. . . . . . . "[Artificial neural networks with exhaustive search for all marker combinations revealed that markers FoxP3, Nfat-C2, IL-16 and GATA-3 distinguished patients with persisting CMA most accurately from other study groups.]. Sentence from MEDLINE/PubMed, a database of the U.S. National Library of Medicine."@en . . . . . "2017-02-19"^^ . . "Gene-disease associations inferred from text-mining the literature."@en . "DisGeNET evidence - LITERATURE"@en . "2017-10-17T13:12:55+02:00"^^ . . . . . . . . . . . "v5.0.0.0" . "v5.0.0" .