12 papers · ranked by Valyu relevance
Michael A. Boemo, Luca Cardelli, Conrad A. Nieduszynski
Biological systems are made up of components that change their actions (and interactions) over time and coordinate with other components nearby. Together with a large state space, the complexity of this behaviour can make it difficult to create concise mathematical models that can be easily extended or modified. This…
Alessandra Livigni, Laura O’Hara, Marta E. Polak, Tim Angus + 2 more
In silico modelling of biological pathways is a major endeavour of systems biology. Here we present a methodology for construction of pathway models from the literature and other sources using a biologist-friendly graphical modelling system. The pathway notation scheme, called mEPN, is based on the principles of the…
Simon Gamache-Poirier, Alexia Souvane, William Leclerc, Catherine Villeneuve + 1 more
A common depiction for biological signaling networks is the influence graph in which the activation and inhibition effects between molecular species are shown with vertices and arcs connecting them. Another formalism for reaction-based models is the Petri nets which has a graphical representation and a mathematical…
Dan Liu, Francesca Young, Kieran D. Lamb, Adalberto Claudio Quiros + 5 more
Computational prediction of protein structure from amino acid sequences alone has been achieved with unprecedented accuracy, yet the prediction of protein-protein interactions (PPIs) remains an outstanding challenge. Here we assess the ability of protein language models (PLMs), routinely applied to protein folding, to…
Hans Colonius, Adele Diederich
The ability to inhibit our responses voluntarily is an important case of cognitive control. The stop-signal paradigm is a popular tool to study response inhibition. Participants perform a response time task (go task) and, occasionally, the go stimulus is followed by a stop signal after a variable delay, indicating…
Lu Cheng, Siddharth Ramchandran, Tommi Vatanen, Niina Lietzen + 3 more
Biomedical research typically involves longitudinal study designs where samples from individuals are measured repeatedly over time and the goal is to identify risk factors (covariates) that are associated with an outcome value. General linear mixed effect models have become the standard workhorse for statistical…
Daniele Pessina, Tony Tian, Oliver Watson, Jerry Y. Heng + 1 more
Modelling complex crystallisation processes remains challenging due to limited experimental datasets, high measurement noise, and the need for generalisability across varying operating conditions. Neural Ordinary Differential Equations (NODEs) and transfer learning (TL) offer promising tools to overcome these…
Benjamin M Gyori, John A Bachman, Kartik Subramanian, Jeremy L Muhlich + 2 more
Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. We present an approach to building computational models directly from natural language using…
Agustin A. Corbat, Mauro Silberberg, Hernán E. Grecco
Apoptosis, a form of programmed cell death central to all multicellular organisms, plays a key role during organism development and is often misregulated in cancer. Devising a single model applicable to distinct stimuli and conditions has been limited by lack of robust observables. Indeed, previous numerical models…
Kate E. Dray, Joseph J. Muldoon, Niall M. Mangan, Neda Bagheri + 1 more
Mathematical modeling is invaluable for advancing understanding and design of synthetic biological systems. However, the model development process is complicated and often unintuitive, requiring iteration on various computational tasks and comparisons with experimental data. Ad hoc model development can pose a barrier…
Wassim Abou-Jaoudé, Pedro T. Monteiro, Aurélien Naldi, Maximilien Grandclaudon + 3 more
Computational modeling constitutes a crucial step towards the functional understanding of complex cellular networks. In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant…
Raúl Luna, Miguel A. Vadillo, David Luque
Human behaviour is driven by two types of processes running in parallel: goal-directed and habitual, each supported by different computational-learning mechanisms, model-free and model-based respectively. In model-free strategies, stimulus-response associations are strengthened when actions are followed by a reward and…