Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response
The Immune System is, together with Central Nervous System, one of the most important and complex unit of our organism. Despite great advances in recent years that shed light on its understanding and in the unraveling of key mechanisms behind its functions, there are still many areas of the Immune S...
| Main Authors: | , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Springer-Verlag
2016
|
| Online Access: | http://hdl.handle.net/1721.1/101287 |
| _version_ | 1811080118306603008 |
|---|---|
| author | Stracquadanio, Giovanni Umeton, Renato Costanza, Jole Annibali, Viviana Mechelli, Rosella Pavone, Mario Zammataro, Luca Nicosia, Giuseppe |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Stracquadanio, Giovanni Umeton, Renato Costanza, Jole Annibali, Viviana Mechelli, Rosella Pavone, Mario Zammataro, Luca Nicosia, Giuseppe |
| author_sort | Stracquadanio, Giovanni |
| collection | MIT |
| description | The Immune System is, together with Central Nervous System, one of the most important and complex unit of our organism. Despite great advances in recent years that shed light on its understanding and in the unraveling of key mechanisms behind its functions, there are still many areas of the Immune System that remain object of active research. The development of in-silico models, bridged with proper biological considerations, have recently improved the understanding of important complex systems [1,2]. In this paper, after introducing major role players and principal functions of the mammalian Immune System, we present two computational approaches to its modeling; i.e., two in-silico Immune Systems. (i) A large-scale model, with a complexity of representation of 10[superscript 6] − 10[superscript 8] cells (e.g., APC, T, B and Plasma cells) and molecules (e.g., immunocomplexes), is here presented, and its evolution in time is shown to be mimicking an important region of a real immune response. (ii) Additionally, a viral infection model, stochastic and light-weight, is here presented as well: its seamless design from biological considerations, its modularity and its fast simulation times are strength points when compared to (i). Finally we report, with the intent of moving towards the virtual lymph note, a cost-benefits comparison among Immune System models presented in this paper. |
| first_indexed | 2024-09-23T11:26:07Z |
| format | Article |
| id | mit-1721.1/101287 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:26:07Z |
| publishDate | 2016 |
| publisher | Springer-Verlag |
| record_format | dspace |
| spelling | mit-1721.1/1012872022-10-01T03:37:19Z Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response Stracquadanio, Giovanni Umeton, Renato Costanza, Jole Annibali, Viviana Mechelli, Rosella Pavone, Mario Zammataro, Luca Nicosia, Giuseppe Massachusetts Institute of Technology. Department of Biological Engineering Umeton, Renato The Immune System is, together with Central Nervous System, one of the most important and complex unit of our organism. Despite great advances in recent years that shed light on its understanding and in the unraveling of key mechanisms behind its functions, there are still many areas of the Immune System that remain object of active research. The development of in-silico models, bridged with proper biological considerations, have recently improved the understanding of important complex systems [1,2]. In this paper, after introducing major role players and principal functions of the mammalian Immune System, we present two computational approaches to its modeling; i.e., two in-silico Immune Systems. (i) A large-scale model, with a complexity of representation of 10[superscript 6] − 10[superscript 8] cells (e.g., APC, T, B and Plasma cells) and molecules (e.g., immunocomplexes), is here presented, and its evolution in time is shown to be mimicking an important region of a real immune response. (ii) Additionally, a viral infection model, stochastic and light-weight, is here presented as well: its seamless design from biological considerations, its modularity and its fast simulation times are strength points when compared to (i). Finally we report, with the intent of moving towards the virtual lymph note, a cost-benefits comparison among Immune System models presented in this paper. 2016-02-26T03:12:24Z 2016-02-26T03:12:24Z 2011 Article http://purl.org/eprint/type/BookItem 978-3-642-22370-9 978-3-642-22371-6 0302-9743 1611-3349 http://hdl.handle.net/1721.1/101287 Stracquadanio, Giovanni, Renato Umeton, Jole Costanza, Viviana Annibali, Rosella Mechelli, Mario Pavone, Luca Zammataro, and Giuseppe Nicosia. “Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response.” Artificial Immune Systems (2011): 15–29. en_US http://dx.doi.org/10.1007/978-3-642-22371-6_2 Artificial Immune Systems Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Springer-Verlag Umeton |
| spellingShingle | Stracquadanio, Giovanni Umeton, Renato Costanza, Jole Annibali, Viviana Mechelli, Rosella Pavone, Mario Zammataro, Luca Nicosia, Giuseppe Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response |
| title | Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response |
| title_full | Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response |
| title_fullStr | Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response |
| title_full_unstemmed | Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response |
| title_short | Large Scale Agent-Based Modeling of the Humoral and Cellular Immune Response |
| title_sort | large scale agent based modeling of the humoral and cellular immune response |
| url | http://hdl.handle.net/1721.1/101287 |
| work_keys_str_mv | AT stracquadaniogiovanni largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse AT umetonrenato largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse AT costanzajole largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse AT annibaliviviana largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse AT mechellirosella largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse AT pavonemario largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse AT zammataroluca largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse AT nicosiagiuseppe largescaleagentbasedmodelingofthehumoralandcellularimmuneresponse |