Research Interests

Driving force behind my endeavors in science is the desire to better understand the creative potential of Nature. Common thread to my work in computational modeling is the attempt to provide abstract theoretical concepts and mathematical models with better physical foundations.

Molecular and higher-level organization

In order to understand how molecular and higher-level self-assembly and driving enable self-replication, inheritance, and ultimately chemical evolution, I have studied the thermodynamics and kinetics of self-assembling, self-replicating lipid aggregates,[1, 2] template-directed nucleic acid replicators,[3] as well as coupled container-metabolism-information systems (protocells).[4, 5, 6]

self-replicating oil droplet

Replication of a surfactant covered oil droplet, simulated in dissipative particle dynamics.[1]

  1. H. Fellermann and R. Solé. Minimal model of self-replicating nanocells: A physically embodied, information-free scenario. Philos. Trans. R. Soc. Ser. B, 2007
  2. B. Corominas-Murtra, H. Fellermann, R. Solé, S. Rasmussen. On the Interplay of Thermodynamics, Kinetics, and Information in Simple Replicator Systems. Proceedings of the 12th International Conference on the Synthesis and Simulation of Living Systems, 2010
  3. H. Fellermann and S. Rasmussen. On the Growth Rate of Non-Enzymatic Molecular Replicators Entropy, 2011
  4. H. Fellermann, S. Rasmussen, H.-J. Ziock, R. Solé. Life-cycle of a minimal protocell – a dissipative particle dynamics (DPD) study, Artif. Life, 2007
  5. H. Fellermann and S. Rasmussen. Physically Grounded Simulations of a Self-Replicating Chemical Agrgegate. Proceedings of the 12th International Conference on the Synthesis and Simulation of Living Systems, 2010
  6. H. Fellermann, B. Corominas-Murtra, R. Solé, S. Rasmussen. Thermodynamics and kinetics of protocells: toward a quantitative theory of early life. Proceedings of the European Conference of Complex Systems 2011

Origin of inheritable information

I am interested in the acquisition of information in chemical/ living systems through evolution. To this end, I am developing information measures that quantify the communication process between system and environment inherent to evolutionary selection and its breakdown of ergodicity. In conjunction with the above thermodynamic replicator analysis, this work will allow us to quantitatively study the energetics of information acquisition (e.g. in bits/joule) in living systems in various environments.

Molecular computation and construction

Information is not only processed during evolution, but also at the level of the individual chemical system, where chemical computation accounts for signal/response and autonomy. I am interested in unconventional computing approaches (chemical, membrane, DNA computing) and the analysis of their computational and constructive power. I am currently providing the calculus of membrane computing with a tighter physical foundation, in order to apply it in programmable microfluidic devices that manipulate DNA tagged cargo vesicles. This work attempts to integrate chemical computation and material production as it is manifested in living systems ("artificial subcellular matrix").

Computational method development

Complex chemical systems typically exhibit dynamics on a multitude of lengths and time scales. This requires multi-scale simulation techniques with consistent non-equilibrium thermodynamics. I am interested in coarse-graining and renormalization techniques and have contributed to method development by applying dimensional reduction techniques to particle based systems (dissipative particle dynamics),[7] and modular Boolean networks.[8] I have developed multi-scale simulation frameworks that map between spatially resolved and distribution based models in soft condensed matter physics and systems ecology. In future, I would like to further stretch the boundaries of computational modeling frameworks of multi-scale non-equilibrium systems.

coarse-graining of the dissipative particle dynamics method

Coarse-graining in the dissipative particle dynamics method. We have shown that interaction parameters in particle based methods are, contrary to previous claims, scale free.[7]

  1. R. Füchslin, H. Fellermann, A. Eriksson, and H.-J. Ziock, Coarse-graining and scaling in dissipative particle dynamics, J. Chem. Phys., 2009
  2. H. Fellermann, M. Davidich, Seeing the net for the nodes: coarse-graining modular Boolean networks, Santa Fe Institute Working paper. 2008

Despite the theoretical/conceptual nature of my interests, I am eager to scrutinize the validity of simulation results by calibration and verification with experimental data, to which end I am interested in standard and state-of-the-art data analysis and statistical inference techniques.