{"id":"https://openalex.org/W2914503804","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633240","title":"Using Support Tensor Mechine for Predicting Cell Penetrating Peptides by Fusing DipC and TipC","display_name":"Using Support Tensor Mechine for Predicting Cell Penetrating Peptides by Fusing DipC and TipC","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2914503804","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633240","mag":"2914503804"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2018.8633240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5101816456","display_name":"Lin Deng","orcid":"https://orcid.org/0000-0003-0177-7252"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Deng","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079218325","display_name":"Yuan Fang","orcid":"https://orcid.org/0000-0001-5740-9526"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Fang","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040105964","display_name":"Shunfang Wang","orcid":"https://orcid.org/0000-0002-1927-8753"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunfang Wang","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009775329","display_name":"Zicheng Cao","orcid":"https://orcid.org/0000-0001-6215-6850"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zicheng Cao","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101816456"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13753071,"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":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9987000226974487,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9987000226974487,"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/T10725","display_name":"RNA Interference and Gene Delivery","score":0.9957000017166138,"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/T10602","display_name":"Glycosylation and Glycoproteins Research","score":0.9882000088691711,"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/support-vector-machine","display_name":"Support vector machine","score":0.8209308981895447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.749075174331665},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.603538453578949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5579838156700134},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5464949607849121},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5140637159347534},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4937792718410492},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43311724066734314},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42685699462890625}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8209308981895447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.749075174331665},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.603538453578949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5579838156700134},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5464949607849121},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5140637159347534},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4937792718410492},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43311724066734314},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42685699462890625},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2018.8633240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323193","display_name":"Natural Science Foundation of Yunnan Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1606139699","https://openalex.org/W1838260305","https://openalex.org/W1985718949","https://openalex.org/W2048960012","https://openalex.org/W2069182579","https://openalex.org/W2090091537","https://openalex.org/W2097169398","https://openalex.org/W2114358087","https://openalex.org/W2114661696","https://openalex.org/W2134837462","https://openalex.org/W2137611320","https://openalex.org/W2148002238","https://openalex.org/W2151040995","https://openalex.org/W2168639488","https://openalex.org/W2220780917","https://openalex.org/W3146366344"],"related_works":["https://openalex.org/W2250488071","https://openalex.org/W2356150353","https://openalex.org/W2090763504","https://openalex.org/W2380744779","https://openalex.org/W1999647744","https://openalex.org/W2018643641","https://openalex.org/W4288315282","https://openalex.org/W2951122819","https://openalex.org/W2009284386","https://openalex.org/W2353313924"],"abstract_inverted_index":{"Cell":[0],"penetrating":[1,26,106,163,179],"peptides":[2,107,164],"can":[3,136],"carry":[4],"a":[5,14,43,83,99,111,171],"variety":[6],"of":[7,24,50,64,85,102,104,131,142,150,156,161,177],"bioactive":[8],"substances":[9],"into":[10,97],"cells":[11],"and":[12,17,38,69,78,94,134,147],"play":[13],"biological":[15,91],"activity":[16],"therapeutic":[18],"role.":[19],"Aiming":[20],"at":[21],"the":[22,48,62,65,126,129,132,143,148,159,175],"prediction":[23,176],"cell":[25,105,162,178],"peptides,":[27],"this":[28],"paper":[29],"fused":[30],"two":[31],"feature":[32,45,67,167],"extraction":[33],"methods":[34],"dipeptide":[35],"composition":[36,40],"(DipC)":[37],"tripeptide":[39],"(TipC)":[41],"as":[42],"new":[44,172],"expression":[46],"on":[47,125],"premise":[49],"sequence":[51],"segmentation.":[52],"Then,":[53],"linear":[54],"discriminant":[55],"analysis":[56],"(LDA)":[57],"was":[58,74,152],"used":[59,75,87],"to":[60,76,118],"reduce":[61],"dimensions":[63],"three":[66],"expressions,":[68],"support":[70,114],"vector":[71],"machine":[72,116],"(SVM)":[73],"classify":[77],"predict.":[79],"Besides,":[80],"SVM":[81,157],"is":[82],"kind":[84],"commonly":[86],"classification":[88,93],"method":[89,146],"in":[90,158],"sequence-based":[92],"prediction.":[95],"Taking":[96],"acount":[98],"fewer":[100],"number":[101],"samples":[103],"consideration,":[108],"we":[109],"introduced":[110],"novel":[112],"classifier":[113],"sentor":[115],"(STM)":[117],"compare":[119],"with":[120],"SVM.":[121],"It's":[122],"showed":[123],"based":[124],"results":[127],"that":[128,141,155],"fusion":[130],"TipC":[133],"DipC":[135],"get":[137],"higher":[138,153],"accurary":[139],"than":[140,154],"single":[144],"feature-based":[145],"accuracy":[149],"STM":[151],"identification":[160],"under":[165],"different":[166],"expression,":[168],"which":[169],"brought":[170],"idea":[173],"for":[174],"peptides.":[180]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
