Solving Immunology?
Trends Immunol
; 38(2): 116-127, 2017 02.
Article
en En
| MEDLINE
| ID: mdl-27986392
ABSTRACT
Emergent responses of the immune system result from the integration of molecular and cellular networks over time and across multiple organs. High-content and high-throughput analysis technologies, concomitantly with data-driven and mechanistic modeling, hold promise for the systematic interrogation of these complex pathways. However, connecting genetic variation and molecular mechanisms to individual phenotypes and health outcomes has proven elusive. Gaps remain in data, and disagreements persist about the value of mechanistic modeling for immunology. Here, we present the perspectives that emerged from the National Institute of Allergy and Infectious Disease (NIAID) workshop 'Complex Systems Science, Modeling and Immunity' and subsequent discussions regarding the potential synergy of high-throughput data acquisition, data-driven modeling, and mechanistic modeling to define new mechanisms of immunological disease and to accelerate the translation of these insights into therapies.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Sistemas de Administración de Bases de Datos
/
Modelos Inmunológicos
/
Biología de Sistemas
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Sistema Inmunológico
/
Inmunidad
Límite:
Animals
/
Humans
Idioma:
En
Revista:
Trends Immunol
Asunto de la revista:
ALERGIA E IMUNOLOGIA
Año:
2017
Tipo del documento:
Article
País de afiliación:
Estados Unidos