12 papers · ranked by Valyu relevance
Ismail El Korde, Jason M. Lewis, Erik Clarkson, Tommy Dam + 3 more
Single-particle tracking methods have emerged as a crucial tool for the characterization of dynamical and diffusive processes in a range of biological and synthetic systems. Here, we propose a simple and light-weight yet accurate method for the segmentation of multi-state Brownian trajectories based on an optimised…
Mingjian He, Proloy Das, Gladia Hotan, Patrick L. Purdon
Linear parametric state-space models are a ubiquitous tool for analyzing neural time series data, providing a way to characterize the underlying brain dynamics with much greater statistical efficiency than non-parametric data analysis approaches. However, neural time series data are frequently time-varying, exhibiting…
Ismail El Korde, Jason M. Lewis, Erik Clarkson, Tommy Dam + 3 more
Single-particle tracking methods have emerged as a crucial tool for the characterization of dynamical and diffusive processes in a range of biological and synthetic systems. Here, we propose a simple and light-weight yet accurate method for the segmentation of multi-state Brownian trajectories based on an optimised…
R. M. Razban, E. I. Shakhnovich
The distribution of protein stability effects is known to be well-approximated by a Gaussian distribution from previous empirical fits. Starting from first-principles statistical mechanics, we more rigorously motivate this empirical observation by deriving per residue protein stability effects to be Gaussian. Our…
Raphaël Liégeois, Timothy O. Laumann, Abraham Z. Snyder, Juan Zhou + 1 more
Resting-state functional connectivity is a powerful tool for studying human functional brain networks. Temporal fluctuations in functional connectivity, i.e., dynamic functional connectivity (dFC), are thought to reflect dynamic changes in brain organization and non-stationary switching of discrete brain states.…
M. Nicolás Cruz-Bournazou, Harini Narayanan, Alessandro Fagnani, Alessandro Butté
Hybrid modeling, meaning the integration of data-driven and knowledge-based methods, is quickly gaining popularity among many research fields, including bioprocess engineering and development. Recently, the data-driven part of hybrid methods have been largely extended with machine learning algorithms (e.g., artificial…
Sebastian Spreizer, Martin Angelhuber, Jyotika Bahuguna, Ad Aertsen + 1 more
Striatum is predominantly inhibitory and the main input nucleus of the basal ganglia. A functional characterization of its activity dynamics is crucial for understanding the mechanisms underlying phenomenon such as action selection and initiation. Here, we investigated the effects of the spatial connectivity structure…
Hanjin Liu, Tomohiro Shima
The hidden Markov model (HMM) is widely used to analyze biophysical chronological data with discrete states, such as binding/detachment of biomolecules, protein/nucleotide conformational changes and step-like movement of single proteins. Despite its usefulness, classical HMM fitting has practical drawbacks that it…
Nischal Mainali, Rava Azeredo da Silveira, Yoram Burak
Hippocampal place cells form a spatial map by selectively firing at specific locations in an animal’s environment^1^. Until recently the hippocampus appeared to implement a simple coding scheme for position, in which each neuron is assigned to a single region of space in which it is active^1^. Recently, new experiments…
Rod Chalk, Oktawia Borkowska, Kamal Abdul Azeez, Stephanie Oerum + 3 more
The electrospray mass/charge distribution for a protein is an instantaneous measurement of surface areas during the transition from liquid to gas phase. Protonation is dependent upon surface area and surface area is related to protein folding under all conditions. M/z distributions for proteins and protein analogues…
Amitava Roy, Vishwesh Venkatraman, Tibra Ali
Inspired by black hole thermodynamics, the area law that entropy is proportional to horizon area has been proposed in quantum entanglement entropy and has largely maintained its validity. This article shows that the area law is also valid for the thermodynamic entropy of molecules. We showed that the gas-phase entropy…
Luke E. Rogerson, Zhijian Zhao, Katrin Franke, Philipp Berens + 1 more
Variability, stochastic or otherwise, is a central feature of neural circuits. Yet the means by which variation and uncertainty are derived from noisy observations of neural activity is often unprincipled, with too much weight placed on numerical convenience at the cost of statistical rigour. For two-photon imaging…