Bisexual flowering plants are at high risk of self-fertilization, which would produce less fit offspring (known as ‘inbreeding depression’). Hence, more than 100 flowering plant families have developed various mechanisms to avoid self-fertilization, generally called ‘self-incompatibility’ (SI). Under these mechanisms, the species is subdivided into multiple 'types' or 'classes', such that a...
The human immune system consists of lymphoid tissue in different localisations, including about 600 lymph nodes. The latter can be divided in different compartments, concentrating specialised immune cells in a highly effective manner. We investigated and defined human lymph nodes applying confocal laser technologies to generate 3-D pictures and 4Dmovies. Many parameters as cell speeds tracks...
Data analytics requires large data archives beyond current world storage media, causing researchers to seek alternative storage media. Scientists in fields like biology, ecology, life sciences, and medicine are using data archiving to aid their research. During the last decade, DNA (Deoxyribonucleic Acid) storage has been significantly investigated as a method for archiving data at massive...
This presentation explores advanced topics in the simulation of biochemical systems, with a particular emphasis on multiscale approaches for modeling open systems characterized by varying particle/molecule numbers. We will discuss key methods, including hybrid and coarse-grained simulation schemes, as well as the integration of thermodynamic principles and field theory representations to...
Molecular dynamics simulations with atomistic resolution are a standard tool to study liquids and biomolecular systems. Most often, force field (FF) limitations mean that simulations must be performed at low concentrations. I will discuss recent advances in FFs of ions and the insight they enabled into the molecular scale mechanisms leading to protein halophilicity, as well as the...
Unlike personalized predictive models, which operate independently of the real world and are sometimes incorrectly labeled as digital twins, Medical Digital Twins require a tightly integrated workflow. This workflow includes sensors to monitor the health state, predictive models (propagators) to forecast changes in that state over time, comparators to assess the agreement between forecast and...
Drosophila gastrulation is a popular model used to study morphogenesis. Despite a long-standing effort to determine the physical nature of cell shape changes in this key model system, there is no consensus on the underlying biophysical mechanism. Any predictive model of a morphogenetic event requires the knowledge of material properties of the tissue undergoing morphogenesis. Using our...
During the embryonic stage, mechanical forces such as contraction, stretching, and bending play a crucial role in forming structured cell groups and patterns. However, it is still unclear how these different forces affect pattern formation in developing tissues. In order to understand how these different factors affect tissue dynamics and cellular rearrangements we used the active vertex...
The limb bud development exemplifies the complexity of organogenesis, whereby the organ’s macroscopic state feeds back on cellular decisions. Digital twins are an exciting approach towards understanding such systems. Regarding limb bud elongation, diverse hypotheses have been proposed. Involving ectodermal constraints, proliferation, motility, migration, as well as PCP induced intercalation....
The effectiveness of therapies and preventive strategies for nervous system disorders relies on our ability to customize treatments to the unique needs of each individual. Digital twins of the nervous system have the potential to revolutionize precision medicine. As a result, one of the key research and innovation areas for advancing brain health is the development of digital twins for both...
Biomembranes are integral part of the cell, the basic building block of all life. They are a two- dimensional fluid, composed of myriad proteins and lipid species, which provide identity to the cell and to many internal organelles. An intriguing aspect of membranes is their ability to assume a variety of shapes, which is crucial for many cellular processes such as food update, waste disposal,...
Molecular dynamics (MD) is a well-established simulation method that has successfully been applied to study a wide range of biomolecular processes. As a result of continuous improvements in both modeling methods and computational infrastructures, the study of mesoscopic, multi-component systems has become more attainable. However, the intricacies involved in setting up MD simulations for...
In the yeast plasma membrane, domains rich in long-chain sphingolipids are observed. Our study employs MD simulations to explore the influence of these lipids on membrane properties. We utilize both coarse-grained and all-atom models, employing a simplified lipid composition with varying concentrations of long-chain lipids. We assess the impact on diverse parameters such as order parameter,...
G protein-coupled receptors (GPCRs) play a crucial role in modulating physiological responses by transmitting extracellular signals into the cell. Moreover, they are the main target of drugs like salmeterol and salbutamol, which act against pulmonary diseases by activating the GPCR, β2-adrenergic receptor (β2AR). In this study, we employ coarse-grained molecular dynamics simulations with the...
Combining synthetic polymers with biological matter such as proteins or DNA is a cornerstone technique in nanomedicine and biotechnology. For example, antibody formulations can be stabilized through the addition of low molecular weight polymers or nucleic acid delivered by combining them with ionic polymers to form polyplexes. Exploiting the vast chemical composition space spanned by synthetic...
All-atom and coarse-grained molecular dynamics (MD), Langevin dynamics (LD) and Brownian dynamics (BD) are computational methodologies, which have been applied to spatio-temporal modelling of a number of intracellular processes. I will discuss connections between MD, LD and BD, with a focus on the development, analysis and applications of multi-resolution methods, which use (detailed) MD...
My research is focused on the mathematical and computational modeling of cell regulatory processes. We and others have developed an approach to modeling the reaction kinetics of biochemical systems that allows detailed knowledge about protein-protein interactions to be encoded as rules that generalize the standard reaction network formulation and enables the building, simulation, and analysis...
The inositol-requiring enzyme 1 (IRE1) serves as a highly conserved stress sensor within the endoplasmic reticulum (ER), crucial for mitigating the cytotoxic effects resulting from the accumulation of unfolded proteins. Dysregulation of the unfolded protein response (UPR), a network of signaling pathways aimed at alleviating ER stress, is implicated in various human pathologies including...
Biological movement patterns are sometimes quasi linear with abrupt changes in direction and speed, as in movements of plastids in root cells of plants. We discuss random walk (RW) models suggesting that modelling absolute movement direction can be advantageous as compared to relative direction as assumed in the widely used correlated RWs. A new stochastic model called linear walk is proposed...
Understanding how multicellular organisms reliably orchestrate cell-fate decisions is a central challenge in developmental biology. This is particularly intriguing in early mammalian development, where early cell-lineage differentiation arises from processes that initially appear cell-autonomous but later materialize reliably at the tissue level. In this study, we develop a multi-scale,...
Precise spatial patterning of cell fate during morphogenesis requires accurate inference of cellular position. In making such inferences from morphogen profiles, cells must contend with inherent stochasticity in morphogen production, transport, sensing and signalling. Motivated by the multitude of signalling mechanisms in various developmental contexts, we show how cells may utilise multiple...
“You, your joys and sorrows, your memories and ambitions, your sense of personal identity and free will, are in fact no more than the behavior of a vast assembly of nerve cells and their associated molecules.” Francis Crick’s words encapsulate a core challenge in neuroscience: cracking the neural code. This challenge has been hindered by two major limitations: (1) our ability to record...
For years, neurons in visual cortex have been characterized in terms of simple feature dimensions such as orientation and spatial frequency. However, in recent years deep learning methods have set new standards in predicting the activity of neurons in visual cortex to arbitrary stimuli. Because of this property, these models are sometimes referred to as digital twins (DTs). Here we show how...
The fundamental structure of cortical networks arises early in development prior to the onset of sensory experience. However, how endogenously generated networks respond to the onset of sensory experience, and how they form mature sensory representations with experience remains unclear. Here we examine this ‘nature-nurture transform’ at the single trial level using chronic in vivo calcium...
Qualitative, cartoon-based understanding of physiological processes is not sufficient and needs to be taken to a deeper, quantitative (computational) level. Two types of computational models, namely statistical & mechanistic models, can be used to predict subcellular, cellular and supracellular phenomena in silico. This talk will mainly focus on mechanistic models. A simulation of a large...
Human intelligence and human consciousness emerge gradually during the process of cognitive development. Understanding this development is an essential aspect of understanding the human mind and may facilitate the construction of artificial minds with similar abilities. In this talk I will describe our lab's recent efforts to develop a digital twin of the developing human mind and body. To...
Astrophysical research often relies on sophisticated software tools to model, simulate, and analyze complex astronomical phenomena. The dynamic range in astrophysics simulations often covers more than 20 orders of magnitude in temporal and spatial scales. Further complications are introduced by the interaction among various physicals process, such as gravity, hydrodynamics, nuclear fusion...
Nuclear and globular star clusters (NSC and GC) are spectacular self-gravitating stellar systems in our Galaxy and across the Universe - in many respects. They populate disks and spheroids of galaxies as well as almost every galactic center. In massive elliptical galaxies NSCs harbor supermassive black holes, which influence the evolution of their host galaxies as a whole. The evolution of...
