Abstract: A system is provided for analyzing metabolomics data received from an analytical device across a group of samples. The system automatically receives a data matrix corresponding to each of the samples, wherein the data matrix includes rows corresponding to each of the samples and columns corresponding to a group of ions present in the respective samples. A processor is provided for determining a characteristic value corresponding to at least one of a group of components present in the samples, wherein the components are made up of at least a portion of the group of ions, using at least one of a correlation function and a factorization function. A user interface is in communication with the processor for displaying a visual indication of the characteristic value such that a user may receive a visual indication of the types of components present in the samples.

Abstract: A cell-based binning method (“Data Driven” binning method) allows the inclusion of all molecules, generates a high percentage of occupied cells, and provides adequate division of the molecules in the low-dimensional subspaces (typically all one-dimension (1-D), two-dimension (2-D), and three-dimension (3-D) subspaces). A chemical space coverage criterion (“Uniform Cell Coverage (UCC)” criterion) measures the uniformity of coverage of the molecules selected. A fast exchange design algorithm (“fast exchange UCC” algorithm) that minimizes the number of searches of the candidate points while maximizing the number of exchanges during each pass through the candidate points. This method is many times faster than previous exchange algorithms and generates designs with good coverage properties.

Abstract: A method of drug discovery in finding compounds with some desired activity for a chosen biological target that reduces reliance on searches of relatively large numbers of compounds. Rules are derived from a relatively small screening data set linking structural features to biological activity, which rules can be used to guide the selection of additional compounds for screening so that screening costs can be reduced as the total number of compounds screened is reduced. Properties of compounds are described numerically and said compounds are placed into small mathematical bins that comprise narrow ranges of the numerical descriptors. Through statistical analysis, it is then determined which combinations of bins describe regions of chemical space that are most likely to contain active compounds. Untested compounds that fall into these regions are then seen as good candidates for screening.

Abstract: Statistical classification of activities of molecules is a computer implemented methodology of QSAR employing visualization of molecular features and statistical techniques for correlating features of molecules with their observed biological properties. Each molecule is described by noting the presence (1) or absence (0) of a feature of interest. The identification of specific features coded by 1's or 0's is accomplished by recursive partitioning. The data sets are planned or unplanned. The method is also applicable to classification of individuals in biological populations on the basis of their genetic makeup.

Abstract: Thread-based methods and systems for using the idle processing power of one or more networked computers include at least one server and at least one client. The server stores data and job descriptions relating to a complex scientific problem and provides the job descriptions and portions of the data to clients in response to requests from the clients. Each of the clients starts a first idle thread for pulling job descriptions from the server. Each client also starts a second idle thread for requesting data from the server and for performing the job specified in the job description. The first and second idle threads are automatically scheduled for execution by the operating system.

Abstract: Conditional associations among features in samples are identified by defining a matrix having rows that represent the samples and columns that represent the features. Each row-column position of the matrix has a first binary value if the sample that is associated with the row exhibits the feature that is associated with the column, and a second binary value if a sample that is associated with the row does not exhibit the feature that is associated with the column. Recursive partitioning then is performed for each column. In particular, for each column, the column is recursively partitioned relative to the remaining ones of the columns, to define a tree of conditional branches for the rows for each column. The collection of trees of conditional branches for the columns may be displayed and/or analyzed to identify conditional associations of interest. Continuous features, wherein each row-column position of the matrix has a value selected from a continuous range of values, also may be analyzed.

Abstract: Statistical classification of activities of molecules is a computer implemented methodology of QSAR employing visualization of molecular features and statistical techniques for correlating features of molecules with their observed biological properties. Each molecule is described by noting the presence (1) or absence (0) of a feature of interest. The identification of specific features coded by 1's or 0's is accomplished by recursive partitioning. The data sets are planned or unplanned. The method is also applicable to classification of individuals in biological populations on the basis of their genetic makeup.