Abstract: An information management system creates data structures based entirely on the content of source files, then compares these data structures to discover synergies and commonalities. In one embodiment, the system accepts a first collection of source files, and extracts text from each source file. The text is compared to tags in one or more dictionaries, which comprise hierarchical listing of tags. Tags matching the text are associated with each source file. The system then generates a virtual relational network in which each source file having matching tags is a node. Tags associated with two or more source files are links between the nodes. This virtual relational network may be compared with another virtual relational network to discover common nodes or links. Source files later added to a collection are massively linked by associating all tags from all source files with the newly added source file, and vice versa.

Abstract: An information management system creates data structures based entirely on the content of source files, then compares these data structures to discover synergies and commonalities. In one embodiment, the system accepts a first collection of source files, and extracts text from each source file. The text is compared to tags in one or more dictionaries, which comprise hierarchical listing of tags. Tags matching the text are associated with each source file. The system then generates a virtual relational network in which each source file having matching tags is a node. Tags associated with two or more source files are links between the nodes. This virtual relational network may be compared with another virtual relational network to discover common nodes or links. Source files later added to a collection are massively linked by associating all tags from all source files with the newly added source file, and vice versa.

Abstract: An information management system creates data structures based entirely on the content of source files, then compares these data structures to discover synergies and commonalities. In one embodiment, the system accepts a first collection of source files, and extracts text from each source file. The text is compared to tags in one or more dictionaries, which comprise hierarchical listing of tags. Tags matching the text are associated with each source file. The system then generates a virtual relational network in which each source file having matching tags is a node. Tags associated with two or more source files are links between the nodes. This virtual relational network may be compared with another virtual relational network to discover common nodes or links. Source files later added to a collection are massively linked by associating all tags from all source files with the newly added source file, and vice versa.

Abstract: An information management system creates data structures based entirely on the content of source files, then compares these data structures to discover synergies and commonalities. In one embodiment, the system accepts a first collection of source files, and extracts text from each source file. The text is compared to tags in one or more dictionaries, which comprise hierarchical listing of tags. Tags matching the text are associated with each source file. The system then generates a virtual relational network in which each source file having matching tags is a node. Tags associated with two or more source files are links between the nodes. This virtual relational network may be compared with another virtual relational network to discover common nodes or links. Source files later added to a collection are massively linked by associating all tags from all source files with the newly added source file, and vice versa.

Abstract: An information management system creates data structures based entirely on the content of source files, then compares these data structures to discover synergies and commonalities. In one embodiment, the system accepts a first collection of source files, and extracts text from each source file. The text is compared to tags in one or more dictionaries, which comprise hierarchical listing of tags. Tags matching the text are associated with each source file. The system then generates a virtual relational network in which each source file having matching tags is a node. Tags associated with two or more source files are links between the nodes. This virtual relational network may be compared with another virtual relational network to discover common nodes or links. Source files later added to a collection are massively linked by associating all tags from all source files with the newly added source file, and vice versa.

Abstract: The database is populated with target chemicals, corresponding listings of reagent chemicals, corresponding listings of equipment and corresponding listings of procedures. The database is then searched in response to user identification of a target chemical. In response, a listing is displayed of reagent chemicals that are used to synthesize the target chemical, equipment that is used to synthesize the target chemical, and a procedure that is used to synthesize the target chemical by reacting the reagent chemicals in the equipment according to the procedure. An icon-based reaction editor and/or context-sensitive Boolean query option generators may be provided. A reaction template may be used to perform predictive chemistry. A reaction relay may be used to graphically display related chemicals and procedures using a hub and spoke arrangement.

Abstract: An information management system creates data structures based entirely on the content of source files, then compares these data structures to discover synergies and commonalities. In one embodiment, the system accepts a first collection of source files, and extracts text from each source file. The text is compared to tags in one or more dictionaries, which comprise hierarchical listing of tags. Tags matching the text are associated with each source file. The system then generates a virtual relational network in which each source file having matching tags is a node. Tags associated with two or more source files are links between the nodes. This virtual relational network may be compared with another virtual relational network to discover common nodes or links. Source files later added to a collection are massively linked by associating all tags from all source files with the newly added source file, and vice versa.

Abstract: The database is populated with target chemicals, corresponding listings of reagent chemicals, corresponding listings of equipment and corresponding listings of procedures. The database is then searched in response to user identification of a target chemical. In response, a listing is displayed of reagent chemicals that are used to synthesize the target chemical, equipment that is used to synthesize the target chemical, and a procedure that is used to synthesize the target chemical by reacting the reagent chemicals in the equipment according to the procedure. An icon-based reaction editor and/or context-sensitive Boolean query option generators may be provided. A reaction template may be used to perform predictive chemistry. A reaction relay may be used to graphically display related chemicals and procedures using a hub and spoke arrangement.

Abstract: The database is populated with target chemicals, corresponding listings of reagent chemicals, corresponding listings of equipment and corresponding listings of procedures. The database is then searched in response to user identification of a target chemical. In response, a listing is displayed of reagent chemicals that are used to synthesize the target chemical, equipment that is used to synthesize the target chemical, and a procedure that is used to synthesize the target chemical by reacting the reagent chemicals in the equipment according to the procedure. An icon-based reaction editor and/or context-sensitive Boolean query option generators may be provided. A reaction template may be used to perform predictive chemistry. A reaction relay may be used to graphically display related chemicals and procedures using a hub and spoke arrangement.

Abstract: In response to a user query that identifies a target chemical, a listing is displayed of reagent chemicals that are used to synthesize the target chemical. A listing also is displayed of equipment that is used to synthesize the target chemical. A listing also is displayed of a procedure that is used to synthesize the target chemical by reacting the reagent chemicals in the equipment according to the procedure. User input is accepted to electronically order the reagent chemicals that are used to synthesize the target chemical, the target chemical itself and/or the equipment that is used to synthesize the target chemical. In response, a transaction is performed to electronically order the reagent chemicals that are used to synthesize the target chemical, the equipment that is used to synthesize the target chemical and/or the target chemical itself.

Abstract: In response to a user query that identifies a target chemical, a listing is displayed of reagent chemicals that are used to synthesize the target chemical. A listing also is displayed of equipment that is used to synthesize the target chemical. A listing also is displayed of a procedure that is used to synthesize the target chemical by reacting the reagent chemicals in the equipment according to the procedure. User input is accepted to electronically order the reagent chemicals that are used to synthesize the target chemical, the target chemical itself, and/or the equipment that is used to synthesize the target chemical. In response, a transaction is performed to electronically order the reagent chemicals that are used to synthesize the target chemical, the equipment that is used to synthesize the target chemical and/or the target chemical itself.