{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T01:54:11Z","timestamp":1783475651957,"version":"3.55.0"},"reference-count":13,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T00:00:00Z","timestamp":1567468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R35 GM118101"],"award-info":[{"award-number":["R35 GM118101"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["2P30CA046592"],"award-info":[{"award-number":["2P30CA046592"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["NCIR37CA214955-01A1"],"award-info":[{"award-number":["NCIR37CA214955-01A1"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["RSG-16-005-01"],"award-info":[{"award-number":["RSG-16-005-01"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University of Michigan Biosciences Initiative and UM Natural Products Discovery Core"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>DDAP is a tool for predicting the biosynthetic pathways of the products of type I modular polyketide synthase (PKS) with the focus on providing a more accurate prediction of the ordering of proteins and substrates in the pathway. In this study, the module docking domain (DD) affinity prediction performance on a hold-out testing dataset reached 0.88 as measured by the area under the receiver operating characteristic (ROC) curve (AUC); the Mean Reciprocal Ranking (MRR) of pathway prediction reached 0.67. DDAP has advantages compared to previous informatics tools in several aspects: (i) it does not rely on large databases, making it a high efficiency tool, (ii) the predicted DD affinity is represented by a probability (0\u20131), which is more intuitive than raw scores, (iii) its performance is competitive compared to the current popular rule-based algorithm. DDAP is so far the first machine learning based algorithm for type I PKS DD affinity and pathway prediction. We also established the first database of type I modular PKSs, featuring a comprehensive annotation of available docking domains information in bacterial biosynthetic pathways.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The DDAP database is available at https:\/\/tylii.github.io\/ddap. The prediction algorithm DDAP is freely available on GitHub (https:\/\/github.com\/tylii\/ddap) and released under the MIT license.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz677","type":"journal-article","created":{"date-parts":[[2019,8,30]],"date-time":"2019-08-30T15:29:05Z","timestamp":1567178945000},"page":"942-944","source":"Crossref","is-referenced-by-count":10,"title":["DDAP: docking domain affinity and biosynthetic pathway prediction tool for type I polyketide synthases"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2559-184X","authenticated-orcid":false,"given":"Tingyang","family":"Li","sequence":"first","affiliation":[{"name":"Department of Computational Medicine and Bioinformatics , MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashootosh","family":"Tripathi","sequence":"additional","affiliation":[{"name":"Natural Products Discovery Core, Life Sciences Institute , MI, USA"},{"name":"Department of Medicinal Chemistry , MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengan","family":"Yu","sequence":"additional","affiliation":[{"name":"Natural Products Discovery Core, Life Sciences Institute , MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David H","family":"Sherman","sequence":"additional","affiliation":[{"name":"Natural Products Discovery Core, Life Sciences Institute , MI, USA"},{"name":"Department of Medicinal Chemistry , MI, USA"},{"name":"Department of Chemistry, Department of Microbiology and Immunology , MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arvind","family":"Rao","sequence":"additional","affiliation":[{"name":"Department of Computational Medicine and Bioinformatics , MI, USA"},{"name":"Department of Radiation Oncology, Michigan Institute for Data Science and Department of Biomedical Engineering, University of Michigan , Ann Arbor, MI, USA"},{"name":"Department of Electrical and Computer Engineering, Rice University , Houston, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2019,9,3]]},"reference":[{"key":"2023013110091917800_btz677-B1","doi-asserted-by":"crossref","first-page":"W36","DOI":"10.1093\/nar\/gkx319","article-title":"antiSMASH 4.0\u2014improvements in chemistry prediction and gene cluster boundary identification","volume":"45","author":"Blin","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023013110091917800_btz677-B2","doi-asserted-by":"crossref","first-page":"W81","DOI":"10.1093\/nar\/gkz310","article-title":"antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline","volume":"47","author":"Blin","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023013110091917800_btz677-B3","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1038\/nature13423","article-title":"Structure of a modular polyketide synthase","volume":"510","author":"Dutta","year":"2014","journal-title":"Nature"},{"key":"2023013110091917800_btz677-B4","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1126\/science.284.5413.482","article-title":"Dissecting and exploiting intermodular communication in polyketide synthases","volume":"284","author":"Gokhale","year":"1999","journal-title":"Science"},{"key":"2023013110091917800_btz677-B5","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/S1367-5931(99)00046-0","article-title":"Role of linkers in communication between protein modules","volume":"4","author":"Gokhale","year":"2000","journal-title":"Curr. 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