{"id":"https://openalex.org/W2912998328","doi":"https://doi.org/10.1109/bibm.2018.8621190","title":"Predicting Local Inversions Using Rectangle Clustering and Representative Rectangle Prediction","display_name":"Predicting Local Inversions Using Rectangle Clustering and Representative Rectangle Prediction","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2912998328","doi":"https://doi.org/10.1109/bibm.2018.8621190","mag":"2912998328"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2018.8621190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2018.8621190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101629418","display_name":"Shenglong Zhu","orcid":"https://orcid.org/0000-0003-1989-1248"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shenglong Zhu","raw_affiliation_strings":["Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019857186","display_name":"Scott Emrich","orcid":"https://orcid.org/0000-0002-5741-4517"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Scott J. Emrich","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060901632","display_name":"Danny Z. Chen","orcid":"https://orcid.org/0000-0001-6565-2884"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danny Z. Chen","raw_affiliation_strings":["Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101629418"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":0.3677,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61203757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"38","issue":null,"first_page":"254","last_page":"259"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10521","display_name":"RNA and protein synthesis mechanisms","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10434","display_name":"Chromosomal and Genetic Variations","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7497854232788086},{"id":"https://openalex.org/keywords/rectangle","display_name":"Rectangle","score":0.7444950938224792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6476637125015259},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.6440991759300232},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5578088164329529},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5140279531478882},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.4848853051662445},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.456484317779541},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.43437647819519043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39878618717193604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34994396567344666},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19333741068840027},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08694705367088318},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08467534184455872},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08276474475860596}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7497854232788086},{"id":"https://openalex.org/C2781302577","wikidata":"https://www.wikidata.org/wiki/Q209","display_name":"Rectangle","level":2,"score":0.7444950938224792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6476637125015259},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6440991759300232},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5578088164329529},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5140279531478882},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4848853051662445},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.456484317779541},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.43437647819519043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39878618717193604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34994396567344666},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19333741068840027},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08694705367088318},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08467534184455872},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08276474475860596},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2018.8621190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2018.8621190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1982977023","https://openalex.org/W1984068087","https://openalex.org/W1993608360","https://openalex.org/W2012328875","https://openalex.org/W2018286686","https://openalex.org/W2025183726","https://openalex.org/W2032247293","https://openalex.org/W2056078939","https://openalex.org/W2082534286","https://openalex.org/W2095680943","https://openalex.org/W2102163928","https://openalex.org/W2103011829","https://openalex.org/W2104817809","https://openalex.org/W2105510846","https://openalex.org/W2110171180","https://openalex.org/W2111350087","https://openalex.org/W2116753165","https://openalex.org/W2130407782","https://openalex.org/W2133112449","https://openalex.org/W2137759177","https://openalex.org/W2139993758","https://openalex.org/W2140869203","https://openalex.org/W2141581393","https://openalex.org/W2146005104","https://openalex.org/W2150506261","https://openalex.org/W2160261558","https://openalex.org/W2161382621","https://openalex.org/W2162927194","https://openalex.org/W2164558813","https://openalex.org/W2169508919","https://openalex.org/W2189047836","https://openalex.org/W2194510225","https://openalex.org/W2559529626","https://openalex.org/W2575750030","https://openalex.org/W2773788879","https://openalex.org/W2803750811","https://openalex.org/W2884561358","https://openalex.org/W2891476731","https://openalex.org/W2950121474","https://openalex.org/W2950354111","https://openalex.org/W4230122138","https://openalex.org/W4240700790","https://openalex.org/W4394666350","https://openalex.org/W6674561012","https://openalex.org/W6676232336","https://openalex.org/W6747082828"],"related_works":["https://openalex.org/W2242098268","https://openalex.org/W4244945894","https://openalex.org/W4224881918","https://openalex.org/W2760515006","https://openalex.org/W2003462717","https://openalex.org/W2802042052","https://openalex.org/W174828583","https://openalex.org/W1987609185","https://openalex.org/W2321986606","https://openalex.org/W2059098648"],"abstract_inverted_index":{"As":[0],"a":[1,53,91],"specific":[2],"type":[3],"of":[4,63],"structural":[5],"variation,":[6],"inversions":[7,24],"are":[8],"particularly":[9],"interesting":[10],"due":[11],"to":[12,90],"their":[13],"established":[14],"role":[15],"in":[16,27,38],"evolution.":[17],"Using":[18],"third-generation":[19],"sequencing":[20],"technology":[21],"for":[22,56],"predicting":[23],"is":[25],"growing":[26],"interest,":[28],"but":[29],"many":[30,41],"such":[31],"methods":[32],"focus":[33],"on":[34,60,112],"improving":[35],"sensitivity,":[36],"resulting":[37],"either":[39],"too":[40],"false":[42,80],"positives":[43],"or":[44],"very":[45,110],"long":[46],"runtime.":[47],"In":[48],"this":[49,105],"paper,":[50],"we":[51],"propose":[52],"new":[54,106],"framework":[55,107],"inversion":[57,82],"detection":[58],"based":[59],"the":[61,86],"combination":[62,75],"two":[64],"novel":[65],"theoretical":[66],"models:":[67],"Rectangle":[68,72],"Clustering":[69],"and":[70,98],"Representative":[71],"Prediction.":[73],"This":[74],"can":[76,108,117],"automatically":[77],"filter":[78],"out":[79],"positive":[81,100],"predictions":[83],"while":[84],"retaining":[85],"correct":[87],"ones,":[88],"leading":[89],"method":[92],"that":[93],"has":[94],"both":[95],"high":[96,99],"sensitivity":[97],"prediction":[101],"values":[102],"(PPV).":[103],"Further,":[104],"run":[109],"fast":[111],"available":[113],"data.":[114],"Our":[115],"software":[116],"be":[118],"freely":[119],"obtained":[120],"at":[121],"https://github.com/UTbioinf/RigInv.":[122]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}