in a patient receiving the drug to evaluate whether the patient will develop resistance to the drug. Furthermore, the assay methods of the present invention are useful for optimizing the dose of a tyrosine kinase inhibitor in a patient receiving the drug to achieve therapeutic efficacy and/or reduce toxic side-effects.

The invention provides methods for simultaneously amplifying multiple nucleic acid regions of interest in one reaction volume as well as methods for selecting a library of primers for use in such amplification methods. The invention also provides library of primers with desirable characteristics, such as minimal formation of amplified primer dimers or other non-target amplicons.

Methods for determining statistical models for predicting disease risks of a population are provided. Two types of data associated with members of the population are collected. The data may include both genetic and non-genetic types of data. A candidate statistical model is selected for calculating the disease risk. The model has a plurality of parameters and is a function of only one of the two types of data. A data weight is determined for each member of the population. Members having like data of the other type have like weights. The parameters of the model are optimized by fitting the collected data to the model taking into account of the weights.

Data mining techniques are provided which are effective and efficient for discovering useful information from an amorphous collection or data set of records. For example, the present invention provides for the mining of data, e.g., of several or many records, to discover interesting associations between entries of qualitative text, and covariances between data of quantitative numerical types, in records. Although not limited thereto, the invention has particular application and advantage when the data is of a type such as clinical, pharmacogenomic, forensic, police and financial records, which are characterized by many varied entries, since the problem is then said to be one of “high dimensionality” which has posed mathematical and technical difficulties for researchers. This is especially true when considering strong negative associations and negative covariance, i.e., between items of data which may so rarely come together that their concurrence is never seen in any record, yet the fact that this is not expected is of potential great interest.

Disclosed herein is a system and method for increasing the fidelity of measured genetic data, for making allele calls, and for determining the state of aneuploidy, in one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available. Genetic material from the target individual is acquired, amplified and the genetic data is measured using known methods. Poorly or incorrectly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related individuals. In accordance with one embodiment of the invention, incomplete genetic data from an embryonic cell are reconstructed at a plurality of loci using the more complete genetic data from a larger sample of diploid cells from one or both parents, with or without haploid genetic data from one or both parents. In another embodiment of the invention, the chromosome copy number can be determined from the measured genetic data of a single or small number of cells, with or without genetic information from one or both parents. In another embodiment of the invention, these determinations are made for the purpose of embryo selection in the context of in-vitro fertilization. In another embodiment of the invention, the genetic data can be reconstructed for the purposes of making phenotypic predictions.

Apparatus and methods for monitoring, analyzing, and/or discriminating molecular species, preferably a biomolecule, within a medium using a multisensor array (MSA) and multivariate processing. Biological compounds such as nucleotides and polynucleotides can be detected and analyzed. A reaction process such as an accumulation cycle of nucleic acids can be monitored, analyzed, and controlled using a multisensor array (MSA) and multivariate processing. Monitoring a biomolecule includes interrogating the medium, and preferably its gas phase, by coupling a sensor responsive to any changes of the medium and or biomolecule and its secondary products when, for example, an amplification reaction is proceeded. It is also a scope of the present invention to use direct detection and monitoring of biomolecular reactions in real-time without radioactive or fluorescent labeling. A preferred application is real-time polymerase chain reaction (PCR) detection.

The invention relates to the use of protein design automation (P DA) to generate computationally prescreened secondary libraries of proteins, and to methods and compositions utilizing the libraries.

The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

The invention relates to a method for treating subterranean formation comprising providing distributed temperature sensors, injecting a treatment fluid and monitoring the temperature across the treatment interval during the injection process.

A method of providing a prognosis of lung cancer is conducted by analyzing the expression-of a group of genes. Gene expression profiles in a variety of medium such as microarrays are included as are kits that contain them.

The present invention relates to methods for the diagnosis, evaluation, and treatment of mood disorders, particularly bipolar disorder. In particular, patient test samples are analyzed for the presence and amount of members of a panel of biallelic markers comprising one or more specific markers for bipolar treatment and one or more non-specific markers for bipolar treatment. A variety of markers are disclosed for assembling a panel of markers for such diagnosis and evaluation. Algorithms for determining proper treatment are disclosed. A diagnostic kit for a panel of said markers is disclosed. In various aspects, the invention provides methods for the early detection and differentiation of mood disorders or bipolar treatment. Methods for screening therapeutic compounds for mood disorders are disclosed. The invention (1) gives methods providing rapid, sensitive and specific assays that can greatly increase the number of patients that can receive beneficial treatment and therapy, thereby reducing the costs associated with incorrect diagnosis, and (2) provides methods for improved therapies.

Methods for estimating genomic copy number and loss of heterozygosity using Hidden Markov Model based estimation are disclosed.