Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches.
Semin Immunol
; 25(3): 193-200, 2013 Oct 31.
Article
en En
| MEDLINE
| ID: mdl-23375135
ABSTRACT
Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Enfermedades Autoinmunes
/
Virosis
/
Biología de Sistemas
/
Alergia e Inmunología
/
Sistema Inmunológico
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Semin Immunol
Asunto de la revista:
ALERGIA E IMUNOLOGIA
Año:
2013
Tipo del documento:
Article