Potential disease-associated proteins predicted for asthma, eczema and rhinitis.
- Daniel Aguilar (45107)
- Mariona Pinart (242789)
- Gerard H. Koppelman (153163)
- Yvan Saeys (3781)
- Martijn C. Nawijn (285064)
- Dirkje S. Postma (101740)
- Mübeccel Akdis (733539)
- Charles Auffray (782)
- Stéphane Ballereau (4100119)
- Marta Benet (188966)
- Judith García-Aymerich (4100116)
- Juan Ramón González (23801)
- Stefano Guerra (333552)
- Thomas Keil (177240)
- Manolis Kogevinas (135763)
- Bart Lambrecht (341720)
- Nathanael Lemonnier (4100110)
- Erik Melen (4100113)
- Jordi Sunyer (59833)
- Rudolf Valenta (186284)
- Sergi Valverde (402461)
- Magnus Wickman (642820)
- Jean Bousquet (20909)
- Baldo Oliva (34524)
- Josep M. Antó (489697)
Publication date
June 2017
DOIAbstract
<p>NetZcore prediction scores are shown as <i>z</i>-scores. Proteins are ranked according to their average <i>z</i>-score for all diseases. Empty cell: the protein was not predicted to be associated with the disease with <i>z</i>-score > 2.31 (corresponding to <i>P</i> < 0.01). <i>Exp</i>: the protein is experimentally known to be associated to the disease. This table only shows the 30 top-scoring proteins that were found to be associated to more than one disease. The complete list is available in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179125#pone.0179125.s023" target="_blank">S12 Table</a>.</p
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