Construction and evolution of immunity

Edition 2017

Complexity of the immune system

Contributed by Véronique Thomas-Vaslin

As a complex biological system, the immune system is an adaptive, highly diversified, robust and resilient system with emergent properties, such as anamnestic responses and regulation. The immune system is characterized by complexity at different levels: network organization through fluid cell populations with inter- and intra-cell signaling, lymphocyte receptor diversity, cell clonotype selection and competition at cell level, migration and interaction inside the immunological tissues and fluid dissemination through the organism, homeostatic regulation while rapid adaptation to a changing environment.

The immune system develops during the fetal life and organizes in relation with the mother immunity and microbiote that thus transmits its historicity. The genetic diversity of the antigenic receptors and the correct differentiation and renewal of lymphocytes insures during all the life a potential to react to any antigens that is kept through quiescent lymphocytes that remain in “standby”. Then, quiescent lymphocytes that perceive antigens are activated and involved collectively during immune responses, through various functions and communications.   This allows the cognition of the worldwide molecular diversity, including the eukaryote and prokaryote cells that compose our human “holobionte” organism. Innovative primary and memory adaptive immune responses arise in responses to the constant fluxes of molecular perturbations and alterations occurring throughout all our life. This immune protection insures that at the macroscopic level, organisms remain in healthy state, with resilience to immune perturbations and infections, efficiency for reproduction of species, including the protection of the fetus from immune system mother. Delicate networks and oscillations through regulations occur daily in the immune system and lymphoid organs. They continuously reproduce new diversified lymphocytes, provide a selection that kill more than 90% of the cells produced, to distribute and control functions of selected lymphocytes through the body and establish collaborative cell functions of immuno-surveillance.
Understanding the organization and regulation of this complex immune system  (but also disorganization, instability and aging) refers to transversal questions already mentioned for other complex systems such as other biological, social or ecological macro systems, with some peculiarities specific to the immune system as summarized below.

Transversal questions commons to other complex systems (specific to immune system):

-Study and modelling of adaptive multiscale system (the adaptive immune system)
-Integration of high-throughput multiscale and multiparametric data and metadata and sharing (data from transcriptome, proteome, but also cytome, repertome…)
-Computer or mathematical tools for exploration and formalisation (supervised and non supervised statistical modeling, mechanistic reconstruction of immune system behaviour)
-Theoretical reconstruction (data mining, multiscale analysis, representation of heterogeneous data, organisation of knowledge’s database describing the immune system around the lymphocyte level, from molecule to organism, data-driven and hypothesis-driven reconstruction
-Metamodels, multiformalism for reconstruction and visualization of dynamics, differentiation, and behaviour (mathematical & computer modelling for lymphocyte cell population dynamics, activation, regulation and selection processes; use of oriented object, graphical language based on state and transition diagrams, SMA, ontologies, for modelling the immune system…)
-Fluctuations, stability, variability, regulations at multiscale levels (Multilevel/Multiscale: organism, lymphoid tissues, lymphocyte populations, cellular and molecular lymphoid repertoires)
-Robustness/resilience (describe, predict and control immune system development & aging; resilience to perturbations, transition to immunopathologies (infection, autoimmunity, cancer…); immunotherapy/vaccination.
-Model the relationships between biodiversity, functioning and dynamics of the (eco)systems (diversity, stability / perturbation of immune repertoires and lymphocyte populations)
-Self organization, simulation of virtual landscapes (auto-organisation of cells in lymphoid organs and development, cell network and immune repertoire)
-Data mining: extraction, visualization of data and semantic and syntactic analysis of scientific literature requires artificial intelligence and automatic learning approaches (information extraction and visualization of immune literature with concepts specific to immune system according to  a given context)

Transversal questions commons to other complex systems Questions specific to the immune system
Study and modeling of adaptive multi-scale system The adaptive immune system
Integration of high-throughput multi-scale and multi-parametric data and metadata and sharing Biological generic data from transcriptome, proteome, but also cytome, repertome…
Computer or mathematical tools for exploration and formalization Supervised and non supervised statistical modeling, mechanistic reconstruction of immune system and lymphocyte behaviour
Theoretical reconstruction Multi-scale analysis, representation of heterogeneous data, organisation of knowledge’s database describing the immune system around the lymphocyte level, from molecule to organism, for data-driven and hypothesis-driven reconstruction
Metamodels, multi-formalism for reconstruction and visualization of dynamics, differentiation, and behaviour Mathematical & computer modelling for lymphocyte cell population dynamics, activation, regulation and selection processes; use of oriented object, graphical languages, SMA, ontologies, for modeling the multi-scale entities of the immune system…
Fluctuations, stability, variability, regulations at multi-scale levels Multi-level/Multi-scale: organism, lymphoid tissues, lymphocyte populations, cellular and molecular lymphoid repertoires
Robustness/resilience and relation to organization Behavior of immune system from development to aging; resilience to perturbations, transition to immunopathologies (infection, autoimmunity, cancer…); immunotherapy/vaccination
Model the relationships between biodiversity, functioning and dynamics of the (eco)systems Diversity, stability/perturbation of immune repertoires and lymphocyte populations
Self organization, simulation of virtual landscapes Auto-organization of cells in lymphoid organs and development, cell network and immune repertoire
Data mining, extraction, visualization of data and semantic and syntactic analysis of scientific literature requires artificial intelligence and automatic learning approaches Information extraction and visualization of immune literature with concepts specific to immune system,  according to  a given biological context

Table 1: Crossing transversal questions identified for the investigation of the complex systems with the questions specific to the immune system.

Challenges related to the complexity of the immune system

More than transversal question common to other complex systems, the immune system present some peculiarities that require particular investigations and modeling and represent new challenges to overcome.
1. Objective identification of immune system cell populations

2. Lymphocyte population dynamics & repertoire selection: Integration of multilevel/ multiscale data and dynamic modeling

3. Understanding resilience or instabilities to perturbations, immune dysfunction in order to improve immuno-intervention strategies

4. Extract, visualize and organise immunological knowledge from scientific immune literature

5. Contribute to global evaluation of complex systems and risk issue

6. Revisite the “immune system”: limits, definition, characteristics, functions and stability

7. Bio-inspired and artificial immune systems

8. Immune system and communication

9. From micro-ecosystems to social ecological developments, clinical and research impacts

1. Objective identification of immune system cell populations

Innate and adaptive immune system subpopulations are currently defined based on the revelation of a combination of cell surface or intracellular/nuclear molecules that the researcher has to define. Thus, the cell populations revealed by cell staining are largely dependent on the mixture and the number of chosen parameters (n) that will drive the number of subpopulations (2n). Techniques like Flow cytometry analysis allow quantification of several parameters from individual cells allowing characterizing cell size, structure, specific phenotype and function of millions of cells in a multi-dimensional way. However, analyses performed by manual gating inspect parameters 2 by 2 and do not reveal the complexity of the lymphocyte subpopulations that co-express several parameters.
The challenge is developing methods and software tools for current immunological analysis and automatic identification of cell subsets and their trajectory during their differentiation and their cell cyle. This allows objective investigation and identification of cell subpopulations that have certainly been ignored by immunologists, to identify variability/stability, resilience or perturbations among development/aging, through genetic backgrounds, and during the course of perturbations as immunopathologies or immunotherapies.

2. Lymphocyte population dynamics & repertoire selection: Integration of multilevel/ multiscale data and reconstruction of dynamic interactions

The most important feature of the immune system is the availability of a diverse cell repertoire and its selection constraints. Lymphocytes are produced from precursors in primary lymphoid organs that differentiate and somatically rearrange DNA variable genes composing a particular repertoire. T or B cell repertoires are thus collections of lymphocytes, each characterized by its antigen-specific receptor produced by random somatic rearrangements of V(D)J gene segments during lymphocyte differentiation, producing a potential repertoire of a quadrillion of TCR/Ig receptors about one thousand beyond the lymphocyte count in a single individual. Then, process of lymphocyte selection with high cell death or amplification of particular antigen specific clones represent a network of dynamical interactions conferring tolerance to avoid autoimmunity though retaining the potential to respond to a very large collection of antigens. Thus the dynamics of cell fluxes and turnover, cell selection process through division and cell death constraint the immune system to adapt a dynamic equilibrium according to programmed genetic variability’s and permanent antigen challenge. The rules governing the clonal selection processes and cell population dynamics stability or disturbance in immune pathologies and aging are far to be fully understood. Integration of high-throughput data describing qualitatively and quantitatively cell populations, repertoire diversity and gene expression should allow data mining, signature discovery and reconstruction of dynamics behaviours.

The challenge is the integration of multiscale data and metadata describing cell populations, cellular and molecular repertoires and gene expression across time, lymphoid organs and genetic background or various conditions describing physiological or pathological states or treatments. Organisation of knowledge’s using standardised database with ontologies and state transition diagram and influences should improve the organisation of data for data mining and dynamic computational modelling. Object-oriented computer modelling taking into account the levels of the “organism”, the “organs”, the “cell” and the “molecule” through various time scales, should improve the interoperability of mathematical and computer models already developed in the field, allowing also the direct intervention of the biologist to implement the models and suggest new experiments or treatments.

3. Understanding resilience or instabilities to perturbations, immune dysfunction in order to improve immuno-intervention strategies

Aging, immunopathologies as infectious, autoimmune or inflammatory diseases, cancer as well as immunotherapies, vaccination represent either internal instability or external aggressions that impact the stability and reactivity of the immune system at various biological levels (from molecules to organism). Genetic or environmental component alterations (antigens, infections, chemicals, nutriments…) or other biological instabilities (as in nervous, hormonal, metabolic systems…) and  disorganisation related to  aging can affect the organisation of immune system its dynamics and repertoires and turn the physiologic equilibrium to immuno-pathologies. The identification and quantification of variability and perturbations at these different levels and through time should allow understanding the resilience or instability of the system. Conversely, improving knowledge on the physiological or pathological dynamic behaviour of the immune system should also reveal keys for immuno-interventions.
The challenge is to connect and better integrate knowledge’s as a result of data mining and dynamic computer modelling and simulations of such perturbations. The resilience and homeostatic regulation of the system (steady state dynamic equilibrium) but also variability/fluctuation (according to genetic background, physiological development and aging) to pathological perturbations of the immune system should thus be investigated by multidisciplinary approaches. This requires the development of original biological, mathematical and computer modelling tools. This might allow to assess the quantity /quality of small perturbations at various scale levels that can impact /dys-balance the whole immune system equilibrium or on the contrary to estimate the maximal variability the system can endure without global perturbations at the organism level.

4. Extract, visualize and organise immunological knowledge from scientific immune literature__

The complexity of the immune system, related to biological multi-scale levels, but also of the data generated by multiple technologies, published in the form of unstructured text requires the development of innovative techniques of data and literature mining to enhance information retrieval, visualization of enormous quantities of data and organisation of knowledge.

The challenge is to develop data mining, text mining and machine learning methods to have a better understanding of the complexity of the immuno-physiome. Innovative data mining, semantic and syntactic analytical approaches should help define the concepts that have to be extracted and algorithms to automatically extracts the data with a maximum of accuracy.

5. Contribute to global evaluation of complex systems and risk issue

A global evaluation of the behaviour of complex systems should be undertaken under philosophical and scientific aspects. The behaviour of complex systems is related to their multi-scale organisation. While the immune system is related to micro-levels from molecule to organism, the biosphere is related to macro-levels from organisms to global environment, though social interactions, migration, ecosystems, climate and biosphere. The immune system represents a model of choice to evaluate the common properties of organisation and behaviour of such other complex systems at higher scale levels. Indeed data, simulations and predictions are difficult to establish for some systems. Organisation of systems results from the selection among diversities of only a small fraction of all potential possibilities, with an infinite combination of parameters. This contributes to selected dynamic equilibrium allowing the systems to resist perturbations trough time unless the resilience is disrupted.
The challenge is to provide a global analysis of common properties of complex multi-scale systems to understand the robustness and degree of resilience of systems selected on the basis of their organisation and risk of changes in the dynamic equilibrium. The notion of emergence and immergence have to be analysed to understand whether aging and evolution of a system and threshold effects are involved in the resilience of systems or could induce their disorganisation.

6. Revisiting the “immune system”: limits, definition, characteristics, functions and stability

Complex systems are often viewed as multi-scale, self-assembly, adaptive dynamic and cognitive networks of diverse interacting agents capable of sensing patterns with degenerative properties. In biology, links between entities and processes are insured at various scales. At the macroscopic level, the nervous system insures the cognition, perception and memory of “self”, through mental links and relations to macroscopic external environment, allowing to define ego as well as physical/somatic identity based on consciousness, memory and social interactions. Similarly, at the microscopic level, the immune system as a cognitive, diverse, dynamic, fluid and anamnestic system, sense the quality and quantity of microscopic patterns, either from body or environment. The immune system is thus at the interface of the dynamic symbiotic organisation of the individual (composed in adults as many prokaryotic than eukaryotic cells) and constantly senses its molecular and celllular environment, and its own components (idiotopes). This leads to individual cell signalling up to collective decision-making allowing for discrimination and memory of microscopic entities in a systemic way.

Biological and philosophical conceptual questions remain about the notion of organisation, organism, immune system, the perception of self, identity, memory, tolerance and resilience.

• Are there limits between the immune system, the organism and the environment?
• Has the immune system a role to define the identity of an organism?
• What are the major characteristics of an organisation and an organism?
• How do cognition, diversity, selection, memory and dominant tolerance contribute to the dynamic stability of the system and the resilience of the organism?
• How can we define the immune system? Is the term “immune”, with its etymologic origin meaning “exempt”, adequate according to current knowledge?

Responding to these challenges will improve global data exploration and understanding of the complexity of the immune system (Immuno-physiome) linked to other biological systems or to macro ecological/biosphere systems.

7. Bio-inspired and artificial immune systems

Knowledge’s assembled to understand, reconstruct, simulate and predict the complex multi-scale behaviour and resilience of the immune system dynamics in health, aging, diseases or treatments could be useful for the design of innovative artificial immune systems reproducing or inspired from the behaviour of the natural immune system. Thus, understanding this natural organisation, selected during the evolution of species and cells in organism, can help to design innovative evolutive artificial immune systems, and referring to the “war” metaphor to design the best “immuno-logistic” optimization. This could help understanding the characteristics of an organisation as a process and as a result, from organisms to societies and for the design of regulatory processes and security purposes.

The challenge is to overcome the conceptual and technical limitations to design self-organized artificial immune systems resilient to perturbations and able to preserve the identity and integrity of the organism or societies.

8. Immune system and communication

The immune system is inside the holobionte and poly-genomic organism, at the interface between eukaryote and prokaryote cells. This cognitive system makes the interface between the molecular world and cells, on the basis of dynamic communication. Deciphering the concept of cellular and molecular communication and signal transmission could be done at various levels: at horizontal level inside innate and adaptive, between cells, between organisms, and at vertical level from molecule to organism and up to social system.

The challenge is to model the rules that govern communication, the interactions, transmission and percolation up to emergence of patterns. Modeling the physiological communication and transmission of information could help understanding alterations resulting in pathologies and aging and to design therapeutic interventions to improve defective communication.

9. From micro-ecosystems to social ecological developments, clinical and research impacts

Cognitive systems like the immune system and the nervous system are involved in the perception, adaptation and memory of our microscopic to macroscopic social ecological environments that are constantly perturbed, and in the orientation of our individual and collective behavior. Indeed defective immune responses or altered regulations of the immune system have great impact on our health, and consequently on our decisions and social behavior.

Immuno-pathologies can potentially affect each individual, but also increase their frequency in the society as epidemic spreading and alter the health, the reproduction, activity and the longevity of individuals, with societal impact. On one side, in case of immuno-deficiencies, or inefficient responses of the immune system to rapidly control replicative microbes or tumors cells infections and tumors can progress. The role of vaccination is thus primordial to accelerate and amplify the immune response to control the infection and prevent transmission to other individuals. On the other side, in case of defective control and feedback regulations of the immune system, the uncontrolled reactivity against body components, like in autoimmune and inflammatory diseases, or the defective orientation of immune responses or cell population dynamics could also occur and lead to allergies, metabolic diseases, fetal abortions, tumor growth.

Aging of the immune system and of the human population can moreover alter both sides with delayed or defectives process: the internal cell metabolism, reproduction and repair inside adaptive lymphocytes and innate cells; the inter-cell communication/activation/functions/distribution and altered feedback loops through various biological levels.

Perturbations in our environment, lifestyle and human industrialization since the last century, has allowed for the rapid change of the immune context, as detected by lymphocytes. The occurrence of some 133 millions new chemicals with more than 10, 000 new substances created each day should be considered. The deviation of immune regulations and functions related to excessive hygiene and deprivation of the co-evolutive microbiote (like in caesarean) or wide usage of antibiotics could alter the cross-talk between the immune system, the microbiote and the antigenic world and lead to emergence of new pathologies like allergies and metabolic disorders.

Human interventions by prevention, biotherapies, chemotherapies, chronobiology can try to manipulate and control immune responses. One way is to improve and accelerate a specific immune response by vaccination, in order to gain the race against selected replicative pathogenic microbes or tumors. Another way is to induce specific tolerance against some body components, while preserving other potential beneficial responses with specific immuno-regulation. This is indeed an alternative to global immunosuppression that non-specifically decreases the immuno-competence and increases the risk of occurrence of infections or tumors.

The challenge is to integrate interactions from the micro-ecosystem that includes the immune system and the microbiote of each individual, up to the social-ecological development of humans that include personal and societal health, nutrition, chronobiology, stress, industrial and technological developments that impact back on immune system by immergence. Information should be given to the society at any level, from child to elderly and also researchers in multi-disciplinary domains, like mathematicians and computer scientists involved in modeling of immune system and ecosystems. Indeed people should have information’s about the complex cognitive immune system behavior that keep the trace of the molecular and cell history of our body, those cells react at any instant to molecular perturbations in its environment to preserve by emergence the individual but also eco-socio system viability. The consciousness that in each individual our immune system is facing our world according to its context that depends on hygiene, food, micro-flora, chemicals, antibiotics, therapies, aging and stress could change the way understanding the traces that the immune system lives in the body up to social systems. Moreover, immuno-clinical investigations and immunotherapies are developing and open new avenues for prevention. Risk perception and its evaluation at global levels of organization, for the resilience of our living systems is also of importance.

Conclusions

Identifying theoretical and methodological questions related to the complexity of the natural and artificial immune systems will help to structure new ideas and collaborative work across complex systems. Responding to these challenges will improve the global data exploration, the emergence of new concepts and understanding of the immune system linked to other biological systems or to macro ecological/biosphere systems. The ImmunoComplexiT network  from the RNSC  http://immunocomplexit.net/is currently  questionning and modeling the complexity  of the immune system.

Some references

Abi Haidar, A., Six, A., Ganascia, J.-G., & Thomas-Vaslin, V. (2013). The Artificial Immune Systems Domain: Identifying Progress and Main Contributors Using Publication and Co-Authorship Analyses (Vol. 12).

Bellier, B., Six, A., Thomas-Vaslin, V., & Klatzmann, D. (2011). Predicting immune responses to viral vectors and transgenes in gene therapy and vaccination : the coming of systems biology. Clinibook.

Bellier, B., Six, A., Thomas-Vaslin, V., & Klatzmann, D. (2013). Systems Immunology, Novel Evaluation of Vaccine. In W. Dubitzky, O. Wolkenhauer, K.-H. Cho, & H. Yokota (Eds.), Encyclopedia of Systems Biology (pp. 2089-2092 ): Springer New York.

Bersini, H., Klatzmann, D., Six, A., & Thomas-Vaslin, V. (2012). State-transition diagrams for biologists. PLoS ONE, 7(7), e41165. doi:10.1371/journal.pone.0041165

Jacquemart, F., & Thomas-Vaslin, V. (2016). L’évaluation globale des technologies. In B. Bocquet (Ed.), La Fièvre de l’évaluation (pp. 196): Presses Universitaires du Septentrion.

Jacquemart, F., Thomas-Vaslin, V., & Coutellec, L. (2016). Pour une évaluation globale des OGM : Des perspectives épistémologiques renouvelées pour l’analyse des risques.Retrieved from https://hal.archives-ouvertes.fr/hal-01298382

Lavelle, C., Berry, H., Beslon, G., Ginelli, F., Giavitto, J., Kapoula, Z., . . . Bourgine, P. (2008). From molecules to organisms: towards multiscale integrated models of biological systems. Theoretical Biology Insights, 1, 13-22.

McEwan, C., Bersini, H., Klatzmann, D., Thomas-Vaslin, V., & Six, A. (2011). A computational technique to scale mathematical models towards complex heterogeneous systems: Luniver press. ISBN.

Six, A., Bellier, B., Thomas-Vaslin, V., & Klatzmann, D. (2012). Systems biology in vaccine design. Microb Biotechnol, 5(2), 295-304. doi:10.1111/j.1751-7915.2011.00321.x

Six, A., Mariotti-Ferrandiz, M. E., Chaara, W., Magadan, S., Pham, H. P., Lefranc, M. P., . . . Boudinot, P. (2013). The Past, Present, and Future of Immune Repertoire Biology – The Rise of Next-Generation Repertoire Analysis. Front Immunol, 4, 413. doi:10.3389/fimmu.2013.00413

Thomas-Vaslin, V. (2014a). A complex immunological idiotypic network for maintenance of tolerance. Front Immunol, 5, 369. doi:10.3389/fimmu.2014.00369

Thomas-Vaslin, V. (2014b). Evaluation de la résilience et des perturbations des systèmes complexes. La lettre de l’inSHS du CNRS. Retrieved from http://www.cnrs.fr/inshs/Lettres-information-INSHS/lettre_infoinshs_32.pdf

Thomas-Vaslin, V. (2015). Complexité multi-échelle du système immunitaire: Evolution, du chaos aux fractales. In E. Matériologiques (Ed.), Le vivant critique et chaotique (pp. 333). Paris.

Thomas-Vaslin, V. (2016, sep 2015). Understanding and modelling the complexity of the immune system. Paper presented at the First Complex Systems Digital Campus World E-Conference 2015, Tempe, United States.

Thomas-Vaslin, V. (2017a). Le rôle des traces dans le système immunitaire : des anticorps au corps (B. Galinon-Mélénec Ed. Paris CNRS éditions ed. Vol. 4).

Thomas-Vaslin, V. (2017b). Questionnements et connaissance de la complexité. In E. Matériologiques (Ed.), Qu’est ce que la science… pour vous? Textes rassemblés par Marc Silberstein (pp. 251-256). Paris.

Thomas-Vaslin, V. (2017). Understanding and Modeling the Complexity of the Immune System. In P. Bourgine, P. Collet, & P. Parrend (Eds.), First Complex Systems Digital Campus World E-Conference 2015 (pp. 261-270). Cham: Springer International Publishing.

Thomas-Vaslin, V., Altes, H. K., de Boer, R. J., & Klatzmann, D. (2008). Comprehensive assessment and mathematical modeling of T cell population dynamics and homeostasis. J Immunol, 180(4), 2240-2250.

Thomas-Vaslin, V., & Jacquemart, F. (Producer). (2016). Approche de la résilience et perturbations des systèmes complexes par une évaluation globale. Congrès mondial pour la pensée complexe: Les défis d’un monde globalisé; reseau-canope.fr/congres-mondial-pour-la-pensee-complexe/pensee-complexe.html#bandeauPtf. [article] Retrieved from https://www.reseau-canope.fr/fileadmin/user_upload/Projets/pensee_complexe/thomas_vaslin_jacquemart_approche_resilience_perturbations_systemes_complexes.pdf

Thomas-Vaslin, V., Six, A., Bellier, B., & Klatzmann, D. (2013). Lymphocyte Dynamics and Repertoires, Biological Methods. In W. Dubitzky, O. Wolkenhauer, K.-H. Cho, & H. Yokota (Eds.), Encyclopedia of Systems Biology (pp. 1145-1149): Springer New York.

Thomas-Vaslin, V., Six, A., Bellier, B., & Klatzmann, D. (2013). Lymphocytes dynamics and repertoires, modeling. In W. O. Dubitzky W (Ed.), Encyclopedia of Systems Biology (pp. 1149-1152): Springer, Heidelberg New York.

Thomas-Vaslin, V., Six, A., Pham, H. P., Dansokho, C., Chaara, W., Gouritin, B., . . . Klatzmann, D. (2012). Immunodepression & Immunosuppression during aging. In M. B. Portela (Ed.), Immunosuppression (pp. 125-146). Brazil: InTech open acces publisher.

Vibert, J., & Thomas-Vaslin, V. (2017). Modelling T Cell Proliferation: Dynamics Heterogeneity, Depending on Cell Differentiation, Age, and Genetic Background. PLoS Comput Biol, 13 (3), e1005417. doi:10.1371

Read more…

CS-CD 2015

http://cs-dc-15.org/e-tracks/organisms/#cognitive-immune-sys

http://cs-dc-15.org/papers/organisms/cognitive-immune-sys/understanding-and-modelling-the-complexity-of-the-immune-system/

ImmunocomplexiT network http://immunocomplexit.net/

 

 

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