학술논문
Type 2‐low asthma phenotypes by integration of sputum transcriptomics and serum proteomics.
Document Type
Article
Author
Zounemat Kermani, Nazanin; Saqi, Mansoor; Agapow, Paul; Pavlidis, Stelios; Kuo, Chihhsi; Tan, Kai Sen; Mumby, Sharon; Sun, Kai; Loza, Matthew; Baribaud, Frederic; Sousa, Ana R.; Riley, John; Wheelock, Asa M.; Wheelock, Craig E.; De Meulder, Bertrand; Schofield, Jim; Sánchez‐Ovando, Stephany; Simpson, Jodie Louise; Baines, Katherine Joanne; Wark, Peter A.
Source
Subject
*PROTEOMICS
*SPUTUM
*ASTHMA
*SERUM
*TRANSCRIPTOMES
*PHENOTYPES
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Language
ISSN
0105-4538
Abstract
Keywords: asthma; bioinformatics; endotypes; precision medicine; systems biology EN asthma bioinformatics endotypes precision medicine systems biology 380 383 4 01/09/21 20210101 NES 210101 I To the Editor, i Asthma is a complex heterogeneous disease that presents with varying degrees of severity. We identified four optimal clusters (TAC*1, TAC*2, TAC*3a and TAC*3b) (Figure S3), in agreement with our previous clustering1 where TAC*3a and TAC*3b were combined. Asthma, bioinformatics, endotypes, precision medicine, systems biology. [Extracted from the article]