{"id":"https://openalex.org/W4307561054","doi":"https://doi.org/10.1186/s12859-022-04998-z","title":"BoostMEC: predicting CRISPR-Cas9 cleavage efficiency through boosting models","display_name":"BoostMEC: predicting CRISPR-Cas9 cleavage efficiency through boosting models","publication_year":2022,"publication_date":"2022-10-26","ids":{"openalex":"https://openalex.org/W4307561054","doi":"https://doi.org/10.1186/s12859-022-04998-z","pmid":"https://pubmed.ncbi.nlm.nih.gov/36289480"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-022-04998-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04998-z","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04998-z","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04998-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035404360","display_name":"Oscar A. Zarate","orcid":null},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oscar A. Zarate","raw_affiliation_strings":["Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068201000","display_name":"Yiben Yang","orcid":"https://orcid.org/0009-0001-2864-7442"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiben Yang","raw_affiliation_strings":["Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620372","display_name":"Xiaozhong Wang","orcid":"https://orcid.org/0000-0001-8658-1931"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaozhong Wang","raw_affiliation_strings":["Department of Molecular BioSciences, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Molecular BioSciences, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100679503","display_name":"Jiping Wang","orcid":"https://orcid.org/0000-0003-3741-4269"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]},{"id":"https://openalex.org/I4210100400","display_name":"Northwestern University","ror":"https://ror.org/00m6w7z96","country_code":"PH","type":"education","lineage":["https://openalex.org/I4210100400"]}],"countries":["PH","US"],"is_corresponding":true,"raw_author_name":"Ji-Ping Wang","raw_affiliation_strings":["Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA. jzwang@northwestern.edu","Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA. jzwang@northwestern.edu","institution_ids":["https://openalex.org/I111979921","https://openalex.org/I4210100400"]},{"raw_affiliation_string":"Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100679503"],"corresponding_institution_ids":["https://openalex.org/I111979921","https://openalex.org/I4210100400"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2790},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2790},"fwci":1.0969,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.75994414,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"23","issue":"1","first_page":"446","last_page":"446"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10878","display_name":"CRISPR and Genetic Engineering","score":0.9779000282287598,"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/T10878","display_name":"CRISPR and Genetic Engineering","score":0.9779000282287598,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.0034000000450760126,"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/T12610","display_name":"RNA regulation and disease","score":0.0034000000450760126,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/crispr","display_name":"CRISPR","score":0.9239646196365356},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7180210947990417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6283739805221558},{"id":"https://openalex.org/keywords/cas9","display_name":"Cas9","score":0.5536431670188904},{"id":"https://openalex.org/keywords/guide-rna","display_name":"Guide RNA","score":0.44639691710472107},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.4420829713344574},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42119863629341125},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4176400303840637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4161585867404938},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3681674301624298},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.28450149297714233},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.16928109526634216},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.1415274441242218}],"concepts":[{"id":"https://openalex.org/C98108389","wikidata":"https://www.wikidata.org/wiki/Q412563","display_name":"CRISPR","level":3,"score":0.9239646196365356},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7180210947990417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6283739805221558},{"id":"https://openalex.org/C132455925","wikidata":"https://www.wikidata.org/wiki/Q16965677","display_name":"Cas9","level":4,"score":0.5536431670188904},{"id":"https://openalex.org/C97702854","wikidata":"https://www.wikidata.org/wiki/Q4039747","display_name":"Guide RNA","level":5,"score":0.44639691710472107},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.4420829713344574},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42119863629341125},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4176400303840637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4161585867404938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3681674301624298},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.28450149297714233},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.16928109526634216},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.1415274441242218},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072669","descriptor_name":"Gene Editing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072669","descriptor_name":"Gene Editing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000072669","descriptor_name":"Gene Editing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D058727","descriptor_name":"RNA, Small Untranslated","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D058727","descriptor_name":"RNA, Small Untranslated","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D058727","descriptor_name":"RNA, Small Untranslated","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D064113","descriptor_name":"CRISPR-Cas Systems","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D064113","descriptor_name":"CRISPR-Cas Systems","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D064113","descriptor_name":"CRISPR-Cas Systems","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12859-022-04998-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04998-z","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04998-z","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:36289480","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36289480","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:doaj.org/article:a89854242d96498cb52bc54fc00721e5","is_oa":true,"landing_page_url":"https://doaj.org/article/a89854242d96498cb52bc54fc00721e5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 23, Iss 1, Pp 1-14 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9597963","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9597963","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"BMC Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12859-022-04998-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-04998-z","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-04998-z","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4307561054.pdf","grobid_xml":"https://content.openalex.org/works/W4307561054.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1869792624","https://openalex.org/W1879165674","https://openalex.org/W1912701812","https://openalex.org/W1915704240","https://openalex.org/W1968342623","https://openalex.org/W1982846895","https://openalex.org/W2003171404","https://openalex.org/W2006765654","https://openalex.org/W2045435533","https://openalex.org/W2046156611","https://openalex.org/W2064815984","https://openalex.org/W2077381938","https://openalex.org/W2086561953","https://openalex.org/W2134298288","https://openalex.org/W2164695230","https://openalex.org/W2174491738","https://openalex.org/W2180291937","https://openalex.org/W2252568502","https://openalex.org/W2461013690","https://openalex.org/W2508771945","https://openalex.org/W2521327281","https://openalex.org/W2563593003","https://openalex.org/W2565920990","https://openalex.org/W2740658361","https://openalex.org/W2768348081","https://openalex.org/W2801626640","https://openalex.org/W2810756255","https://openalex.org/W2902305894","https://openalex.org/W2913240367","https://openalex.org/W2950052016","https://openalex.org/W2973312556","https://openalex.org/W2984059576","https://openalex.org/W2996772158","https://openalex.org/W3030186330","https://openalex.org/W3032564623","https://openalex.org/W3081226444","https://openalex.org/W3194399644","https://openalex.org/W4281663275"],"related_works":["https://openalex.org/W3081777379","https://openalex.org/W2615218473","https://openalex.org/W3040709352","https://openalex.org/W2977624170","https://openalex.org/W4394740655","https://openalex.org/W2605577322","https://openalex.org/W2615346513","https://openalex.org/W4307138640","https://openalex.org/W4320033130","https://openalex.org/W2667943050"],"abstract_inverted_index":{"BACKGROUND:":[0],"In":[1],"the":[2,5,17,39,101],"CRISPR-Cas9":[3,77,105,131],"system,":[4],"efficiency":[6,133,163],"of":[7,25,34,43,103,130,146],"genetic":[8],"modifications":[9],"has":[10],"been":[11,29],"found":[12,30],"to":[13,31,68,76,89,175],"vary":[14],"depending":[15],"on":[16,115,140,151,169],"single":[18],"guide":[19],"RNA":[20],"(sgRNA)":[21],"used.":[22],"A":[23],"variety":[24],"sgRNA":[26,46,135,147],"properties":[27],"have":[28],"be":[32],"predictive":[33],"CRISPR":[35,162],"cleavage":[36,78,132],"efficiency,":[37],"including":[38],"position-specific":[40],"sequence":[41,47,144],"composition":[42],"sgRNAs,":[44],"global":[45],"properties,":[48],"and":[49,119,137,142,149,181],"thermodynamic":[50],"features.":[51],"While":[52],"prevalent":[53],"existing":[54],"deep":[55,170],"learning-based":[56],"approaches":[57],"provide":[58,127],"competitive":[59,122],"prediction":[60,102,164],"accuracy,":[61],"a":[62,83],"more":[63,177],"interpretable":[64,178],"model":[65],"is":[66],"desirable":[67],"help":[69],"understand":[70],"how":[71],"different":[72],"features":[73,145],"may":[74],"contribute":[75],"efficiency.":[79,107],"RESULTS:":[80],"We":[81,108],"propose":[82],"gradient":[84],"boosting":[85],"approach,":[86],"utilizing":[87],"LightGBM":[88],"develop":[90],"an":[91,157],"integrated":[92],"tool,":[93],"BoostMEC":[94,110,125,155],"(Boosting":[95],"Model":[96],"for":[97,100,134],"Efficient":[98],"CRISPR),":[99],"wild-type":[104],"editing":[106],"benchmark":[109],"against":[111],"10":[112],"popular":[113],"models":[114,165],"13":[116],"external":[117],"datasets":[118],"show":[120],"its":[121,173],"performance.":[123],"CONCLUSIONS:":[124],"can":[126],"state-of-the-art":[128,161],"predictions":[129],"design":[136],"selection.":[138],"Relying":[139],"direct":[141],"derived":[143],"sequences":[148],"based":[150,168],"conventional":[152],"machine":[153],"learning,":[154],"maintains":[156],"advantage":[158],"over":[159],"other":[160],"that":[166],"are":[167],"learning":[171],"through":[172],"ability":[174],"produce":[176],"feature":[179],"insights":[180],"predictions.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
