{"id":"https://openalex.org/W4400908716","doi":"https://doi.org/10.1109/siu61531.2024.10601132","title":"Comparison of Machine Learning Methods in Assessing Druglikeness of Chemical Molecules: Example of Lipinski Descriptors and Lipinski Rules","display_name":"Comparison of Machine Learning Methods in Assessing Druglikeness of Chemical Molecules: Example of Lipinski Descriptors and Lipinski Rules","publication_year":2024,"publication_date":"2024-05-15","ids":{"openalex":"https://openalex.org/W4400908716","doi":"https://doi.org/10.1109/siu61531.2024.10601132"},"language":"en","primary_location":{"id":"doi:10.1109/siu61531.2024.10601132","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/siu61531.2024.10601132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","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/A5104971327","display_name":"An\u0131l Ku\u015f\u00e7u","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"An\u0131l Ku\u015f\u00e7u","raw_affiliation_strings":["Çukurova Üniversitesi,Bilgisayar Mühendisliği Bölümü,Adana,Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Çukurova Üniversitesi,Bilgisayar Mühendisliği Bölümü,Adana,Turkey","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081542798","display_name":"Mehmet Sar\u0131g\u00fcl","orcid":"https://orcid.org/0000-0001-7323-6864"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mehmet Sarig\u00fcl","raw_affiliation_strings":["Çukurova Üniversitesi,Bilgisayar Mühendisliği Bölümü,Adana,Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Çukurova Üniversitesi,Bilgisayar Mühendisliği Bölümü,Adana,Turkey","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13181832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10908","display_name":"Analytical Chemistry and Chromatography","score":0.9223999977111816,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lipinskis-rule-of-five","display_name":"Lipinski's rule of five","score":0.7300728559494019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48788881301879883},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39090675115585327},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.34687936305999756},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32308119535446167},{"id":"https://openalex.org/keywords/biochemistry","display_name":"Biochemistry","score":0.07937854528427124}],"concepts":[{"id":"https://openalex.org/C41847442","wikidata":"https://www.wikidata.org/wiki/Q916723","display_name":"Lipinski's rule of five","level":4,"score":0.7300728559494019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48788881301879883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39090675115585327},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.34687936305999756},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32308119535446167},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.07937854528427124},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C2775905019","wikidata":"https://www.wikidata.org/wiki/Q192572","display_name":"In silico","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu61531.2024.10601132","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/siu61531.2024.10601132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694"],"abstract_inverted_index":{"Assessing":[0],"drug-likeness":[1,24],"in":[2,9,30,76,82,93,123,141,160,192],"chemical":[3,117],"compounds":[4,118],"is":[5,164],"a":[6,39,113],"critical":[7],"step":[8],"drug":[10,49,143,177,198],"discovery":[11,178],"and":[12,62,80,98,107,119,155,179],"development.":[13,199],"Traditional":[14],"approaches":[15,140],"often":[16],"rely":[17],"on":[18,53,134,147,152,172],"Lipinski\u2019s":[19],"Rules":[20],"to":[21,58,103,169],"evaluate":[22],"the":[23,60,64,69,83,124,135,153,187,194],"of":[25,42,71,78,88,95,116,129,137,157,189,197],"compounds;":[26],"however,":[27],"recent":[28],"advances":[29],"machine":[31,44,73,138,190],"learning":[32,45,74,139,191],"offer":[33],"alternative":[34],"methods.":[35],"This":[36,166],"study":[37,131],"presents":[38],"comprehensive":[40],"comparison":[41,70],"various":[43],"methods":[46,90,175],"for":[47,176],"predicting":[48,142],"similarity.":[50],"Classification":[51],"based":[52],"Lipinski":[54,162],"Descriptors":[55,163],"was":[56,91],"performed":[57],"prepare":[59],"dataset":[61,111],"train":[63],"models.":[65],"The":[66,86,110,127],"research":[67],"includes":[68,112],"many":[72],"algorithms":[75,159],"terms":[77,94],"performance":[79,87],"accuracy":[81],"mentioned":[84],"context.":[85],"these":[89],"evaluated":[92],"accuracy,":[96],"sensitivity,":[97],"specificity,":[99],"considering":[100],"their":[101],"ability":[102],"distinguish":[104],"between":[105],"drug-like":[106],"non-drug-like":[108],"compounds.":[109],"wide":[114],"range":[115],"has":[120],"been":[121],"compiled":[122],"chembl":[125],"database.":[126],"findings":[128],"this":[130],"shed":[132],"light":[133],"effectiveness":[136],"similarity":[144],"without":[145],"relying":[146],"predefined":[148],"rules.":[149],"Additionally,":[150],"information":[151],"strengths":[154],"limitations":[156],"different":[158],"processing":[161],"discussed.":[165],"work":[167,171,184],"contributes":[168],"ongoing":[170],"improving":[173],"computational":[174],"may":[180],"guide":[181],"future":[182],"similar":[183],"by":[185],"highlighting":[186],"potential":[188],"optimizing":[193],"early":[195],"stages":[196]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}