Abstract: A device, method and system are provided for diagnosing a disease using a gene expression reader to analyze biological samples and output gene expression values to calculate a scaling factor using a computer by counting a number of link counts Cn for groups of an individual genes' expression values at different times at a threshold value C or for groups of genes' expression values at a single time at the threshold value C, calculating an average number Cave of the link counts Cn, calculating a largest number M of the Cn, iteratively applying a relation Cave=M/log(M) for different threshold values C, comparing data of the Cave values versus M/log(M), and calculating a fitting to the compared data to output the scaling factor a. The scaling factor a is compared with other scaling factors a? in a database to output a report of estimates for a degree of health.

Abstract: A device, method and system are provided for diagnosing a disease using a gene expression reader to analyze biological samples and output gene expression values to calculate a scaling factor using a computer by counting a number of link counts Cn for groups of an individual genes' expression values at different times at a threshold value C or for groups of genes' expression values at a single time at the threshold value C, calculating an average number Cave of the link counts Cn, calculating a largest number M of the Cn, iteratively applying a relation Cave=M/log(M) for different threshold values C, comparing data of the Cave values versus M/log(M), and calculating a fitting to the compared data to output the scaling factor a. The scaling factor a is compared with other scaling factors a? in a database to output a report of estimates for a degree of health.

Abstract: A device, method and system are provided for diagnosing a disease using a gene expression reader to analyze biological samples and output gene expression values to calculate a scaling factor using a computer by counting a number of link counts Cn for groups of an individual genes' expression values at different times at a threshold value C or for groups of genes' expression values at a single time at the threshold value C, calculating an average number Cave of the link counts Cn, calculating a largest number M of the Cn, iteratively applying a relation Cave=M/log(M) for different threshold values C, comparing data of the Cave values versus M/log(M), and calculating a fitting to the compared data to output the scaling factor a. The scaling factor a is compared with other scaling factors a? in a database to output a report of estimates for a degree of health.

Abstract: There is described a method for manipulation, storage, modeling, visualization, and quantification of datasets, which correspond to target strings. An iterative algorithm is used to generate comparison strings corresponding to some set of points that can serve as the domain of an iterative function. The comparison string is scored by evaluating a function having the comparison string and one of the plurality of target strings as inputs. The score measures a relationship between a comparison string and a target string. The evaluation may be repeated for a number of the other target strings. The score or some other property corresponding to the comparison string is used to determine the target string's placement on a map. The target string may also be marked by a point on a visual display.

Abstract: There is described a method for manipulation, storage, modeling, visualization, and quantification of datasets, which correspond to target strings. A number of target strings are provided. An iterative algorithm is used to generate comparison strings corresponding to some set of points that can serve as the domain of an iterative function. Preferably these points are located in the complex plane, such as in and/or near the Mandelbrot Set or a Julia Set. These comparison strings are also datasets. The comparison string is scored by evaluating a function having the comparison string and one of the plurality of target strings as inputs. The score measures a relationship between a comparison string and a target string. The evaluation may be repeated for a number of the other target strings. The score or some other property corresponding to the comparison string is used to determine the target string's placement on a map. The target string may also be marked by a point on a visual display.

Abstract: There is described a method for manipulation, storage, modeling, visualization, and quantification of datasets, which correspond to target strings. A number of target strings are provided. An iterative algorithm is used to generate comparison strings corresponding to some set of points that can serve as the domain of an iterative function. Preferably these points are located in the complex plane, such as in and/or near the Mandelbrot Set or a Julia Set. These comparison strings are also datasets. The comparison string is scored by evaluating a function having the comparison string and one of the plurality of target strings as inputs. The score measures a relationship between a comparison string and a target string. The evaluation may be repeated for a number of the other target strings. The score or some other property corresponding to the comparison string is used to determine the target string's placement on a map. The target string may also be marked by a point on a visual display.