FRINK Linked Data Fragments server

Matches in Wikidata for { <http://www.wikidata.org/entity/Q47304377> ?p ?o ?g. }

• Q47304377 description "2017 nî lūn-bûn" @default.
• Q47304377 description "2017年の論文" @default.
• Q47304377 description "2017年学术文章" @default.
• Q47304377 description "2017年学术文章" @default.
• Q47304377 description "2017年学术文章" @default.
• Q47304377 description "2017年学术文章" @default.
• Q47304377 description "2017年学术文章" @default.
• Q47304377 description "2017年学术文章" @default.
• Q47304377 description "2017年學術文章" @default.
• Q47304377 description "2017年學術文章" @default.
• Q47304377 description "2017年學術文章" @default.
• Q47304377 description "2017年學術文章" @default.
• Q47304377 description "2017年學術文章" @default.
• Q47304377 description "2017년 논문" @default.
• Q47304377 description "article científic" @default.
• Q47304377 description "article scientific" @default.
• Q47304377 description "article scientifique" @default.
• Q47304377 description "articol științific" @default.
• Q47304377 description "articolo scientifico" @default.
• Q47304377 description "artigo científico" @default.
• Q47304377 description "artigo científico" @default.
• Q47304377 description "artigo científico" @default.
• Q47304377 description "artikel ilmiah" @default.
• Q47304377 description "artikull shkencor" @default.
• Q47304377 description "artikulong pang-agham" @default.
• Q47304377 description "artykuł naukowy" @default.
• Q47304377 description "artículo científico publicado en 2017" @default.
• Q47304377 description "artículu científicu" @default.
• Q47304377 description "bilimsel makale" @default.
• Q47304377 description "bài báo khoa học" @default.
• Q47304377 description "naučni članak" @default.
• Q47304377 description "scienca artikolo" @default.
• Q47304377 description "scientific article published on 27 November 2017" @default.
• Q47304377 description "scientific article published on 27 November 2017" @default.
• Q47304377 description "scientific article published on 27 November 2017" @default.
• Q47304377 description "teaduslik artikkel" @default.
• Q47304377 description "tieteellinen artikkeli" @default.
• Q47304377 description "tudományos cikk" @default.
• Q47304377 description "vedecký článok" @default.
• Q47304377 description "vetenskaplig artikel" @default.
• Q47304377 description "videnskabelig artikel" @default.
• Q47304377 description "vitenskapelig artikkel" @default.
• Q47304377 description "vitskapeleg artikkel" @default.
• Q47304377 description "vědecký článek" @default.
• Q47304377 description "wetenschappelijk artikel" @default.
• Q47304377 description "wissenschaftlicher Artikel" @default.
• Q47304377 description "επιστημονικό άρθρο" @default.
• Q47304377 description "мақолаи илмӣ" @default.
• Q47304377 description "наукова стаття, опублікована в листопаді 2017" @default.
• Q47304377 description "научна статия" @default.
• Q47304377 description "научная статья" @default.
• Q47304377 description "научни чланак" @default.
• Q47304377 description "научни чланак" @default.
• Q47304377 description "מאמר מדעי" @default.
• Q47304377 description "مقالة علمية نشرت في 27 نوفمبر 2017" @default.
• Q47304377 description "২৭ নভেম্বর ২০১৭-এ প্রকাশিত বৈজ্ঞানিক নিবন্ধ" @default.
• Q47304377 description "บทความทางวิทยาศาสตร์" @default.
• Q47304377 description "სამეცნიერო სტატია" @default.
• Q47304377 name "Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach." @default.
• Q47304377 name "Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach." @default.
• Q47304377 type Item @default.
• Q47304377 label "Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach." @default.
• Q47304377 label "Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach." @default.
• Q47304377 prefLabel "Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach." @default.
• Q47304377 prefLabel "Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach." @default.
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