Method for analyzing biological networks
Significance of biological pathway in disease state is predicted by (a) providing expression level data for a plurality of biomolecules differentially expressed in a disease state, compared with same biomolecules expressed in a non-diseased state: (b) determining presence probability of the biomolec...
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creator | Dr{hacek over (a)}ghici, Sorin |
description | Significance of biological pathway in disease state is predicted by (a) providing expression level data for a plurality of biomolecules differentially expressed in a disease state, compared with same biomolecules expressed in a non-diseased state: (b) determining presence probability of the biomolecules in disease state; (c) determining effect of each biomolecule from the plurality of biomolecules on the expression of different downstream biomolecules within pathway to provide perturbation factor for each biomolecule in the pathway; (d) combining statistical significance of differentially expressed biomolecules present in the disease state, with a sum of perturbation factors for all of the biomolecules, generating an impact factor; (e) calculating statistical significance of impact factor based upon determined probability of having statistical significant presence of differentially expressed biomolecules in step (b) and the sum of perturbation factors in step (c); and (f) outputting statistical significance of impact factor for the pathway relevant to the disease. |
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(c) determining effect of each biomolecule from the plurality of biomolecules on the expression of different downstream biomolecules within pathway to provide perturbation factor for each biomolecule in the pathway; (d) combining statistical significance of differentially expressed biomolecules present in the disease state, with a sum of perturbation factors for all of the biomolecules, generating an impact factor; (e) calculating statistical significance of impact factor based upon determined probability of having statistical significant presence of differentially expressed biomolecules in step (b) and the sum of perturbation factors in step (c); and (f) outputting statistical significance of impact factor for the pathway relevant to the disease.</description><language>eng</language><creationdate>2011</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/8068994$$EPDF$$P50$$Guspatents$$Hfree_for_read</linktopdf><link.rule.ids>230,308,780,802,885,64039</link.rule.ids><linktorsrc>$$Uhttps://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/8068994$$EView_record_in_USPTO$$FView_record_in_$$GUSPTO$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Dr{hacek over (a)}ghici, Sorin</creatorcontrib><creatorcontrib>Wayne State University</creatorcontrib><title>Method for analyzing biological networks</title><description>Significance of biological pathway in disease state is predicted by (a) providing expression level data for a plurality of biomolecules differentially expressed in a disease state, compared with same biomolecules expressed in a non-diseased state: (b) determining presence probability of the biomolecules in disease state; (c) determining effect of each biomolecule from the plurality of biomolecules on the expression of different downstream biomolecules within pathway to provide perturbation factor for each biomolecule in the pathway; (d) combining statistical significance of differentially expressed biomolecules present in the disease state, with a sum of perturbation factors for all of the biomolecules, generating an impact factor; (e) calculating statistical significance of impact factor based upon determined probability of having statistical significant presence of differentially expressed biomolecules in step (b) and the sum of perturbation factors in step (c); and (f) outputting statistical significance of impact factor for the pathway relevant to the disease.</description><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2011</creationdate><recordtype>patent</recordtype><sourceid>EFH</sourceid><recordid>eNrjZNDwTS3JyE9RSMsvUkjMS8yprMrMS1dIyszPyU_PTE7MUchLLSnPL8ou5mFgTUvMKU7lhdLcDApuriHOHrqlxQWJJal5JcXx6UWJIMrAwsDMwtLSxJgIJQDJUCmc</recordid><startdate>20111129</startdate><enddate>20111129</enddate><creator>Dr{hacek over (a)}ghici, Sorin</creator><scope>EFH</scope></search><sort><creationdate>20111129</creationdate><title>Method for analyzing biological networks</title><author>Dr{hacek over (a)}ghici, Sorin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-uspatents_grants_080689943</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2011</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Dr{hacek over (a)}ghici, Sorin</creatorcontrib><creatorcontrib>Wayne State University</creatorcontrib><collection>USPTO Issued Patents</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dr{hacek over (a)}ghici, Sorin</au><aucorp>Wayne State University</aucorp><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Method for analyzing biological networks</title><date>2011-11-29</date><risdate>2011</risdate><abstract>Significance of biological pathway in disease state is predicted by (a) providing expression level data for a plurality of biomolecules differentially expressed in a disease state, compared with same biomolecules expressed in a non-diseased state: (b) determining presence probability of the biomolecules in disease state; (c) determining effect of each biomolecule from the plurality of biomolecules on the expression of different downstream biomolecules within pathway to provide perturbation factor for each biomolecule in the pathway; (d) combining statistical significance of differentially expressed biomolecules present in the disease state, with a sum of perturbation factors for all of the biomolecules, generating an impact factor; (e) calculating statistical significance of impact factor based upon determined probability of having statistical significant presence of differentially expressed biomolecules in step (b) and the sum of perturbation factors in step (c); and (f) outputting statistical significance of impact factor for the pathway relevant to the disease.</abstract><oa>free_for_read</oa></addata></record> |
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title | Method for analyzing biological networks |
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