Paul Bogdan
Overview
Explore the profile of Paul Bogdan including associated specialties, affiliations and a list of published articles.
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48
Citations
406
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Recent Articles
1.
Yin C, Imms P, Chowdhury N, Chaudhari N, Ping H, Wang H, et al.
Proc Natl Acad Sci U S A
. 2025 Feb;
122(10):e2413442122.
PMID: 39993207
Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes...
2.
McGlothin C, Kotov N, Whisnant K, Turali Emre E, Owuor D, Lu J, et al.
Angew Chem Int Ed Engl
. 2024 Dec;
64(9):e202413444.
PMID: 39663992
Self-replication of bioorganic molecules and oil microdroplets have been explored as models in prebiotic chemistry. An analogous process for inorganic nanomaterials would involve the autocatalytic nucleation of metal, semiconductor, or...
3.
Sia J, Zhang W, Cheng M, Bogdan P, Cook D
New Phytol
. 2024 Nov;
245(2):785-806.
PMID: 39573924
This study investigated the generalizability of Arabidopsis thaliana immune responses across diverse pathogens, including Botrytis cinerea, Sclerotinia sclerotiorum, and Pseudomonas syringae, using a data-driven, machine learning approach. Machine learning models...
4.
Guo K, Chaudhari N, Jafar T, Chowdhury N, Bogdan P, Irimia A
Neuroinformatics
. 2024 Nov;
22(4):591-606.
PMID: 39503843
The black box nature of deep neural networks (DNNs) makes researchers and clinicians hesitant to rely on their findings. Saliency maps can enhance DNN explainability by suggesting the anatomic localization...
5.
Guo K, Chaudhari N, Jafar T, Chowdhury N, Bogdan P, Irimia A
Res Sq
. 2024 Nov;
PMID: 39483910
The black box nature of deep neural networks (DNNs) makes researchers and clinicians hesitant to rely on their findings. Saliency maps can enhance DNN explainability by suggesting the anatomic localization...
6.
Yang R, Bernardino K, Xiao X, Gomes W, Mattoso D, Kotov N, et al.
Adv Sci (Weinh)
. 2024 Jul;
11(33):e2402464.
PMID: 38952077
Phase transitions are typically quantified using order parameters, such as crystal lattice distances and radial distribution functions, which can identify subtle changes in crystalline materials or high-contrast phases with large...
7.
Cha M, Turali Emre E, Xiao X, Kim J, Bogdan P, VanEpps J, et al.
Nat Comput Sci
. 2024 Jan;
2(4):243-252.
PMID: 38177552
Biomimetic nanoparticles are known to serve as nanoscale adjuvants, enzyme mimics and amyloid fibrillation inhibitors. Their further development requires better understanding of their interactions with proteins. The abundant knowledge about...
8.
Xiao Y, Nazarian S, Bogdan P
Sci Rep
. 2023 Dec;
13(1):22655.
PMID: 38114657
The urgent need for low latency, high-compute and low power on-board intelligence in autonomous systems, cyber-physical systems, robotics, edge computing, evolvable computing, and complex data science calls for determining the...
9.
Reed E, Ramos G, Bogdan P, Pequito S
Sci Rep
. 2023 Nov;
13(1):19502.
PMID: 37945616
Controlling large-scale dynamical networks is crucial to understand and, ultimately, craft the evolution of complex behavior. While broadly speaking we understand how to control Markov dynamical networks, where the current...
10.
Znaidi M, Sia J, Ronquist S, Rajapakse I, Jonckheere E, Bogdan P
Sci Rep
. 2023 Oct;
13(1):17948.
PMID: 37864007
Deciphering the non-trivial interactions and mechanisms driving the evolution of time-varying complex networks (TVCNs) plays a crucial role in designing optimal control strategies for such networks or enhancing their causal...