{"id":"https://openalex.org/W7204467980","doi":"https://doi.org/10.4230/lipics.wabi.2026.10","title":"Exact and Efficient Inference of Tumor Phylogenies via Novel Pruning Techniques","display_name":"Exact and Efficient Inference of Tumor Phylogenies via Novel Pruning Techniques","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7204467980","doi":"https://doi.org/10.4230/lipics.wabi.2026.10"},"language":"en","primary_location":{"id":"pmh:doi:10.4230/lipics.wabi.2026.10","is_oa":true,"landing_page_url":"https://github.com/jdluque/faster-tphyl-reconstruction","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"type":"conference-paper","indexed_in":["datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://github.com/jdluque/faster-tphyl-reconstruction","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102838487","display_name":"Juan Luque","orcid":"https://orcid.org/0000-0002-6565-4684"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luque, Juan","raw_affiliation_strings":["Department of Computer Science, University of Maryland, College Park, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-6565-4684","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148431993","display_name":"Jacob Gilbert","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140884","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210140884"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gilbert, Jacob","raw_affiliation_strings":["Cancer Data Science Laboratory, National Cancer Institute, Bethesda, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cancer Data Science Laboratory, National Cancer Institute, Bethesda, MD, USA","institution_ids":["https://openalex.org/I4210140884"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118452188","display_name":"Arjun Subramanian","orcid":null},"institutions":[{"id":"https://openalex.org/I2799595691","display_name":"Pingry School","ror":"https://ror.org/04d5ffq02","country_code":"US","type":"education","lineage":["https://openalex.org/I2799595691"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Subramanian, Arjun","raw_affiliation_strings":["The Pingry School, Basking Ridge, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pingry School, Basking Ridge, NJ, USA","institution_ids":["https://openalex.org/I2799595691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005118312","display_name":"Aravind Srinivasan","orcid":"https://orcid.org/0000-0002-0062-3684"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinivasan, Aravind","raw_affiliation_strings":["Department of Computer Science, University of Maryland, College Park, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-0062-3684","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045683675","display_name":"Salem Maliki\u0107","orcid":"https://orcid.org/0000-0002-4215-5655"},"institutions":[{"id":"https://openalex.org/I4210140884","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210140884"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Malikic, Salem","raw_affiliation_strings":["Cancer Data Science Laboratory, National Cancer Institute, Bethesda, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-4215-5655","affiliations":[{"raw_affiliation_string":"Cancer Data Science Laboratory, National Cancer Institute, Bethesda, MD, USA","institution_ids":["https://openalex.org/I4210140884"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5148465027","display_name":"S. Cenk Sahinalp","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140884","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210140884"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sahinalp, S. Cenk","raw_affiliation_strings":["Cancer Data Science Laboratory, National Cancer Institute, Bethesda, MD 20894, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cancer Data Science Laboratory, National Cancer Institute, Bethesda, MD 20894, USA","institution_ids":["https://openalex.org/I4210140884"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.7202000021934509},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.625},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.5554999709129333},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49639999866485596},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4300000071525574},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.41929998993873596},{"id":"https://openalex.org/keywords/phylogenetic-tree","display_name":"Phylogenetic tree","score":0.40799999237060547},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.3693999946117401}],"concepts":[{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.7202000021934509},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.625},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5554999709129333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5403000116348267},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49639999866485596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4650999903678894},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4320000112056732},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.41929998993873596},{"id":"https://openalex.org/C193252679","wikidata":"https://www.wikidata.org/wiki/Q242125","display_name":"Phylogenetic tree","level":3,"score":0.40799999237060547},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.3693999946117401},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3555000126361847},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33649998903274536},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.3273000121116638},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29840001463890076},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C26619641","wikidata":"https://www.wikidata.org/wiki/Q3142246","display_name":"Phylogenetic network","level":4,"score":0.28949999809265137},{"id":"https://openalex.org/C207024777","wikidata":"https://www.wikidata.org/wiki/Q621673","display_name":"Search tree","level":3,"score":0.26589998602867126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.2578999996185303}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.4230/lipics.wabi.2026.10","is_oa":true,"landing_page_url":"https://github.com/jdluque/faster-tphyl-reconstruction","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},{"id":"doi:10.4230/lipics.wabi.2026.10","is_oa":true,"landing_page_url":"https://doi.org/10.4230/lipics.wabi.2026.10","pdf_url":null,"source":{"id":"https://openalex.org/S4393917817","display_name":"Leibniz international proceedings in informatics","issn_l":"1868-8969","issn":["1868-8969"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"ConferencePaper"}],"best_oa_location":{"id":"pmh:doi:10.4230/lipics.wabi.2026.10","is_oa":true,"landing_page_url":"https://github.com/jdluque/faster-tphyl-reconstruction","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reconstructing":[0],"the":[1,44,65,79,94,100,124],"evolutionary":[2,69],"history":[3,70],"of":[4,47,54,75,123],"tumors":[5],"using":[6],"single-cell":[7],"sequencing":[8],"(SCS)":[9],"data":[10],"presents":[11],"significant":[12],"computational":[13],"challenges.":[14],"Existing":[15],"approaches":[16],"are":[17],"either":[18],"computationally":[19],"intractable":[20],"for":[21,93],"emerging":[22],"large-scale":[23],"datasets":[24],"or":[25],"rely":[26],"on":[27],"heuristics":[28],"that":[29,42,63],"lack":[30],"optimality":[31],"guarantees.":[32],"In":[33],"this":[34],"work,":[35],"we":[36,86],"propose":[37],"a":[38,51,60],"novel,":[39],"time-efficient":[40],"algorithm":[41,62,113],"constructs":[43],"phylogenetic":[45],"tree":[46,102],"tumor":[48,68,125],"evolution":[49],"with":[50],"provable":[52],"guarantee":[53],"optimality.":[55],"Our":[56],"main":[57],"result":[58],"is":[59],"branch-and-bound":[61,101,108],"reconstructs":[64],"most":[66],"likely":[67],"up":[71],"to":[72,98,120],"two":[73],"orders":[74],"magnitude":[76],"faster":[77,121],"than":[78],"previous":[80,105],"best":[81],"algorithm.":[82],"To":[83],"achieve":[84],"this,":[85],"use":[87],"efficient":[88],"and":[89],"well-known":[90],"2-approximation":[91],"algorithms":[92],"Vertex":[95],"Cover":[96],"problem":[97],"prune":[99],"effectively.":[103],"Unlike":[104],"works'":[106],"polynomial-time":[107],"bounding":[109,112],"strategies,":[110],"our":[111],"provides":[114],"strong":[115],"worst-case":[116],"theoretical":[117],"guarantees,":[118],"leading":[119],"reconstruction":[122],"evolution.":[126]},"counts_by_year":[],"updated_date":"2026-08-30T07:30:35.949966","created_date":"2026-08-28T00:00:00"}
