Abstract: Stimulus-response patterns are analyzed using deduction protocols applied through AI systems such as expert systems and neural networks. Generating an output signal matrix database involves: (i) constructing a stimulated physical matrix; (ii) detecting a physical signal at each unit of the physical matrix; (iii) transducing each physical signal to generate an electrical output signal; (iv) storing each output signal in an output signal matrix data structure; and (v) repeating steps (i)-(iv) to iteratively store output signal matrix data structures for a plurality of stimuli to form an output signal matrix database. Individual output signal matrices are compared to such output signal matrix databases according for qualitative analysis. The stimulated physical matrices comprise an ordered array of units, each confining (1) either a different responder of a living thing or a probe corresponding to such a different responder and, (2) an identifier for the responder or probe.

Abstract: The present invention relates to methods of identifying genes whose expression is indicative of activation of a particular biochemical or metabolic pathway or a common set of biological reactions or functions in a cell (“regulon indicator genes”) The present invention provides an example of such an indicator gene. The present invention also relates to methods of partially characterizing a gene of unknown function by determining which biological pathways, reactions or functions its expression is associated with, thereby placing the gene within a functional genetic group or “regulon”. These partially characterized genes may be used to identify desirable therapeutic targets of biological pathways of interest (“regulon target genes”) The present invention provides examples of such target genes. Methods for identifying effectors (activators and inhibitors) of regulon target genes are provided. The present invention also provides examples of regulon target gene inhibitors.

Abstract: The present invention provides methods of screening for a molecule that inhibits the expression or activity of a protein encoded by a target gene which affects the fitness of a cell. The methods are based on a co-culture assay, and entail culturing together two cell populations, each of which is a population of identical cells, of the same species that differs substantially only in the expression or activity of the gene to be targeted or its encoded protein and the presence or absence of a reporter gene. The screen can be applied to cultured cells, unicellular and multicellular organisms. Manipulating the expression or activity of the target gene sensitizes the host to a molecule which inhibits the target gene or its encoded protein such that the cell or organism comprising the manipulated target gene grows at a different rate from the cell or organism comprising the unmanipulated gene in response to exposure to the molecule.

Abstract: The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine.

Abstract: Stimulus-response patterns are analyzed using deduction protocols applied through AI systems such as expert systems and neural networks. Generating an output signal matrix database involves: (i) constructing a stimulated physical matrix; (ii) detecting a physical signal at each unit of the physical matrix; (iii) transducing each physical signal to generate an electrical output signal; (iv) storing each output signal in an output signal matrix data structure; and (v) repeating steps (i)-(iv) to iteratively store output signal matrix data structures for a plurality of stimuli to form an output signal matrix database. Individual output signal matrices are compared to such output signal matrix databases according for qualitative analysis. The stimulated physical matrices comprise an ordered array of units, each confining (1) either a different responder of a living thing or a probe corresponding to such a different responder and, (2) an identifier for the responder or probe.

Abstract: Stimulus-response patterns are analyzed using deduction protocols applied through AI systems such as expert systems and neural networks. Generating an output signal matrix database involves: (i) constructing a stimulated physical matrix; (ii) detecting a physical signal at each unit of the physical matrix; (iii) transducing each physical signal to generate an electrical output signal; (iv) storing each output signal in an output signal matrix data structure; and (v) repeating steps (i)-(iv) to iteratively store output signal matrix data structures for a plurality of stimuli to form an output signal matrix database. Individual output signal matrices are compared to such output signal matrix databases according for qualitative analysis. The stimulated physical matrices comprise an ordered array of units, each confining (1) either a different responder of a living thing or a probe corresponding to such a different responder and, (2) an identifier for the responder or probe.

Abstract: Stimulus-response patterns are analyzed using deduction protocols applied through AI systems such as expert systems and neural networks. Generating an output signal matrix database involves: (i) constructing a stimulated physical matrix; (ii) detecting a physical signal at each unit of the physical matrix; (iii) transducing each physical signal to generate an electrical output signal; (iv) storing each output signal in an output signal matrix data structure; and (v) repeating steps (i)-(iv) to iteratively store output signal matrix data structures for a plurality of stimuli to form an output signal matrix database. Individual output signal matrices are compared to such output signal matrix databases according for qualitative analysis. The stimulated physical matrices comprise an ordered array of units, each confining (1) either a different responder of a living thing or a probe corresponding to such a different responder and, (2) an identifier for the responder or probe.

Abstract: Methods and compositions for modeling the transcriptional responsiveness of an organism to a candidate drug involve (a) detecting reporter gene product signals from each of a plurality of different, separately isolated cells of a target organism, wherein each cell contains a recombinant construct comprising a reporter gene operatively linked to a different endogenous transcriptional regulatory element of the target organism such that the transcriptional regulatory element regulates the expression of the reporter gene, and the sum of the cells comprises an ensemble of the transcriptional regulatory elements of the organism sufficient to model the transcriptional responsiveness of said organism to a drug; (b) contacting each cell with a candidate drug; (c) detecting reporter gene product signals from each cell; (d) comparing reporter gene product signals from each cell before and after contacting the cell with the candidate drug to obtain a drug response profile which provides a model of the transcriptional res