System and method for evaluating data using and applying a virtual landscape

1 . The method of generating a structured format document comprising the steps of:

generating at least one new coded form of a chemical or biological entity based on combinations of the identified, common and non-common features of one or more biological or chemical identifiers mapped to a virtual n-dimensional array, wherein generating at least one new coded form of a chemical or biological entity, further comprises:

submitting, in electronic form, a search to at least one document database for documents describing the subject matter using a defined search strategy;

extrapolating, to a first array within the memory of the computer, at least one biologic or chemical identifier described in at least one document returned from the search, the extrapolating step using an extraction module comprising code executing in a processor;

transforming each biologic identifier in the first array into a respective coded form having a range of values using a conversion module comprising code executing in the processor;

populating the respective coded forms into a second array within the memory of the computer;

generating a virtual n-dimensional array of nodes configured to encompass the range of values in the second array using a node array generator module comprising code executing in the processor, each node of the virtual n-dimensional array having an associated weight vector value based on the range of values in the second array;

placing each coded form in the second array into a node of the virtual n-dimensional array according to an unsupervised learning algorithm using a placement module comprising code executing in the processor to effect a placement;

outputting at least one chemical or biological identifier corresponding to the new coded form; and

generating a structured text document that includes the chemical or biological identifier.

2 . The method of claim 1 , further comprising the steps of:

selecting a target node among the nodes within the virtual n-dimensional array;

comparing, using a chemical feature (“CF”) module which comprises code executing in the processor, at least one CF corresponding to the coded form contained within a first node adjacent to the target node to at least one CF corresponding to the coded form contained in at least a second node adjacent to the target node, the first and second nodes sharing a border with the target node in the virtual n-dimensional array;

identifying common and non-common CFs between the target and second nodes using a commonality module which comprises code executing in the processor;

generating at least one new coded form based on combinations of the identified, common and non-common CFs which, when inserted into the virtual n-dimensional array, results in a placement within the target node, using a coded form generator module which comprises code executing in the processor; and

outputting a chemical identifier corresponding to the new coded form.

3 . The method of claim 1 , wherein the chemical or biological identifier is output to a generated structured text document.

4 . The method of claim 3 , wherein the structured text document is a patent application.

5 . The method of claim 3 , wherein the step of generating the structured text document comprises the steps of:

accessing, from a processor, a structured text template data structure, wherein the structured text template data structure includes one or more default variables;

updating at least one default variable of the structured template data structure to include reference to the outputted chemical or biological identifier;

converting the structured text template data structure to the structured text document.

6 . The method of claim 3 , wherein the step of generating the structured text document comprises the steps of:

accessing, from a processor, a pre-trained neural network, wherein the pre-trained neural network is configured to receive a parameter list that includes at least one biological or chemical identifier and at least one ailment associated with the chemical or biological identifier;

providing the outputted chemical or biological identifier and the at least one ailment associated therewith to the pre-trained neural network; and

outputting, using the neural network a structured text document that includes the at least one chemical or biological identifier and at least one ailment associated with the chemical or biological identifier.

7 . The method of claim 1 , further comprising:

generating a visual display indicating the addition of numerical forms to virtual n-dimensional array of nodes in the memory, wherein the addition of numerical forms concerns a common owner of the patent documents returned from the search, wherein the generating uses a time-series module comprising code executing in the processor;

generating, using a time series plotting module comprising code executing in the processor, a time series plot indicating the publication of the patent documents over time;

extrapolating, with an extrapolating module comprising code executing in the processor and based on the rate of publication of the patent documents and biologic or chemical identifiers extracted from the patent documents, a development path for an inventor or assignee; common to the patent documents returned from the search;

generating a new biologic or chemical entity that when placed in virtual n-dimensional array of nodes occupies a node in the development path; and

outputting a chemical formula corresponding to the new numerical value.

8 . The method of claim 7 , further comprising:

generating, with a synthesis design module configured as code executing on the processor to generate, based on the new biologic identifier, a synthesis strategy for synthesizing a biologic described by the biologic identifier; and

adding the synthesis strategy to the structured text document.