Viatcheslav Gurev
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View article: A standard transformer and attention with linear biases for molecular conformer generation
A standard transformer and attention with linear biases for molecular conformer generation Open
Sampling low-energy molecular conformations, spatial arrangements of atoms in a molecule, is a critical task for many different calculations performed in the drug discovery and optimization process. Numerous specialized equivariant network…
View article: BMFM-RNA: An Open Framework for Building and Evaluating Transcriptomic Foundation Models
BMFM-RNA: An Open Framework for Building and Evaluating Transcriptomic Foundation Models Open
Transcriptomic foundation models (TFMs) have recently emerged as powerful tools for analyzing gene expression in cells and tissues, supporting key tasks such as cell-type annotation, batch correction, and perturbation prediction. However, …
View article: Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer’s Disease Using Biophysical Modeling and Deep Learning
Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer’s Disease Using Biophysical Modeling and Deep Learning Open
View article: Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modelling
Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modelling Open
Predictions for physical systems often rely upon knowledge acquired from ensembles of entities, e.g. ensembles of cells in biological sciences. For qualitative and quantitative analysis, these ensembles are simulated with parametric famili…
View article: Inferring parameters of pyramidal neuron excitability in mouse models of Alzheimer’s disease using biophysical modeling and deep learning
Inferring parameters of pyramidal neuron excitability in mouse models of Alzheimer’s disease using biophysical modeling and deep learning Open
Alzheimer’s disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and tau aggregate in the brain, resulting in a progressive loss of neuronal function. Hippocampal neurons in transgenic mice with amyloidopath…
View article: Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data
Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data Open
Background: Up to 30–50% of chronic heart failure patients who underwent cardiac resynchronization therapy (CRT) do not respond to the treatment. Therefore, patient stratification for CRT and optimization of CRT device settings remain a ch…
View article: Generative adversarial networks for construction of virtual populations of mechanistic models: simulations to study Omecamtiv Mecarbil action
Generative adversarial networks for construction of virtual populations of mechanistic models: simulations to study Omecamtiv Mecarbil action Open
Biophysical models are increasingly used to gain mechanistic insights by fitting and reproducing experimental and clinical data. The inherent variability in the recorded datasets, however, presents a key challenge. In this study, we presen…
View article: Machine Learning prediction of cardiac resynchronisation therapy response from combination of clinical and model-driven data
Machine Learning prediction of cardiac resynchronisation therapy response from combination of clinical and model-driven data Open
A bstract Background Up to 30%-50% of chronic heart failure patients who underwent cardiac resynchronization therapy (CRT) do not respond to the treatment. Therefore, patient stratification for CRT and optimization of CRT device settings r…
View article: Integration of AI and mechanistic modeling in generative adversarial networks for stochastic inverse problems.
Integration of AI and mechanistic modeling in generative adversarial networks for stochastic inverse problems. Open
Stochastic inverse problems (SIP) address the behavior of a set of objects of the same kind but with variable properties, such as a population of cells. Using a population of mechanistic models from a single parametric family, SIP explains…
View article: Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modeling
Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modeling Open
Predictions for physical systems often rely upon knowledge acquired from ensembles of entities, e.g., ensembles of cells in biological sciences. For qualitative and quantitative analysis, these ensembles are simulated with parametric famil…
View article: The ‘Digital Twin’ to enable the vision of precision cardiology
The ‘Digital Twin’ to enable the vision of precision cardiology Open
Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towar…
View article: Model order reduction for left ventricular mechanics via congruency training
Model order reduction for left ventricular mechanics via congruency training Open
Computational models of the cardiovascular system and specifically heart function are currently being investigated as analytic tools to assist medical practice and clinical trials. To achieve clinical utility, models should be able to assi…
View article: Global Sensitivity Analysis of Ventricular Myocyte Model-Derived Metrics for Proarrhythmic Risk Assessment
Global Sensitivity Analysis of Ventricular Myocyte Model-Derived Metrics for Proarrhythmic Risk Assessment Open
Multiscale computational models of the heart are being extensively investigated for improved assessment of drug-induced torsades de pointes (TdP) risk, a fatal side effect of many drugs. Model-derived metrics such as action potential durat…
View article: Model order reduction for left ventricular mechanics via congruency training
Model order reduction for left ventricular mechanics via congruency training Open
Computational models of the cardiovascular system and heart function are currently being investigated as analytic tools to assist medical practice and clinical trials. Recent technological advances allow for finite element models of heart …
View article: Intrinsic structure of model-derived metrics for <i>in silico</i> proarrhytmic risk assessment identified by global sensitivity analysis
Intrinsic structure of model-derived metrics for <i>in silico</i> proarrhytmic risk assessment identified by global sensitivity analysis Open
Multiscale computational models of heart are being extensively investigated for improved assessment of drug-induced Torsades de Pointes (TdP) risk, a fatal side effect of many drugs. Model-derived metrics (features) such as action potentia…
View article: Gaussian Process Regressions for Inverse Problems and Parameter Searches in Models of Ventricular Mechanics
Gaussian Process Regressions for Inverse Problems and Parameter Searches in Models of Ventricular Mechanics Open
Patient specific models of ventricular mechanics require the optimization of their many parameters under the uncertainties associated with imaging of cardiac function. We present a strategy to reduce the complexity of parametric searches f…
View article: Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables Open
Despite significant recent advances in deep neural networks, training them remains a challenge due to the highly non-convex nature of the objective function. State-of-the-art methods rely on error backpropagation, which suffers from severa…
View article: Estimating the probabilities of rare arrhythmic events in multiscale computational models of cardiac cells and tissue
Estimating the probabilities of rare arrhythmic events in multiscale computational models of cardiac cells and tissue Open
Ectopic heartbeats can trigger reentrant arrhythmias, leading to ventricular fibrillation and sudden cardiac death. Such events have been attributed to perturbed Ca2+ handling in cardiac myocytes leading to spontaneous Ca2+ release and del…
View article: Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct Features
Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct Features Open
While pre-clinical Torsades de Pointes (TdP) risk classifiers had initially been based on drug-induced block of hERG potassium channels, it is now well established that improved risk prediction can be achieved by considering block of non-h…
View article: Sensitivity Analysis of the QT and JTpeak Intervals from a High-resolution Human Left-ventricular Wedge Model
Sensitivity Analysis of the QT and JTpeak Intervals from a High-resolution Human Left-ventricular Wedge Model Open
There is an interest in looking at sub-intervals of the QT in the Comprehensive in-vitro Proarrhythmia Assay (CiPA) initiative.Here, we performed a sensitivity analysis of JTpeak and T-wave morphology (TWM) parameters computed on transmura…
View article: Verification of cardiac mechanics software: benchmark problems and solutions for testing active and passive material behaviour
Verification of cardiac mechanics software: benchmark problems and solutions for testing active and passive material behaviour Open
Models of cardiac mechanics are increasingly used to investigate cardiac physiology. These models are characterized by a high level of complexity, including the particular anisotropic material properties of biological tissue and the active…
View article: Papillary muscles contraction does not change ventricular wall mechanics
Papillary muscles contraction does not change ventricular wall mechanics Open
Papillary muscles play a crucial role to support valves in the ventricles. However, much less is known about the role in ventricular wall mechanics. Evidence in the literature is inconclusive, showing both of changes in wall strain and ind…
View article: Verification of cardiac mechanics software: benchmark problems and solutions for testing active and passive material behaviour
Verification of cardiac mechanics software: benchmark problems and solutions for testing active and passive material behaviour Open
Models of cardiac mechanics are increasingly used to investigate cardiac physiology. These models are characterized by a high level of complexity, including the particular anisotropic material properties of biological tissue and the active…