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DESCRIBE <http://purl.uniprot.org/SHA-384/1F450F002CAB7F33456A030A06F5EB635976149D3FFAD92B66AD18F7187088A06508EA28EE264C2C952536615DD1D4D2>
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http://purl.uniprot.org/SHA-384/1F450F002CAB7F33456A030A06F5EB635976149D3FFAD92B66AD18F7187088A06508EA28EE264C2C952536615DD1D4D2
http://www.w3.org/1999/02/22-rdf-syntax-ns#type
http://purl.uniprot.org/core/Annotation
http://purl.uniprot.org/SHA-384/1F450F002CAB7F33456A030A06F5EB635976149D3FFAD92B66AD18F7187088A06508EA28EE264C2C952536615DD1D4D2
http://www.w3.org/2000/01/rdf-schema#comment
"MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting."
xsd:string
http://purl.uniprot.org/uniprot/#_0F54C64C2E50EA657E0CFC51FE251A5D37D3F70592ADC0091B69DC445F3B62E3A6339E9A4226D011BCEF0B9E48054B28
http://www.w3.org/1999/02/22-rdf-syntax-ns#subject
http://purl.uniprot.org/SHA-384/1F450F002CAB7F33456A030A06F5EB635976149D3FFAD92B66AD18F7187088A06508EA28EE264C2C952536615DD1D4D2
http://purl.uniprot.org/uniprot/Q0QER2
http://purl.uniprot.org/core/mappedAnnotation
http://purl.uniprot.org/SHA-384/1F450F002CAB7F33456A030A06F5EB635976149D3FFAD92B66AD18F7187088A06508EA28EE264C2C952536615DD1D4D2
http://purl.uniprot.org/uniprot/#_Q0QER2-mappedCitation-33121211
http://purl.uniprot.org/core/mappedAnnotation
http://purl.uniprot.org/SHA-384/1F450F002CAB7F33456A030A06F5EB635976149D3FFAD92B66AD18F7187088A06508EA28EE264C2C952536615DD1D4D2