Bayesian optimization objective-based experimental design
M Imani, SF Ghoreishi - 2020 American control conference …, 2020 - ieeexplore.ieee.org
Design has become a salient part of most of the scientific and engineering tasks, embracing
a wide range of domains including real experimental settings (eg, material discovery or drug …
a wide range of domains including real experimental settings (eg, material discovery or drug …
Boolean Kalman filter and smoother under model uncertainty
Partially-observed Boolean dynamical systems (POBDS) are a general class of nonlinear
state-space models that provide a rich framework for modeling many complex dynamical …
state-space models that provide a rich framework for modeling many complex dynamical …
[HTML][HTML] Inference of regulatory networks through temporally sparse data
A major goal in genomics is to properly capture the complex dynamical behaviors of gene
regulatory networks (GRNs). This includes inferring the complex interactions between …
regulatory networks (GRNs). This includes inferring the complex interactions between …
Bayesian optimization for efficient design of uncertain coupled multidisciplinary systems
SF Ghoreishi, M Imani - 2020 American Control Conference …, 2020 - ieeexplore.ieee.org
Stabilization of complex cyber-physical systems is extremely important in keeping the critical
infrastructure and the environment safe. This is, in particular, critical in coupled …
infrastructure and the environment safe. This is, in particular, critical in coupled …
BayReL: Bayesian relational learning for multi-omics data integration
E Hajiramezanali, A Hasanzadeh… - Advances in …, 2020 - proceedings.neurips.cc
High-throughput molecular profiling technologies have produced high-dimensional multi-
omics data, enabling systematic understanding of living systems at the genome scale …
omics data, enabling systematic understanding of living systems at the genome scale …
Radiomics based Bayesian inversion method for prediction of cancer and pathological stage
Objective: To develop a Bayesian inversion framework on longitudinal chest CT scans which
can perform efficient multi-class classification of lung cancer. Methods: While the …
can perform efficient multi-class classification of lung cancer. Methods: While the …
Leveraging Substrate Stiffness to Promote Stem Cell Asymmetric Division via Mechanotransduction–Polarity Protein Axis and Its Bayesian Regression Analysis
Asymmetric division of stem cells is an evolutionarily conserved process in multicellular
organisms responsible for maintaining cellular fate diversity. Symmetric–asymmetric division …
organisms responsible for maintaining cellular fate diversity. Symmetric–asymmetric division …
Partially-observed discrete dynamical systems
M Imani, SF Ghoreishi - 2021 American Control Conference …, 2021 - ieeexplore.ieee.org
This paper introduces a new signal model called partially-observed discrete dynamical
systems (PODDS). This signal model is a special case of the hidden Markov model (HMM) …
systems (PODDS). This signal model is a special case of the hidden Markov model (HMM) …
[HTML][HTML] Dynamic modeling of the cellular senescence gene regulatory network
O Bischof - Heliyon, 2023 - cell.com
Cellular senescence is a cell fate that prominently impacts physiological and
pathophysiological processes. Diverse cellular stresses induce it, and dramatic gene …
pathophysiological processes. Diverse cellular stresses induce it, and dramatic gene …
Offline fault detection in gene regulatory networks using next-generation sequencing data
SF Ghoreishi, M Imani - 2019 53rd Asilomar Conference on …, 2019 - ieeexplore.ieee.org
In a previous contribution, a method was proposed for on-line fault detection in Boolean
gene regulatory networks based on the Boolean Kalman Filter and hypothesis testing on …
gene regulatory networks based on the Boolean Kalman Filter and hypothesis testing on …