26 papers · ranked by Valyu relevance
Bhanwar Lal Puniya, Meghna Verma, Chiara Damiani, Shaimaa Bakr + 2 more
In the last few decades, the study of biological systems has witnessed a paradigm shift driven by recognizing inherent nonlinearity and the involvement of diverse molecular players. Systems Biology, an interdisciplinary field integrating biology, mathematics, statistics, and computer science, addresses exploring…
Jessica S. Yu, Blair Lyons, Susanne Rafelski, Julie A. Theriot + 2 more
Iterating between data-driven research and generative computational models is a powerful approach for emulating biological systems, testing hypotheses, and gaining a deeper understanding of these systems. We developed a hybrid agent-based model (ABM) that integrates a Cellular Potts Model (CPM) designed to investigate…
Anna Matuszyńska, Oliver Ebenhöh, Matias D. Zurbriggen, Daniel C. Ducat + 1 more
Synthetic biology designs and constructs new biological parts, devices and systems with predetermined functionalities. With the unlimited ability to synthesise any DNA and RNA and transfer it to almost any organism, we are at the dawn of a new era in which biology is being recreated in ways never before possible. It…
Lilija Wehling, Gurdeep Singh, Ahmad Wisnu Mulyadi, Rakesh Hadne Sreenath + 9 more
In this study, we present Talk2Biomodels (T2B), an open-source^1^, user-friendly, large language model-based agentic AI platform designed to democratize access to computational models of biological interactions and promote the FAIRification (Findability, Accessibility, Interoperability, and Reusability) of these…
Florian Cogoni, David Bernard, Roxana Kazhen, Salvatore Valitutti + 2 more
Agent-based models are commonly used in biology to study tissue-scale phenomena by reproducing the individual behavior of the cells. They offer the possibility to study cellular biology at the individual cell scale to explore the basic behavior of cells which are responsible of the emergence of more complex phenomena…
Oliver Lee, Malte Gather, Eli Zysman-Colman
We describe a new tool for the efficient management of computational chemistry. Digichem is a program that automates and simplifies nearly the entire computational pipeline, including large-scale batch submission of calculations, analysis and results parsing, the generation of 3D density plots and 2D graphs of…
Maja Rudolph, Stefan Kurz, Barbara Rakitsch
Design patterns provide a systematic way to convey solutions to recurring modeling challenges. This paper introduces design patterns for hybrid modeling, an approach that combines modeling based on first principles with data-driven modeling techniques. While both approaches have complementary advantages there are often…
Beatrix C. Hiesmayr, Marc‐Thorsten Hütt
A recent trend in mathematical modeling is to publish the computer code together with the research findings. Here we explore the formal question, whether and in which sense a computer implementation is distinct from the mathematical model. We argue that, despite the convenience of implemented models, a set of implicit…
Olivia Eriksson, Upinder Singh Bhalla, Kim T Blackwell, Sharon M Crook + 8 more
Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system works or why certain phenomena are observed. Data-driven modeling…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Marco Ruscone, Miguel Vazquez, Alfonso Valencia
The construction of multicellular mechanistic models in systems biology typically requires months of literature research, programming expertise, and deep knowledge of specialized computational tools. Here we present intelligent tool orchestration through Model Context Protocol (MCP) servers that enable Large Language…
Marcello Pompa, Simona Panunzi, Alessandro Borri, Laura D’Orsi + 2 more
Large volumes of data are these days collected and archived from patients in a variety of clinical settings. This phenomenon is the product of the evolution of analysis systems and the appearance of new diagnostic techniques . The physician has thus in many cases observations of the clinical status of the patient at…
Panagiotis D. Kolokathis, Nikolaos K. Sidiropoulos, Dimitrios Zouraris, Dimitra-Danai Varsou + 20 more
Modelling Data (MODA) reporting guidelines have been proposed for common terminology and for recording metadata for physics-based materials modelling and simulations in a CEN Workshop Agreement (CWA 17284:2018). Their purpose is similar to that of the Quantitative Structure-Activity Relationship (QSAR) model report…
Herbert Jaeger, Beatriz Noheda, Wilfred G. van der Wiel
Approaching limitations of digital computing technologies have spurred research in neuromorphic and other unconventional approaches to computing. Here we argue that if we want to systematically engineer computing systems that are based on unconventional physical effects, we need guidance from a formal theory that is…
Jonathan Karr, Rahuman S. Malik-Sheriff, James Osborne, Gilberto Gonzalez-Parra + 14 more
'Gilberto Gonzalez-Parra' 'Eric Forgoston' 'Ruth Bowness' 'Yaling Liu' 'Robin Thompson' 'Winston Garira' 'Jacob Barhak' 'John Rice' 'Marcella Torres' 'Hana M. Dobrovolny' 'Tingting Tang' 'William Waites' 'James A. Glazier' 'James R. Faeder' 'Alexander Kulesza'] During the COVID-19 pandemic, mathematical modeling of…
Niloofar Shahidi, Michael Pan, Kenneth Tran, Edmund J. Crampin + 1 more
Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model’s components and assumptions. To address these challenges in…
Maurice HT Ling
Modeling and simulation are recognized as important aspects of the scientific method for more than 70 years but its adoption in biology has been slow. Debates on its representativeness, usefulness, and whether the effort spent on such endeavors is worthwhile, exist to this day. Here, I argue that most of learning is…
Emilia M. Wysocka, Matthew Page, James Snowden, T. Ian Simpson
Dynamic modelling has considerably improved our understanding of complex molecular mechanisms. Ordinary differential equations (ODEs) are the most detailed and popular approach to modelling the dynamics of molecular systems. However, their application in signalling networks, characterised by multi-state molecular…
Luca Serena, Moreno Marzolla, Gabriele D’Angelo, Stefano Ferretti
—Multilevel modeling and simulation (M&S) is becoming increasingly relevant due to the benefits that this methodology offers. Multilevel models allow users to describe a system at multiple levels of detail. From one side, this can make better use of computational resources, since the more detailed and time-consuming…
Pariksheet Nanda, Maral Budak, Christian T. Michael, Kathryn Krupinsky + 1 more
Although infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex…
Konstantia Georgouli, Jae-Seung Yeom, Robert C. Blake, Ali Navid
Whole-cell modeling is “the ultimate goal” of computational systems biology and “a grand challenge for 21st century” (Tomita, Trends in Biotechnology, 2001, 19(6), 205-10). These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the…
Authors not listed
We have developed Aitomia – a platform powered by AI to assist in performing AI-driven atomistic and quantum chemical (QC) simulations. This evolving intelligent assistant platform is equipped with chatbots and AI agents to help experts and guide non-experts in setting up and running atomistic simulations, monitoring…
Adelinde M. Uhrmacher, Peter I. Frazier, Reiner Hähnle, Franziska Klügl + 8 more
'Franziska Klügl' 'Fabian Lorig' 'Bertram Ludäscher' 'Laura Nenzi' 'Cristina Ruiz-Martín' 'Bernhard Rumpe⋆' 'Claudia Szabo' 'Gabriel Wainer' 'Pia Wilsdorf'] Simulation has become, in many application areas, a sine-qua-non. Most recently, COVID-19 has underlined the importance of simulation studies and limitations in…
Samantha Durdy, Cameron J. Hargreaves, Mark Dennison, Benjamin Wagg + 5 more
The discovery of new materials often requires collaboration between experimental and computational chemists. Web based platforms allow more flexibility in this collaboration by giving access to computational tools without the need for access to computational researchers. We present Liverpool Materials Discovery Server…
Authors not listed
Accurate and efficient computations of standard enthalpies of formation (Hf) for small organic molecules are crucial for diverse chemical engineering and scientific applications. Building on part 1 of this work [J. Phys. Chem. A 2024, 128, 21, 4335–4352], we systematically benchmark 284 model chemistries for Hf…
Nicolò Cogno, Cristian Axenie, Roman Bauer, Vasileios Vavourakis
Computational models and simulations are not just appealing because of their intrinsic characteristics across spatiotemporal scales, scalability, and predictive power, but also because the set of problems in cancer biomedicine that can be addressed computationally exceeds the set of those amenable to analytical…