FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2123012927> ?p ?o ?g. }

• W2123012927 endingPage "i333" @default.
• W2123012927 startingPage "i326" @default.
• W2123012927 abstract "The diffusion kernel is a general method for computing pairwise distances among all nodes in a graph, based on the sum of weighted paths between each pair of nodes. This technique has been used successfully, in conjunction with kernel-based learning methods, to draw inferences from several types of biological networks.We show that computing the diffusion kernel is equivalent to maximizing the von Neumann entropy, subject to a global constraint on the sum of the Euclidean distances between nodes. This global constraint allows for high variance in the pairwise distances. Accordingly, we propose an alternative, locally constrained diffusion kernel, and we demonstrate that the resulting kernel allows for more accurate support vector machine prediction of protein functional classifications from metabolic and protein-protein interaction networks.Supplementary results and data are available at noble.gs.washington.edu/proj/maxent" @default.
• W2123012927 created "2016-06-24" @default.
• W2123012927 creator A5057375933 @default.
• W2123012927 creator A5070597006 @default.
• W2123012927 date "2004-08-04" @default.
• W2123012927 modified "2023-10-01" @default.
• W2123012927 title "Learning kernels from biological networks by maximizing entropy" @default.
• W2123012927 cites W14071851 @default.
• W2123012927 cites W1486817521 @default.
• W2123012927 cites W1631356911 @default.
• W2123012927 cites W2011986160 @default.
• W2123012927 cites W2013502943 @default.
• W2123012927 cites W2041862730 @default.
• W2123012927 cites W2060861141 @default.
• W2123012927 cites W2063898585 @default.
• W2123012927 cites W2065304353 @default.
• W2123012927 cites W2090766471 @default.
• W2123012927 cites W2100603120 @default.
• W2123012927 cites W2113221321 @default.
• W2123012927 cites W2113654464 @default.
• W2123012927 cites W2125508747 @default.
• W2123012927 cites W2126602684 @default.
• W2123012927 cites W2128036349 @default.
• W2123012927 cites W2144724079 @default.
• W2123012927 cites W2145590522 @default.
• W2123012927 cites W2155199032 @default.
• W2123012927 cites W2158128075 @default.
• W2123012927 cites W2164104492 @default.
• W2123012927 cites W2166106382 @default.
• W2123012927 cites W2167190345 @default.
• W2123012927 cites W2544883878 @default.
• W2123012927 cites W3119651796 @default.
• W2123012927 doi "https://doi.org/10.1093/bioinformatics/bth906" @default.
• W2123012927 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/15262816" @default.
• W2123012927 hasPublicationYear "2004" @default.
• W2123012927 type Work @default.
• W2123012927 sameAs 2123012927 @default.
• W2123012927 citedByCount "112" @default.
• W2123012927 countsByYear W21230129272012 @default.
• W2123012927 countsByYear W21230129272013 @default.
• W2123012927 countsByYear W21230129272014 @default.
• W2123012927 countsByYear W21230129272015 @default.
• W2123012927 countsByYear W21230129272016 @default.
• W2123012927 countsByYear W21230129272017 @default.
• W2123012927 countsByYear W21230129272018 @default.
• W2123012927 countsByYear W21230129272019 @default.
• W2123012927 countsByYear W21230129272020 @default.
• W2123012927 countsByYear W21230129272022 @default.
• W2123012927 countsByYear W21230129272023 @default.
• W2123012927 crossrefType "journal-article" @default.
• W2123012927 hasAuthorship W2123012927A5057375933 @default.
• W2123012927 hasAuthorship W2123012927A5070597006 @default.
• W2123012927 hasBestOaLocation W21230129271 @default.
• W2123012927 hasConcept C100595998 @default.
• W2123012927 hasConcept C106301342 @default.
• W2123012927 hasConcept C11413529 @default.
• W2123012927 hasConcept C118615104 @default.
• W2123012927 hasConcept C121332964 @default.
• W2123012927 hasConcept C122280245 @default.
• W2123012927 hasConcept C12267149 @default.
• W2123012927 hasConcept C132525143 @default.
• W2123012927 hasConcept C134517425 @default.
• W2123012927 hasConcept C136764020 @default.
• W2123012927 hasConcept C154945302 @default.
• W2123012927 hasConcept C184898388 @default.
• W2123012927 hasConcept C33923547 @default.
• W2123012927 hasConcept C34947359 @default.
• W2123012927 hasConcept C41008148 @default.
• W2123012927 hasConcept C49777392 @default.
• W2123012927 hasConcept C62520636 @default.
• W2123012927 hasConcept C74193536 @default.
• W2123012927 hasConcept C80444323 @default.
• W2123012927 hasConceptScore W2123012927C100595998 @default.
• W2123012927 hasConceptScore W2123012927C106301342 @default.
• W2123012927 hasConceptScore W2123012927C11413529 @default.
• W2123012927 hasConceptScore W2123012927C118615104 @default.
• W2123012927 hasConceptScore W2123012927C121332964 @default.
• W2123012927 hasConceptScore W2123012927C122280245 @default.
• W2123012927 hasConceptScore W2123012927C12267149 @default.
• W2123012927 hasConceptScore W2123012927C132525143 @default.
• W2123012927 hasConceptScore W2123012927C134517425 @default.
• W2123012927 hasConceptScore W2123012927C136764020 @default.
• W2123012927 hasConceptScore W2123012927C154945302 @default.
• W2123012927 hasConceptScore W2123012927C184898388 @default.
• W2123012927 hasConceptScore W2123012927C33923547 @default.
• W2123012927 hasConceptScore W2123012927C34947359 @default.
• W2123012927 hasConceptScore W2123012927C41008148 @default.
• W2123012927 hasConceptScore W2123012927C49777392 @default.
• W2123012927 hasConceptScore W2123012927C62520636 @default.
• W2123012927 hasConceptScore W2123012927C74193536 @default.
• W2123012927 hasConceptScore W2123012927C80444323 @default.
• W2123012927 hasIssue "suppl_1" @default.
• W2123012927 hasLocation W21230129271 @default.
• W2123012927 hasLocation W21230129272 @default.
• W2123012927 hasOpenAccess W2123012927 @default.
• W2123012927 hasPrimaryLocation W21230129271 @default.
• W2123012927 hasRelatedWork W1983263273 @default.
• W2123012927 hasRelatedWork W2011347035 @default.

• next