Advancing predictive risk assessment of chemicals via integrating machine learning, computational modeling, and chemical/nano‐quantitative structure‐activity …

AV Singh, M Varma, M Rai… - Advanced Intelligent …, 2024‏ - Wiley Online Library
The escalating use of novel chemicals and nanomaterials (NMs) across diverse sectors
underscores the need for advanced risk assessment methods to safeguard human health …

Sensitivity analysis methods in the biomedical sciences

G Qian, A Mahdi - Mathematical biosciences, 2020‏ - Elsevier
Sensitivity analysis is an important part of a mathematical modeller's toolbox for model
analysis. In this review paper, we describe the most frequently used sensitivity techniques …

Systems biology informed deep learning for inferring parameters and hidden dynamics

A Yazdani, L Lu, M Raissi… - PLoS computational …, 2020‏ - journals.plos.org
Mathematical models of biological reactions at the system-level lead to a set of ordinary
differential equations with many unknown parameters that need to be inferred using …

Weak SINDy for partial differential equations

DA Messenger, DM Bortz - Journal of Computational Physics, 2021‏ - Elsevier
Abstract Sparse Identification of Nonlinear Dynamics (SINDy) is a method of system
discovery that has been shown to successfully recover governing dynamical systems from …

[كتاب][B] Uncertainty quantification: theory, implementation, and applications

RC Smith - 2024‏ - SIAM
Uncertainty quantification serves a central role for simulation-based analysis of physical,
engineering, and biological applications using mechanistic models. From a broad …

Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to …

JG Chase, JC Preiser, JL Dickson, A Pironet… - Biomedical engineering …, 2018‏ - Springer
Critical care, like many healthcare areas, is under a dual assault from significantly
increasing demographic and economic pressures. Intensive care unit (ICU) patients are …

Modelling approaches for studying the microbiome

M Kumar, B Ji, K Zengler, J Nielsen - Nature microbiology, 2019‏ - nature.com
Advances in metagenome sequencing of the human microbiome have provided a plethora
of new insights and revealed a close association of this complex ecosystem with a range of …

Weak SINDy: Galerkin-based data-driven model selection

DA Messenger, DM Bortz - Multiscale Modeling & Simulation, 2021‏ - SIAM
We present a novel weak formulation and discretization for discovering governing equations
from noisy measurement data. This method of learning differential equations from data fits …

Automated adaptive inference of phenomenological dynamical models

BC Daniels, I Nemenman - Nature communications, 2015‏ - nature.com
Dynamics of complex systems is often driven by large and intricate networks of microscopic
interactions, whose sheer size obfuscates understanding. With limited experimental data …

The virtual brain integrates computational modeling and multimodal neuroimaging

P Ritter, M Schirner, AR McIntosh, VK Jirsa - Brain connectivity, 2013‏ - liebertpub.com
Brain function is thought to emerge from the interactions among neuronal populations. Apart
from traditional efforts to reproduce brain dynamics from the micro-to macroscopic scales …