Portal:Complex Systems Digital Campus/From Molecules to Organisms and Ecosystems e-Department

= From Molecules to Organisms and Ecosystems e-Department =

Description
The physiome is the multi-level model of an organism from its birth to its death. The physiological functions of a multicellular organism result from the integration of cells, tissues and organ properties in the context of the whole organism interacting with its environment. A complex system approach of physiological functions should lead to an iterated cycle combining relevant measurements and experimentation, modeling and simulation. Such a goal requires building multimodal investigation devices for simultaneous in vivo recording at different spatial and temporal scales of relevant parameters as well as designing theoretical methods and tools for appropriate modeling and computer simulation. Biological systems are multiscaled both in time (typically femtoseconds in chemical reactions, seconds in metabolism processes, days to months in cells, years in an living organism) and space (typically nanometers for molecular structures, micrometers for supramolecular assemblies, organelles and cells, centimeters for tissues and organs, meters for organisms). Finding the pertinent space & time scales for experimentation and modeling is a major issue. As a result of evolutionary opportunism (biological tinkering), multiscale space & time correlation is not a priori given. Classical approaches (biochemistry, cellular and molecular biology, behavioral and cognitive studies, etc.) usually have their “preferred” scale by default, mainly due to the fact that protocols and experiments are often designed to work only at a specific scale. This makes back and forth interactions between different scales in observations, experimentations, models and simulations a very exciting transdisciplinary challenge. Variation of individual physiomes around the prototypical one requires characterizing and measuring variability and fluctuations at the molecular, single cell, cell population and physiological levels. The origin, time and space scales, control and functional significance of fluctuations in biological systems are largely unknown. Their functional significance might be approached through their multiscale transmission and possible amplification, reduction/damping or role in mediating bifurcations. Ultimately, the personalized health will be based on the knowledge of the individual physiome of everyone. From organisms to ecosystems: Defined as the close association of an abiotic environment and a collection of living organisms, an ecosystem, essentially, is characterized by a great number of physicochemical factors and biological entities which interact with each other. The multiplicity and diversity of these interactions as well as the fact that they involve a vast range of levels of organization of Life and a broad spectrum of space and temporal scales justify the expression of “ecosystemic complexity”? Moreover, the ecosystems, be they natural, managed or artificial, are subjected to “perturbations”? (e.g. natural hazards or biotic and abiotic stresses) and deliver many and diversified commercial and non-commercial products and “services”? To identify, qualify, formalize and quantify these modes of disturbance and these products and services define research topics that refer, according to cases, to the sciences of the universe and/or the social sciences. To account for this ecosystemic complexity, to understand the resilience of the ecological processes and to open the possibility of ecosystem management and control, require to articulate various strategies: for reconstructing the spatial and temporal dynamics, starting from observations and from increasingly instrumented experiments; for theoretically and experimentally identifying the retroactive mechanisms and the emergence phenomena; for modeling and validating these models.

Board

 * Nadine Peyriéras (chair)
 * Jacques Demongeot (co-chair)

Bibliography & resources
the roadmaps

[|the e-sessions of CS-DC-15.org]

e-laboratories

 * e-Laboratory on Machine Learning in Medicine
 * e-Laboratory on Embryome Digital Campus
 * e-Laboratory on Open Systems Natural Resource Management
 * e-Laboratory : Open Systems Exploration for Ecosystems Leveraging

Board

 * (name) (chair | email)
 * name, name, ...

Board

 * (name) (chair | email)
 * name, name, ...

Keywords
A

adaptation (1) adaptive processes (1) antigens (1) attractive low-dimensional manifolds (1)

B

bursting (1)

C

carbohydrate storage (1) carbon partitoning (1) cell decision-making (1) cell llineage (1) cellular signaling (1) coarse behavior (1) complex systems (10) Computer Sciences (2)

D data fusion (1) development (3) Digital Health (1) dioxin (1) disease resistance (1) E ectopic activity (1) embryo (1) Endocrine system (1) endurance exercise (1) environment (1) equation-free analysis (1) evo-devo (1) evolution (3) excitability (1) exposome (1) exposure biology (1) exposure science (1) F fish (1) forest dynamics (1) fruit growth (1) functional metagenomics (1) functional-structural plant model (1) functional-strutural modeling (1) G gene expression (1) genetics (3) graphical Gaussian Models (1) gut microbiota (1) H hazard assessment. (1) Host microbes interaction (1) Human Hazard (1) I immune response (1) immune system (1) immunologie (1) in silico experiments (1) in vivo imaging (1) Infectious disease (1) infectivity (1) information theory (2) intestinal epithelium (1) L Life science (1) livestock (1) M Mechanism (1) memory (1) Metagenomics (1) Modelling (2) modular plant architecture (1) molecular biology (1) molecular dynamics (1) Multiscale modeling (1) multiscale models (1) N neural modeling (1) neural propagation (1) neurons (1) noise (1) O omic data (1) organogenesis (2) oscillations (1) P pain (1) pathology (1) Patient Engagement (1) pattern recognition (1) phenomenological reconstruction (1) Plant (1) Plant biology (2) Population Health (1) Precision Medicine (1) preimplantation (1) Public Health (1) R rabbit (1) Regulation (1) repertoire diversity (1) resource acquisition and partitioning (1) Root architecture (1) root growth (1) S Self-organization (4) shoot growth (1) Signal processing (1) smart sensors (1) stand structure (1) Systems biology (1) systems toxicology (1) T tolerance (1) toxicity (1) toxicology (3) trauma (1) tree architecture (1) V Virtual tissue (1)