Applied Semantic Knowledgebases and Applications Thereof
Novel tools and techniques for generating and/or implementing an applied semantic knowledgebase. Some tools allow for data integration into coherent, semantically connected networks and for generation of sets of query-based models describing complex functional relationships as sub-networks. In an aspect, an applied semantic knowledgebase may comprise collections of SPARQL network queries describing a specific set of sub-network relationships and their applicable ranges for each element in the query.
1 . A method, comprising:
importing, into an informatics program, a plurality of sets of data from a plurality of sources;
synthesizing the plurality of sets of data to produce a coherent data set;
creating one or more semantic networks, the semantic networks expressing data relationships among data in the coherent data set;
obtaining a pattern characteristic for a biologically relevant function by reducing network complexity of the one or more semantic networks;
generating one or more SPARQL arrays from the pattern characteristic;
storing the one or more SPARQL arrays in a database; and
generating an applied semantic knowledgebase from the one or more SPARQL arrays.
2 . The method of claim 1 , further comprising:
screening an unknown data population with one or more of the SPARQL arrays;
identifying one or more relationships in the unknown data population, based on the screening; and
displaying an indication of the one or more relationships in a user interface.
3 . An apparatus, comprising:
a computer readable medium having encoded thereon a set of instructions executable by one or more computers to perform one or more operations, the set of instructions comprising:
instructions for importing, into an informatics program a plurality of sets of data from a plurality of sources;
instructions for synthesizing the plurality of sets of data to produce a coherent data set;
instructions for creating one or more semantic networks, the semantic networks expressing data relationships among data in the coherent data set;
instructions for obtaining a pattern characteristic for a biologically relevant function by reducing network complexity of the one or more semantic networks;
instructions for generating one or more SPARQL arrays from the pattern characteristic;
instructions for storing the one or more SPARQL arrays in a database; and
instructions for generating an applied semantic knowledgebase from the one or more SPARQL arrays.
4 . A computer system, comprising:
one or more processors; and
a computer readable medium in communication with the one or more processors, the computer readable medium having encoded thereon a set of instructions executable by the computer system to perform one or more operations, the set on instructions comprising:
instructions for importing, into an informatics program a plurality of sets of data from a plurality of sources;
instructions for synthesizing the plurality of sets of data to produce a coherent data set;
instructions for creating one or more semantic networks, the semantic networks expressing data relationships among data in the coherent data set;
instructions for obtaining a pattern characteristic for a biologically relevant function by reducing network complexity of the one or more semantic networks;
instructions for generating one or more SPARQL arrays from the pattern characteristic;
instructions for storing the one or more SPARQL arrays in a database; and
instructions for generating an applied semantic knowledgebase from the one or more SPARQL arrays.
5 . A method, comprising,
generating an applied semantic knowledgebase from one or more SPARQL arrays;
screening an unknown data population with one or more of the SPARQL arrays;
identifying one or more relationships in the unknown data population, based on the screening; and
displaying an indication of the one or more relationships in a user interface.
6 . The method of claim 5 , wherein generating an applied semantic knowledgebase comprises merging a plurality of data sets under a common ontology to produce a unified semantic network.
7 . The method of claim 6 , wherein the unified semantic network is multidimensional.
8 . The method of claim 6 , wherein generating an applied semantic knowledgebase further comprises:
displaying a plurality of markers from within the semantic network;
receiving a selection of a set of markers from within the plurality of markers, the selected set of markers representing a sub-network of the semantic network; and
saving the sub-network as a SPARQL array.
9 . The method of claim 5 , wherein generating an applied semantic knowledgebase comprises generating an applied semantic knowledgebase based on patterns or profiles representing characteristics in datasets applicable to predictive modeling and screening.
10 . The method of claim 9 , wherein generating an applied semantic knowledgebase further comprises:
performing one or more SPARQL queries to identify said patterns or profiles; and
saving said patterns or profiles as one or more applied semantic knowledgebases.
11 . The method of claim 10 , wherein the one or more SPARQL queries comprises a textual query.
12 . The method of claim 10 , wherein the one or more SPARQL queries comprises a graphical query.
13 . The method of claim 10 , wherein the one or more SPARQL queries comprises a numeric query.
14 . The method of claim 5 , further comprising:
validating, with the applied semantic knowledgebase, a predictive modeling quality of one or more known reference datasets.
15 . The method of claim 5 , further comprising:
modeling, with the applied semantic knowledgebase, one or more unknown datasets.
16 . The method of claim 5 , further comprising:
providing decision support, with the applied semantic knowledgebase, for experimental result interpretation in translational research.
17 . The method of claim 5 , further comprising:
providing decision support, with the applied semantic knowledgebase, for experimental result interpretation in drug discovery or development.
18 . The method of claim 17 , wherein providing decision support comprises target validation.
19 . The method of claim 17 , wherein providing decision support comprises biomarker discovery.
20 . The method of claim 17 , wherein biomarker discovery comprises compound efficacy and toxicity screening.
21 . The method of claim 5 , further comprising:
performing predictive modeling, using the applied semantic knowledgebase, in a personalized medicine application.
22 . The method of claim 21 , wherein the personalized medicine application is selected from the group consisting of patient screening, disease characterization and patient stratification.
23 . An apparatus, comprising:
a computer readable medium having encoded thereon a set of instructions executable by one or more computers to perform one or more operations, the set of instructions comprising:
instructions for generating an applied semantic knowledgebase from one or more SPARQL arrays;
instructions for identifying one or more relationships in the unknown data population, based on the screening; and
instructions for displaying an indication of the one or more relationships in a user interface.
24 . A computer system, comprising:
one or more processors; and
a computer readable medium in communication with the one or more processors, the computer readable medium having encoded thereon a set of instructions executable by the computer system to perform one or more operations, the set on instructions comprising:
instructions for generating an applied semantic knowledgebase from one or more SPARQL arrays;
instructions for identifying one or more relationships in the unknown data population, based on the screening; and
instructions for displaying an indication of the one or more relationships in a user interface.