Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits

scientific article published on 14 August 2020

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1371/JOURNAL.PCBI.1008044
P932PMC publication ID7449405
P698PubMed publication ID32797044

P50authorHans HaunerQ21033707
Krina ZondervanQ21264229
Cecilia LindgrenQ30347705
Tim FraylingQ54627337
Christoffer NellåkerQ55296361
Sara PulitQ56356122
Craig A GlastonburyQ59570499
Katarina KosQ62933097
Hanieh YaghootkarQ76491920
Michelle HudsonQ87607025
Jenny C CensinQ88651311
Christian M BeckerQ89455030
Julius HoneckerQ92623973
Nilufer RahmiogluQ92826477
Andrew PittQ98471505
Melina ClaussnitzerQ114122479
P2093author name stringSamantha Laber
Emilie Pastel
Nicola L Beer
P2860cites workIPython: A System for Interactive Scientific ComputingQ24492861
CellProfiler: image analysis software for identifying and quantifying cell phenotypesQ24676898
CellProfiler 3.0: Next-generation image processing for biologyQ56395621
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P4510describes a project that usesscikit-learnQ1026367
CellProfilerQ5058134
scikit-imageQ22442795
Jupyter notebook fileQ70357595
P433issue8
P921main subjectmachine learningQ2539
adipocyteQ357519
P304page(s)e1008044
P577publication date2020-08-14
P1433published inPLOS Computational BiologyQ2635829
P1476titleMachine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits
P478volume16

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