Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

nanite: using machine learning to assess the quality of atomic force microscopy-enabled nano-indentation data
Paul Müller, Shada Abuhattum, Stephanie Möllmert, et al.
BMC Bioinformatics (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 42

Showing 26-50 of 42 citing articles:

Machine learning framework for determination of elastic modulus without contact model fitting
Linh Thi Phuong Nguyen, Bernard Haochih Liu
International Journal of Solids and Structures (2022) Vol. 256, pp. 111976-111976
Open Access | Times Cited: 5
AFM Imaging Defect Detection and Classification with Artificial Intelligence and Deep Learning
Juntao Zhang, Juan Ren, Shuiqing Hu
(2023), pp. 447-452
Closed Access | Times Cited: 2
Deep-Learning-Based Automated Morphology Analysis With Atomic Force Microscopy
Yingao Chang, Zhi-Ang Liu, Yinan Wu, et al.
IEEE Transactions on Automation Science and Engineering (2023) Vol. 21, Iss. 4, pp. 7662-7673
Closed Access | Times Cited: 2
Emerging machine learning strategies for diminishing measurement uncertainty in SPM nanometrology
Linh Thi Phuong Nguyen, Bernard Haochih Liu
Surface Topography Metrology and Properties (2022) Vol. 10, Iss. 3, pp. 033002-033002
Closed Access | Times Cited: 3
Nanobiomechanical data classified by Deep learning based on convolutional neural networks
Adrián Martínez-Rivas, Cécile Formosa‐Dague, Luis Emilio Magaña Espinal, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Iterative Machine Learning for Classification and Discovery of Single-Molecule Unfolding Trajectories from Force Spectroscopy Data
Vanni Doffini, Haipei Liu, Zhaowei Liu, et al.
Nano Letters (2023) Vol. 23, Iss. 22, pp. 10406-10413
Open Access | Times Cited: 1
Deep Learning Regressors of Surface Properties from Atomic Force Microscopy Nanoindentations
Luís R. L. Pacheco, João Ferreira, Marco Parente
Applied Sciences (2024) Vol. 14, Iss. 6, pp. 2376-2376
Open Access
AFMDAQ Visualizer: Software and guide to reconstruct and analyze images with raw external data acquisition from the atomic force microscopies
Diego Oliveira Brito, Eduardo Antonio Murillo Bracamontes, C. I. Enriquez-Flores, et al.
(2024)
Open Access
Atomic Force Microscopy for the Study of Cell Mechanics in Pharmaceutics
Henrik Siboni, Ivana Ruseska, Andreas Zimmer
Pharmaceutics (2024) Vol. 16, Iss. 6, pp. 733-733
Open Access
Intelligent Nanomaterial Image Characterizations – A Comprehensive Review on AI Techniques that Power the Present and Drive the Future of Nanoscience
Umapathi Krishnamoorthy, Sukanya Balasubramani
Advanced Theory and Simulations (2024)
Closed Access
Supervised Learning for Predictive Pore Size Classification of Regenerated Cellulose Membranes Based on Atomic Force Microscopy Measurements
Alex Hadsell, Huong Chau, Richard Barber, et al.
Materials (2021) Vol. 14, Iss. 21, pp. 6724-6724
Open Access | Times Cited: 2
Future perspectives of atomic force microscopy for biophysics
Mi Li
Elsevier eBooks (2023), pp. 309-314
Closed Access
Iterative Machine Learning for Classification and Discovery of Single-molecule Unfolding Trajectories from Force Spectroscopy Data
Vanni Doffini, Haipei Liu, Zhaowei Liu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
OT_Analysis: a software for rich analysis of force curves when probing living cells with optical tweezers
Thierry Galliano, Guillaume Gay, Laurent Limozin, et al.
The Journal of Open Source Software (2023) Vol. 8, Iss. 90, pp. 4877-4877
Open Access
Machine Learning Techniques For AFM-Based Imaging of Cells
Junxi Wang, Fan Yang, Mingyan Gao, et al.
2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO) (2023), pp. 91-95
Closed Access
Application of self-organizing maps to AFM-based viscoelastic characterization of breast cancer cell mechanics
Andreas Weber, María dM Vivanco, José L. Toca‐Herrera
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
An Explicit Model to Extract Viscoelastic Properties of Cells From AFM Force-Indentation Curves
Shada Abuhattum, Dominic Mokbel, Paul Müller, et al.
SSRN Electronic Journal (2021)
Closed Access
Previous Page - Page 2

Scroll to top