Agent-based modeling of the immune system: NetLogo, a promising framework

BioMed Research International

Volumn 2014, Issue , 2014, Pages

  Chiacchio, Ferdinando ^a   Pennisi, Marzio ^a   Russo, Giulia ^a   Motta, Santo ^a   Pappalardo, Francesco ^a  

^a UNIVERSITY OF CATANIA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ENDOTOXIN; GAP JUNCTION PROTEIN; TOLL LIKE RECEPTOR 4; VIRUS ANTIGEN;

ADAPTIVE IMMUNITY; AGENT BASED MODEL; ASPERGILLUS FUMIGATUS; CANDIDA ALBICANS; COMPUTER LANGUAGE; COMPUTER MODEL; CRYPTOCOCCUS NEOFORMANS; EDUCATION; FIBROSIS; FUNGAL VIRULENCE; FUNGUS SPORE; GAP JUNCTION; GENETIC HETEROGENEITY; HUMAN; HUMAN PAPILLOMAVIRUS TYPE 16; IMMUNE RESPONSE; IMMUNE SYSTEM; INFECTION; INFLAMMATION; INNATE IMMUNITY; LEUKOCYTE; MATHEMATICAL MODEL; MICROVASCULATURE; MULTIPLE SCLEROSIS; NETLOGO; NONHUMAN; PROTOZOON; REGULATORY T LYMPHOCYTE; REVIEW; SIGNAL TRANSDUCTION; SIMULATION; SOLID TUMOR; TUMOR GROWTH; TUMOR IMMUNOLOGY; WART VIRUS; BIOLOGICAL MODEL; IMMUNOLOGY; NEOPLASM; PHYSIOLOGY;

HUMANS; IMMUNE SYSTEM; MODELS, IMMUNOLOGICAL; NEOPLASMS; PROGRAMMING LANGUAGES;

EID: 84901342913     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2014/907171     Document Type: Review

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