Abstract: Provided are methods and kits for determining predisposition of a subject to develop a kidney disease, by identifying in a sample of the subject at least one APOL1 polypeptide variant which is characterized by a higher trypanolytic activity on Trypanosoma brucei rhodesiense as compared to the trypanolytic activity of wild type APOL1 polypeptide as set forth in SEQ ID NO:1 on the Trypanosoma brucei rhodesiense under identical assay conditions; or at least one APOL1 nucleotide mutation in the APLO1 genomic sequence set forth in SEQ ID NO:3, wherein the at least one nucleotide mutation or polypeptide variant being in linkage disequilibrium (LD) with the S342G mutation in the APOL1 polypeptide set forth in SEQ ID NO:1, wherein presence of the APOL1 polypeptide variant indicates increased predisposition of the subject to develop the kidney disease.

Abstract: Provided are methods and kits for determining predisposition of a subject to develop a kidney disease, by identifying in a sample of the subject at least one APOL1 polypeptide variant which is characterized by a higher trypanolytic activity on Trypanosoma brucei rhodesiense as compared to the trypanolytic activity of wild type APOL1 polypeptide as set forth in SEQ ID NO:1 on the Trypanosoma brucei rhodesiense under identical assay conditions; or at least one APOL1 nucleotide mutation in the APLO1 genomic sequence set forth in SEQ ID NO:3, wherein the at least one nucleotide mutation or polypeptide variant being in linkage disequlibrium (LD) with the S342G mutation in the APOL1 polypeptide set forth in SEQ ID NO:1, wherein presence of the APOL1 polypeptide variant indicates increased predisposition of the subject to develop the kidney disease.

Abstract: Provided are methods and kits for determining predisposition of a subject to develop a kidney disease, by identifying in a sample of the subject at least one APOL1 polypeptide variant which is characterized by a higher trypanolytic activity on Trypanosoma brucei rhodesiense as compared to the trypanolytic activity of wild type APOL1 polypeptide as set forth in SEQ ID NO:1 on the Trypanosoma brucei rhodesiense under identical assay conditions; or at least one APOL1 nucleotide mutation in the APLO1 genomic sequence set forth in SEQ ID NO:3, wherein the at least one nucleotide mutation or polypeptide variant being in linkage disequlibrium (LD) with the S342G mutation in the APOL1 polypeptide set forth in SEQ ID NO:1, wherein presence of the APOL1 polypeptide variant indicates increased predisposition of the subject to develop the kidney disease.

Abstract: Provided are methods and kits for determining predisposition of a subject to develop a kidney disease, by identifying in a sample of the subject at least one APOL1 polypeptide variant which is characterized by a higher trypanolytic activity on Trypanosoma brucei rhodesiense as compared to the trypanolytic activity of wild type APOL1 polypeptide as set forth in SEQ ID NO:1 on the Trypanosoma brucei rhodesiense under identical assay conditions; or at least one APOL1 nucleotide mutation in the APLO1 genomic sequence set forth in SEQ ID NO:3, wherein the at least one nucleotide mutation or polypeptide variant being in linkage disequlibrium (LD) with the S342G mutation in the APOL1 polypeptide set forth in SEQ ID NO:1, wherein presence of the APOL1 polypeptide variant indicates increased predisposition of the subject to develop the kidney disease.

Abstract: A “variable group selection” system and method in which constructs are based upon a training data set, a regression modeling module that takes into account information on groups of related predictor variables given as input and outputs a regression model with selected variable groups. Optionally, the method can be employed as a component in methods of temporal causal modeling, which are applied on a time series training data set, and output a model of causal relationships between the multiple times series in the data.

Abstract: A method and computer system for monitoring and controlling the quality of tests performed upon a database. A statistical quality layer is provided, which for each new test to be executed on the database, provides recommendations as to a confidence level to be applied to the test and to a number of additional data records to be added to the database in order to maintain the total expected number of type-I errors of tests performed upon the database. The method and computer system further provide access control of users to the database.

Abstract: Provided are methods and kits for determining predisposition of a subject to develop a kidney disease, by identifying in a sample of the subject at least one APOL1 polypeptide variant which is characterized by a higher trypanolytic activity on Trypanosoma brucei rhodesiense as compared to the trypanolytic activity of wild type APOL1 polypeptide as set forth in SEQ ID NO:1 on the Trypanosoma brucei rhodesiense under identical assay conditions; or at least one APOL1 nucleotide mutation in the APLO1 genomic sequence set forth in SEQ ID NO:3, wherein the at least one nucleotide mutation or polypeptide variant being in linkage disequlibrium (LD) with the S342G mutation in the APOL1 polypeptide set forth in SEQ ID NO:1, wherein presence of the APOL1 polypeptide variant indicates increased predisposition of the subject to develop the kidney disease.

Abstract: A method and computer system for monitoring and controlling the quality of tests performed upon a database. A statistical quality layer is provided, which for each new test to be executed on the database, provides recommendations as to a confidence level to be applied to the test and to a number of additional data records to be added to the database in order to maintain the total expected number of type-I errors of tests performed upon the database. The method and computer system further provide access control of users to the database.

Abstract: A “variable group selection” system and method in which constructs are based upon a training data set, a regression modeling module that takes into account information on groups of related predictor variables given as input and outputs a regression model with selected variable groups. Optionally, the method can be employed as a component in methods of temporal causal modeling, which are applied on a time series training data set, and output a model of causal relationships between the multiple times series in the data.

Abstract: A method and system perform ranking-based evaluations for regression models that are often appropriate for marketing tasks and are more robust to outliers than traditional residual-based performance measures. The output provided by the method and system provides visualization that can offer insights about local model performance and outliers. Several models can be compared to each other to identify the “best” model and, therefore, the “best” model data for the particular marketing task.

Abstract: A method and system perform ranking-based evaluations for regression models that are often appropriate for marketing tasks and are more robust to outliers than traditional residual-based performance measures. The output provided by the method and system provides visualization that can offer insights about local model performance and outliers. Several models can be compared to each other to identify the “best” model and, therefore, the “best” model data for the particular marketing task.

Abstract: A method (and system) of predicting an unobserved target variable includes building a graphical predictive model from domain knowledge, which takes advantage of conditional independence to facilitate inference about the unobserved target variable, given observations of other variables in the graphical predictive model from a plurality of information sources.

Abstract: A method and system perform ranking-based evaluations for regression models that are often appropriate for marketing tasks and are more robust to outliers than traditional residual-based performance measures. The output provided by the method and system provides visualization that can offer insights about local model performance and outliers. Several models can be compared to each other to identify the “best” model and, therefore, the “best” model data for the particular marketing task.