Biology subjects

Manolache, S.

Publications and source records attributed to Manolache, S..

4 recordsLinked to original sources

bioRxiv2026

Simulating the dynamics of gene regulatory systems at cellular scale

The temporal nature of eukaryotic gene expression is the result of a complex, non-linear, dynamical system of regulatory processes. So far, models of such systems trade realism for tractability by using strict simplifying assumptions. These simplified models are often unfaithful to our biological understanding; however, without such simplifications, analytical solutions become more challenging and these dynamical systems must then be studied through simulation. Here, we explore the question of how this complex web of gene regulatory connections can be faithfully simulated for all tens of thousands of genes that usually define a eukaryotic organism. We present a proof-of-principle model and simulator, GeneRegulatorySystems.jl which is based on a biophysical chemical master equation that overcomes three key restrictions. First, it allows an exact stochastic simulation of fully non-linear gene expression dynamics, including feedback control, to parsimoniously capture cause and effect relationships of gene regulation. Further, it includes a general framework for implementing diverse mechanisms of gene control such as protein mediated degradation, RNAi, and protein complex formation. Finally, it scales realistically to tens of thousands of genes. We achieve this by introducing a domain-specific programming language to aid the design of experimental protocols from small-scale, well-studied, scenarios of gene regulation inspired by dynamical systems biology up to large-scale, single cell omics experiments with interventions. In this way, our framework provides a grammar of in silico experimental design that can capture single-cell gene expression dynamics for entire genomes.

systems biology↗

bioRxiv2020

Governance networks around grasslands with contrasting management history

Romanian grasslands have high nature value, being among the most important biodiversity hotspots at the European level. The European Union Common Agricultural Policy (CAP) contradicts the Biodiversity Strategy to 2020 objective by hindering coordinated grassland governance and collaboration among the involved actors. At the European level, few attempts have been made in creating conceptual strategies for implementing conservation measures in a multi-actor and multi-scale governance setting. Our paper focuses on a comparative network analysis of grassland landscape governance of three Romanian regions (Iron Gates Natural Park - SW; Sighisoara - Tarnava Mare - center; and Dobrogea - SE), representatives for grassland management in mountain and lowland settings. We investigated the structural characteristics of one-mode directed grassland governance networks in the three protected areas (standard cohesion and reciprocity metrics and exponential random graph models), the position of institutions participating in networks (node-level centrality metrics), and the perception of CAP influence on grassland governance by farmers benefiting of CAP agri-environmental payments. In Sighisoara, grasslands governance has been centralized but biodiversity-friendly, while in Iron Gates, grasslands were traditionally managed through a decentralized, community-level system, and this type of governance continues to date. Whereas for Dobrogeas grasslands, the governance was performed in an intensive, centralized state-run management regime during the communist time and by large landowners after the transition period ended. Our findings illustrate the structure of the three governance networks and dissimilar patterns of collaboration, indicating distinct particularities to be considered when exploring barriers to and options for successful governance in traditionally managed grasslands in the context of CAP measures-driven management.

ecology↗

bioRxiv2018

Who is researching biodiversity hotspots in Eastern Europe? A case study on grasslands from Romania

Farming landscapes of Europe are vital arenas for social-ecological sustainability because of their significant coverage and potential to integrate food production with biodiversity conservation. Knowledge gathered by scientific research is a critical ingredient for developing and implementing socio-economically and ecologically sustainable grassland management strategies for grasslands. The quality of scientific knowledge and its potential to address grasslands as complex social-ecological systems is strongly dependent on the creativity and scientific ambition of the researcher, but also on the network (from academic and non-academic sectors) around the researcher. The goal of this paper is to map the research network around Romanias grasslands. These systems have exceptional socio-cultural and economic values and are between the most biodiverse ecosystems of the world. Considering the multiple threats to these grasslands, it is an urgent need to understand the existing scientific knowledge profile around these systems. This paper aims at using bibliometrics analysis, a well-developed scientific domain that envisages network theory to analyze relationships between affiliations network, co-authorship network, and co-word analysis. The number of studies targeting grassland management in Romania is increasing mainly thanks to international involvement. However, the management of the grasslands is still deficient and the contribution of science to the process is virtually absent. The subject of research is mainly related to the biological and ecological characteristics of grasslands, a notable absence from internationally visible research being the management of grasslands, especially in the context of EU Common Agricultural Policies. To increase scientific performance, and better inform EU and local policies on grassland management, Romanian researchers should better capitalize on international collaborations and local academic leaders. Our findings can be used to identify research gaps and to improve collaboration and knowledge exchange between practitioners, scientists, policy makers, and stakeholders.

scientific communication and education↗

bioRxiv2018

Empirical analysis and modelling of Argos Doppler location errors in Romania

BackgroundAdvances in wildlife tracking technology have allowed researchers to understand the spatial ecology of many terrestrial and aquatic animal species. Argos Doppler is a technology that is widely used for wildlife tracking owing to the small size and low weight of the Argos transmitters. This allows them to be fitted to small-bodied species. The longer lifespan of the Argos units in comparison to units outfitted with miniaturized global positioning system (GPS) technology has also recommended their use. In practice, large Argos location errors often occur due to communication conditions such as transmitter settings, local environment, and the behavior of the tracked individual.\n\nMethodsConsidering the geographic specificity of errors and the lack of benchmark studies in Eastern Europe, the research objectives were: (1) to evaluate the accuracy of Argos Doppler technology under various environmental conditions in Romania, (2) to investigate the effectiveness of straightforward destructive filters for improving Argos Doppler data quality, and (3) to provide guidelines for processing Argos Doppler wildlife monitoring data. The errors associated with Argos locations in four geographic locations in Romania were assessed during static, low-speed and high-speed tests. The effectiveness of the Douglas Argos distance angle filter algorithm was then evaluated to ascertain its effect on the minimization of localization errors.\n\nResultsArgos locations received in the tests had larger associated horizontal errors than those indicated by the operator of the Argos system, including under ideal reception conditions. Positional errors were similar to those obtained in other studies outside of Europe. The errors were anisotropic, with larger longitudinal errors for the vast majority of the data. Errors were mostly related to speed of the Argos transmitter at the time of reception, but other factors such as topographical conditions and orientation of antenna at the time of the transmission also contributed to receiving low-quality data. The Douglas-Argos filter successfully excluded the largest errors while retaining a large amount of data when the threshold was set to the local scale (2 km).\n\nDiscussionFilter selection requires knowledge about the movement patterns and behavior of the species of interest, and the parametrization of the selected filter typically requires a trial and error approach. Selecting the proper filter reduces the errors while retaining a large amount of data. However, the post-processed data typically includes large positional errors; thus, we recommend incorporating Argos error metrics such as error ellipse or use complex modeling approaches when working with filtered data.

ecology↗