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dc.contributor.authorBertoni, Francesco
dc.contributor.authorKwee, Ivo
dc.contributor.authorMontemanni, Roberto
dc.contributor.authorAkhmedov, Murodzhon
dc.contributor.authorLenail, Alexander
dc.contributor.authorFraenkel, Ernest
dc.date.accessioned2018-10-09T13:46:44Z
dc.date.available2018-10-09T13:46:44Z
dc.date.issued2017-05
dc.identifier.isbn978-3-319-59775-1
dc.identifier.isbn978-3-319-59776-8
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttp://hdl.handle.net/1721.1/118381
dc.description.abstractThe Prize-collecting Steiner Forest (PCSF) problem is NP-hard, requiring extreme computational effort to find exact solutions for large inputs. We introduce a new heuristic algorithm for PCSF which preserves the quality of solutions obtained by previous heuristic approaches while reducing the runtime by a factor of 10 for larger graphs. By decreasing the draw on computational resources, this algorithm affords systems biologists the opportunity to analyze larger biological networks faster and narrow their analyses to individual patients. Keywords: Prize-collecting Steiner Forest, Biological networksen_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (U54-NS-091046)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (U01-CA184898)en_US
dc.description.sponsorshipSwiss National Science Foundation (205321-147138)en_US
dc.language.isoen_US
dc.publisherSpringer International Publishingen_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-319-59776-8_22en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceProf. Fraenkel via Howard Silveren_US
dc.titleA Fast Prize-Collecting Steiner Forest Algorithm for Functional Analyses in Biological Networksen_US
dc.typeArticleen_US
dc.identifier.citationAkhmedov, Murodzhon, et al. “A Fast Prize-Collecting Steiner Forest Algorithm for Functional Analyses in Biological Networks.” Integration of AI and OR Techniques in Constraint Programming, edited by Domenico Salvagnin and Michele Lombardi, vol. 10335, Springer International Publishing, 2017, pp. 263–76.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.approverFraenkel, Ernesten_US
dc.contributor.mitauthorAkhmedov, Murodzhon
dc.contributor.mitauthorLenail, Alexander
dc.contributor.mitauthorFraenkel, Ernest
dc.relation.journalIntegration of AI and OR Techniques in Constraint Programmingen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsAkhmedov, Murodzhon; LeNail, Alexander; Bertoni, Francesco; Kwee, Ivo; Fraenkel, Ernest; Montemanni, Robertoen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-9249-8181
mit.licenseOPEN_ACCESS_POLICYen_US


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