Targeted experiment design using the posterior predictive distribution

Abstract only

Simulated evolution of mass conserving reaction networks

With the rise of systems biology, the systematic analysis and construction of behavioral mechanisms in both natural and artificial biochemical networks has become a vital part of understanding and predicting the inner workings of intracellular signaling networks. As a modeling platform, artificial chemistries are commonly adopted to study and construct artificial reaction network motifs that exhibit complex computational behaviors. Here, we present a genetic algorithm to evolve networks that can compute elementary mathematical functions by transforming initial input molecules into the steady state concentrations of output molecules. Morespecifically, the proposed algorithm implicitly guarantees mass conservation through an atom based description of the molecules and reaction networks. We discuss the adopted approach for the artificial evolution of these chemical networks, evolve networks to compute the square root function. Finally,we provide an extensive deterministic and stochastic analysis of a core square root network motif present in these resulting networks, confirming that the motif is indeed capable of computing the square root function

Multiple functionalities of biochemical reaction networks

We consider a biological cell as a highly nterconnected network of chemical reactions, which is constituted of a large number of semi-autonomous functional modules. Depending on the global state of the network, the separate functional modules may display qualitatively different behavior. As an example, we study a conceptual network of phosphorylation cycles, for which the steady-state concentration of an output compound depends on the concentrations of two input enzymes. We show that the input-output relation depends on the expression of the proteins in the network. Hence changes in protein expression, due to changes in the global regulatory network of the cell, can change the functionality of the module. In this specific example, changed expression of two proteins is sufficient to switch between the functionalities of various logical gates

Indirect osteoblast-osteoclast coupling through mechanics explains elevated osteoblastic bone formation as a response to increased osteoclastic activity

Paper 026

Molecular dynamics study of vesicle deformation mechanisms

Lipid bilayer membranes are known to form various structures like large sheets or vesicles. When both bilayer leaflets have equal composition, membranes preferentially form flat sheets or spherical vesicles. However, vesicles with a wide variety of shapes, including ellipsoids, discoids, pear-shaped, cup-shaped and budded vesicles, have been shown experimentally. Such shapes were predicted theoretically from energy minimization of continuous sheets as well. We show, using coarse-grained molecular dynamics simulations, how relatively small asymmetry in composition between the two leaflets may result in spontaneously curved bilayers and all these vesicle shapes. Three types of bilayer asymmetry are considered. Firstly, the situation where the headgroup-solvent interaction and thus the lipid packing alters due to a change in pH or ion-concentration of the vesicle interior/exterior (A). Secondly, where asymmetry arises from phase separation of two lipid types (B). And thirdly, where asymmetry arises from growth of one of the bilayer leaflets by incorporation of additional lipids from the solvent (C)

Blue light phototherapy for Psoriasis from a systems biology perspective

This work analyses the effect of UV-free blue light (BL) irradiation of the skin using mathematical modelling. Prior research has shown that blue light reduces the proliferation of keratinocytes by inducing their differentiation, and causes apoptosis of lymphocytes. The effects of blue light on these cells make it an attractive phototherapy alternative for inflammatory skin conditions, such as psoriasis. Nevertheless, the exact process by which BL affects these cells is not fully understood. A modelling approach may give further insight to understanding how BL irradiation of psoriatic skin leads to the control of the disease. However, no mathematical model is available describing this phenomenon. Two deterministic models were therefore made to describe the epidermal kinetics and interaction between keratinocytes and lymphocytes under the effect of BL irradiation; focusing mainly on the case of psoriasis. We employed a systems biology approach to characterize the effect of BL irradiation of the skin. Since in phototherapy parameters such as fluence and power have a strong impact on the outcome, a parameter sensitivity analysis (PSA) was performed to estimate a range of fluence and power at which BL phototherapy could be successful. The models results suggest that the management of psoriasis is achieved by inducing symmetric differentiation of the keratinocytes in the epidermal proliferative compartment. It is observed that BL irradiation of psoriatic skin decreases the density of keratinocytes and transiently increases the density of lymphocytes, leading to the regulation of the interaction between these two cell types. The PSA of the models predicts that the higher the peak power the better the outcome of the BL phototherapy with a dose of 90J/cm2 per day. This systems biology approach provides additional insight into the use of BL phototherapy for inflammatory skin disorders

Parallel algorithms for transitive reduction for weighted graphs

Abstract. We present a generalization of transitive reduction for weighted graphs and give scalable polynomial algorithms for computing it based on the Floyd-Warshall algorithm for finding shortest paths in graphs. We also show how the algorithms can be optimized for memory efficiency and effectively parallelized to improve the run time. As a consequence, the algorithms can be tuned for modern general purpose graphics processors. Our prototype implementations exhibit significant speedups of more than one order of magnitude compared to their sequential counterparts. Transitive reduction for weighted graphs was instigated by problems in reconstruction of genetic networks. The first experiments in that domain show also encouraging results both regarding run time and the quality of the reconstruction