Multipolar Reactive DPD: A Novel Tool for Spatially Resolved Systems Biology

This article reports about a novel extension of dissipative particle dynamics (DPD) that allows the study of the collective dynamics of complex chemical and structural systems in a spatially resolved manner with a combinatorially complex variety of different system constituents. We show that introducing multipolar interactions between particles leads to extended membrane structures emerging in a self-organized manner and exhibiting both the necessary mechanical stability for transport and fluidity so as to provide a two-dimensional self-organizing dynamic reaction environment for kinetic studies in the context of cell biology. We further show that the emergent dynamics of extended membrane bound objects is in accordance with scaling laws imposed by physics.Comment: submitted to CMSB 0

Spatial Modeling of Vesicle Transport and the Cytoskeleton: The Challenge of Hitting the Right Road

The membrane trafficking machinery provides a transport and sorting system for many cellular proteins. We propose a mechanistic agent-based computer simulation to integrate and test the hypothesis of vesicle transport embedded into a detailed model cell. The method tracks both the number and location of the vesicles. Thus both the stochastic properties due to the low numbers and the spatial aspects are preserved. The underlying molecular interactions that control the vesicle actions are included in a multi-scale manner based on the model of Heinrich and Rapoport (2005). By adding motor proteins we can improve the recycling process of SNAREs and model cell polarization. Our model also predicts that coat molecules should have a high turnover at the compartment membranes, while the turnover of motor proteins has to be slow. The modular structure of the underlying model keeps it tractable despite the overall complexity of the vesicle system. We apply our model to receptor-mediated endocytosis and show how a polarized cytoskeleton structure leads to polarized distributions in the plasma membrane both of SNAREs and the Ste2p receptor in yeast. In addition, we can couple signal transduction and membrane trafficking steps in one simulation, which enables analyzing the effect of receptor-mediated endocytosis on signaling

Everything you always wanted to know about SDPD⋆ (⋆but were afraid to ask)

An overview of the smoothed dissipative particle dynamics (SDPD) method is presented in a format that tries to quickly answer questions that often arise among users and newcomers. It is hoped that the status of SDPD is clarified as a mesoscopic particle model and its potentials and limitations are highlighted, as compared with other methods

Crowdsourcing, Open Innovation and Collective Intelligence in the scientific method: a research agenda and operational framework

The lonely researcher trying to crack a problem in her office still plays an important role in fundamental research. However, a vast exchange, often with participants from different fields is taking place in modern research activities and projects. In the "Research Value Chain" (a simplified depiction of the Scientific Method as a process used for the analyses in this paper), interactions between researchers and other individuals (intentional or not) within or outside their respective institutions can be regarded as occurrences of Collective Intelligence. "Crowdsourcing" (Howe 2006) is a special case of such Collective Intelligence. It leverages the wisdom of crowds (Surowiecki 2004) and is already changing the way groups of people produce knowledge, generate ideas and make them actionable. A very famous example of a Crowdsourcing outcome is the distributed encyclopedia "Wikipedia". Published research agendas are asking how techniques addressing "the crowd" can be applied to non-profit environments, namely universities, and fundamental research in general. This paper discusses how the non-profit "Research Value Chain" can potentially benefit from Crowdsourcing. Further, a research agenda is proposed that investigates a) the applicability of Crowdsourcing to fundamental science and b) the impact of distributed agent principles from Artificial Intelligence research on the robustness of Crowdsourcing. Insights and methods from different research fields will be combined, such as complex networks, spatially embedded interacting agents or swarms and dynamic networks. Although the ideas in this paper essentially outline a research agenda, preliminary data from two pilot studies show that nonscientists can support scientific projects with high quality contributions. Intrinsic motivators (such as "fun") are present, which suggests individuals are not (only) contributing to such projects with a view to large monetary rewards

Coarse graining and scaling in dissipative particle dynamics

Dissipative particle dynamics (DPD) is now a well-established method for simulating soft matter systems. However, its applicability was recently questioned because some investigations showed an upper coarse-graining limit that would prevent the applicability of the method to the whole mesoscopic range. This article aims to re-establish DPD as a truly mesoscopic method by analyzing the problems reported by other authors and by presenting a scaling scheme that allows one to apply DPD simulations directly to any desired length scale

Quando un insieme di reazioni è autocatalitico

L’emergenza di uno o più cicli auto-catalitici all’interno di una rete di molecole interagenti è una proprietà fondamentale sia nello sviluppo di possibili scenari legati all’origine della vita, sia nell’indirizzare la ricerca di laboratorio verso lo sviluppo di nuove molecole capaci di evolversi interagendo con i propri bersagli.Alcuni modelli teorici di reti catalitiche hanno dimostrato una certapredisposizione alla comparsa di cicli, fenomeno che al contrario difficilmente si riesce ad ottenere nei laboratori. UIl nostro studio prende spunto dai lavori di Stuart Kauffman eFarmer, nei quali è stato sviluppato un modello contenentedue tipi di reazioni (condensazione e cleavage) ed in cui tali reazioni vengono catalizzate dalle altre molecole presenti nel sistema.L’obiettivo del nostro lavoro è di migliorare il modello originale introducendo una dinamica stocastica delle molecole, basata sul noto algoritmo di Gillespie, in modo da poter trattare adeguatamente i problemi connessi alla numerosità degli esemplari delle varie specie molecolari, che in alcuni casi può essere anche molto bassa, e alla cinetica delle reazioni. Discutiamo il tipo di analisi di rete necessario per interpretare gli schemi di reazione stocastic

Morphological computation and morphological control: Steps towards a formal theory and applications

Morphological computation can be loosely defined as the exploitation of the shape, material properties, and physical dynamics of a physical system to improve the efficiency of a computation. Morphological control is the application of morphological computing to a control task. In its theoretical part, this article sharpens and extends these definitions by suggesting new formalized definitions and identifying areas in which the definitions we propose are still inadequate. We go on to describe three ongoing studies, in which we are applying morphological control to problems in medicine and in chemistry. The first involves an inflatable support system for patients with impaired movement, and is based on macroscopic physics and concepts already tested in robotics. The two other case studies (self-assembly of chemical micro-reactors; models of induced cell repair in radio-oncology) describe processes and devices on the micrometer scale, in which the emergent dynamics of the underlying physical system (e.g., phase transitions) are dominated by stochastic processes such as diffusion