Predicting the subcellular location of prokaryotic proteins with DeepLocPro
Protein subcellular location prediction is a widely explored task in bioinformatics because of its importance in proteomics research. We propose DeepLocPro, an extension to the popular method DeepLoc, tailored specifically to archaeal and bacterial organisms. DeepLocPro is a multiclass subcellular l...
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| Veröffentlicht in: | Bioinformatics (Oxford, England) England), 2024-11, Vol.40 (12) |
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| container_title | Bioinformatics (Oxford, England) |
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| creator | Moreno, Jaime Nielsen, Henrik Winther, Ole Teufel, Felix |
| description | Protein subcellular location prediction is a widely explored task in bioinformatics because of its importance in proteomics research. We propose DeepLocPro, an extension to the popular method DeepLoc, tailored specifically to archaeal and bacterial organisms.
DeepLocPro is a multiclass subcellular location prediction tool for prokaryotic proteins, trained on experimentally verified data curated from UniProt and PSORTdb. DeepLocPro compares favorably to the PSORTb 3.0 ensemble method, surpassing its performance across multiple metrics in our benchmark experiment.
The DeepLocPro prediction tool is available online at https://ku.biolib.com/deeplocpro and https://services.healthtech.dtu.dk/services/DeepLocPro-1.0/. |
| doi_str_mv | 10.1093/bioinformatics/btae677 |
| format | Article |
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DeepLocPro is a multiclass subcellular location prediction tool for prokaryotic proteins, trained on experimentally verified data curated from UniProt and PSORTdb. DeepLocPro compares favorably to the PSORTb 3.0 ensemble method, surpassing its performance across multiple metrics in our benchmark experiment.
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DeepLocPro is a multiclass subcellular location prediction tool for prokaryotic proteins, trained on experimentally verified data curated from UniProt and PSORTdb. DeepLocPro compares favorably to the PSORTb 3.0 ensemble method, surpassing its performance across multiple metrics in our benchmark experiment.
The DeepLocPro prediction tool is available online at https://ku.biolib.com/deeplocpro and https://services.healthtech.dtu.dk/services/DeepLocPro-1.0/.</description><subject>Archaeal Proteins - chemistry</subject><subject>Archaeal Proteins - metabolism</subject><subject>Bacterial Proteins - metabolism</subject><subject>Computational Biology - methods</subject><subject>Databases, Protein</subject><subject>Proteomics - methods</subject><subject>Software</subject><issn>1367-4811</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkE1PwzAMhiMEYjD4C1OPXMqcps3HEY1PMYkd4FwlacICbTOSVoh_T6YNBBfbsl7brx-EZhguMQgyV8673vrQycHpOFeDNJSxA3SCCWV5yTE-_FNP0GmMbwBQQUWP0YSIqgRG-Al6XAXTOD24_jUb1iaLo9KmbcdWhqz1Om33feZttgn-XYYvn65t68G4Pmafblhn18Zsll6vgj9DR1a20Zzv8xS93N48L-7z5dPdw-JqmWsMhOeMWK5kA1qwoqoog9I2VjQWCsGIsSWjRDRgtBRMFgKnwAtQkDpYKKEtmaKL3d5k5GM0cag7F7euZW_8GGuCC84LQglPUrqT6uBjDMbWm-C69EiNod6CrP-DrPcg0-Bsf2NUnWl-x37IkW_o0HXj</recordid><startdate>20241128</startdate><enddate>20241128</enddate><creator>Moreno, Jaime</creator><creator>Nielsen, Henrik</creator><creator>Winther, Ole</creator><creator>Teufel, Felix</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-1275-8065</orcidid><orcidid>https://orcid.org/0000-0002-9412-9643</orcidid></search><sort><creationdate>20241128</creationdate><title>Predicting the subcellular location of prokaryotic proteins with DeepLocPro</title><author>Moreno, Jaime ; Nielsen, Henrik ; Winther, Ole ; Teufel, Felix</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1038-73f8bad0c972556704fdf9df02973ef47639d0eca97a2917a2820b00ec19b9cf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Archaeal Proteins - chemistry</topic><topic>Archaeal Proteins - metabolism</topic><topic>Bacterial Proteins - metabolism</topic><topic>Computational Biology - methods</topic><topic>Databases, Protein</topic><topic>Proteomics - methods</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Moreno, Jaime</creatorcontrib><creatorcontrib>Nielsen, Henrik</creatorcontrib><creatorcontrib>Winther, Ole</creatorcontrib><creatorcontrib>Teufel, Felix</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Bioinformatics (Oxford, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Moreno, Jaime</au><au>Nielsen, Henrik</au><au>Winther, Ole</au><au>Teufel, Felix</au><au>Cowen, Lenore</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the subcellular location of prokaryotic proteins with DeepLocPro</atitle><jtitle>Bioinformatics (Oxford, England)</jtitle><addtitle>Bioinformatics</addtitle><date>2024-11-28</date><risdate>2024</risdate><volume>40</volume><issue>12</issue><issn>1367-4811</issn><eissn>1367-4811</eissn><abstract>Protein subcellular location prediction is a widely explored task in bioinformatics because of its importance in proteomics research. We propose DeepLocPro, an extension to the popular method DeepLoc, tailored specifically to archaeal and bacterial organisms.
DeepLocPro is a multiclass subcellular location prediction tool for prokaryotic proteins, trained on experimentally verified data curated from UniProt and PSORTdb. DeepLocPro compares favorably to the PSORTb 3.0 ensemble method, surpassing its performance across multiple metrics in our benchmark experiment.
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Access via Oxford University Press (Open Access Collection); EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection |
| subjects | Archaeal Proteins - chemistry Archaeal Proteins - metabolism Bacterial Proteins - metabolism Computational Biology - methods Databases, Protein Proteomics - methods Software |
| title | Predicting the subcellular location of prokaryotic proteins with DeepLocPro |
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