Abstract: Disclosed systems and methods can determine predicted rental income, estimated error of the prediction, and a set of comparable rental real estate properties for use in the valuation of a subject real estate property rental value. In one embodiment, the rent prediction system receives rental information about real-estate properties, determines feature characteristics, trains a rent amount prediction model using the feature characteristics, determines a second set of feature characteristics based on the output of the rent amount prediction model, and trains an error prediction model using the determined second set of feature characteristics. Using the trained models, the systems and method may predict a rental value and prediction error for one or more subject properties.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: Embodiments include systems and methods of detecting and assessing multiple types of risks related to mortgage lending. One embodiment includes a system and method of detecting and assessing risks including fraud risks, early payment default risks, and risks related to fraudulently stated income on loan applications. One embodiment includes a computerized method that includes creating a combined risk detection model based on a plurality of risk detection models and using the combined risk detection model to evaluate loan application data and generate a combined risk score that takes into account interaction of different types of risks individually and collectively detected by the plurality of risk detection models.

Abstract: The present invention provides compounds, compositions, and methods for identification of motifs within regulatory regions of genes involved in adipogenesis and adipocyte differentiation. Compounds and compositions are provided for modulating expression of nuclear receptor/transcription factor-regulated genes. Methods for modulating the function of PPAR-? as well as PPAR-?-regulated gene promoters, and methods of using oligomeric compounds for diagnosis and treatment of diseases such as obesity and diabetes are also provided.

Abstract: The present invention provides, inter alia, methods of selecting a single-stranded oligomeric compounds for inhibiting RNA expression, methods of generating double-stranded oligomeric compounds, methods of identifying optimized double-stranded oligomeric compounds, methods of selecting optimized single-stranded oligomeric compounds, methods of selecting optimized double-stranded oligomeric compounds, methods of identifying multifunctional oligomeric compounds, methods for optimizing target region selection for modulation of RNA expression, methods of optimizing expression modulation of RNA, and the like. The present invention further provides oligomeric compounds, 8-80 nucleobases in length targeted to a target RNA, wherein said oligomeric compound hybridizes to said target RNA and inhibits RNA levels by at least 50% in both single-stranded and double-stranded forms, and multifunctional oligomeric compounds.

Abstract: The present invention provides, inter alia, methods of selecting a single-stranded oligomeric compounds for inhibiting RNA expression, methods of generating double-stranded oligomeric compounds, methods of identifying optimized double-stranded oligomeric compounds, methods of selecting optimized single-stranded oligomeric compounds, methods of selecting optimized double-stranded oligomeric compounds, methods of identifying multifunctional oligomeric compounds, methods for optimizing target region selection for modulation of RNA expression, methods of optimizing expression modulation of RNA, and the like. The present invention further provides oligomeric compounds, 8-80 nucleobases in length targeted to a target RNA, wherein said oligomeric compound hybridizes to said target RNA and inhibits RNA levels by at least 50% in both single-stranded and double-stranded forms, and multifunctional oligomeric compounds.