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OpenAlex Citation Counts

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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 1-25 of 42 citing articles:

Advancing High-Throughput Cellular Atomic Force Microscopy with Automation and Artificial Intelligence
Ophélie Thomas- -Chemin, Sébastien Janel, Zeyd Boumehdi, et al.
ACS Nano (2025)
Closed Access | Times Cited: 2
Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook
Marc Botifoll, Ivan Pinto‐Huguet, Jordi Arbiol
Nanoscale Horizons (2022) Vol. 7, Iss. 12, pp. 1427-1477
Open Access | Times Cited: 68
Atomic Force Microscopy Methods to Measure Tumor Mechanical Properties
Julian Najera, Matthew R. Rosenberger, Meenal Datta
Cancers (2023) Vol. 15, Iss. 13, pp. 3285-3285
Open Access | Times Cited: 21
Application of self-organizing maps to AFM-based viscoelastic characterization of breast cancer cell mechanics
Andreas Weber, María dM Vivanco, José L. Toca‐Herrera
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 17
Enabling autonomous scanning probe microscopy imaging of single molecules with deep learning
Javier Sotres, Hannah Boyd, Juan F. González-Martínez
Nanoscale (2021) Vol. 13, Iss. 20, pp. 9193-9203
Open Access | Times Cited: 38
Recent Advances in the Label-Free Characterization of Exosomes for Cancer Liquid Biopsy: From Scattering and Spectroscopy to Nanoindentation and Nanodevices
Riccardo Di Santo, Sabrina Romanò, Alberto Mazzini, et al.
Nanomaterials (2021) Vol. 11, Iss. 6, pp. 1476-1476
Open Access | Times Cited: 37
Atomic force microscopy in the characterization and clinical evaluation of neurological disorders: current and emerging technologies
David T. She, Mui Hoon Nai, Chwee Teck Lim
Med-X (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 6
Machine learning approaches for improving atomic force microscopy instrumentation and data analytics
Nabila Masud, Jaydeep Rade, Md. Hasibul Hasan Hasib, et al.
Frontiers in Physics (2024) Vol. 12
Open Access | Times Cited: 5
Machine learning on properties of multiscale multisource hydroxyapatite nanoparticles datasets with different morphologies and sizes
Ziteng Liu, Yinghuan Shi, Hongwei Chen, et al.
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 32
An explicit model to extract viscoelastic properties of cells from AFM force-indentation curves
Shada Abuhattum, Dominic Mokbel, Paul Müller, et al.
iScience (2022) Vol. 25, Iss. 4, pp. 104016-104016
Open Access | Times Cited: 22
Biosensing, Characterization of Biosensors, and Improved Drug Delivery Approaches Using Atomic Force Microscopy: A Review
Anwesha Sarkar
Frontiers in Nanotechnology (2022) Vol. 3
Open Access | Times Cited: 21
Scanning probe microscopy in the age of machine learning
Md Ashiqur Rahman Laskar, Umberto Celano
APL Machine Learning (2023) Vol. 1, Iss. 4
Open Access | Times Cited: 13
The role of convolutional neural networks in scanning probe microscopy: a review
Ido Azuri, Irit Rosenhek‐Goldian, Neta Regev‐Rudzki, et al.
Beilstein Journal of Nanotechnology (2021) Vol. 12, pp. 878-901
Open Access | Times Cited: 27
Perceiving and Countering Marine Biofouling: Structure, Forces, and Processes at Surfaces in Sea Water Across the Length Scales
Xiaoyan Xu, Shifeng Guo, G. Julius Vancsó
Langmuir (2025)
Closed Access
Indirect Measurement Methods for Quality and Process Control in Nanomanufacturing
Zhaoyan Fan, Xiaochen Hu, Robert X. Gao
Nanomanufacturing and Metrology (2022) Vol. 5, Iss. 3, pp. 209-229
Open Access | Times Cited: 13
Recent advances and biophysical applications of atomic force microscopy in cancer research: An overview
Bharath Sampath Kumar
(2024)
Open Access | Times Cited: 2
PyFMLab: Open-source software for atomic force microscopy microrheology data analysis
Javier López-Alonso, Mar Eroles, Sébastien Janel, et al.
Open Research Europe (2024) Vol. 3, pp. 187-187
Open Access | Times Cited: 2
Machine learning to probe modal interaction in dynamic atomic force microscopy
Pierpaolo Belardinelli, Abhilash Chandrashekar, Richard Wiebe, et al.
Mechanical Systems and Signal Processing (2022) Vol. 179, pp. 109312-109312
Open Access | Times Cited: 10
Topological Data Analysis of Nanoscale Roughness of Layer-by-Layer Polyelectrolyte Samples Using Machine Learning
Aleksandr S. Aglikov, Timur A. Aliev, Mikhail V. Zhukov, et al.
ACS Applied Electronic Materials (2023) Vol. 5, Iss. 12, pp. 6955-6963
Closed Access | Times Cited: 5
Automatic classification of single-molecule force spectroscopy traces from heterogeneous samples
Nina Ilieva, Nicola Galvanetto, Michele Allegra, et al.
Bioinformatics (2020) Vol. 36, Iss. 20, pp. 5014-5020
Open Access | Times Cited: 11
Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines
Ophélie Thomas - - Chemin, Childérick Séverac, Abderazzak Moumen, et al.
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 34, pp. 44504-44517
Closed Access | Times Cited: 1
Observer Design for Topography Estimation in Atomic Force Microscopy Using Neural and Fuzzy Networks
Mohammad Rafiee Javazm, Hossein Nejat Pishkenari
Ultramicroscopy (2020) Vol. 214, pp. 113008-113008
Closed Access | Times Cited: 9
PyFMLab: Open-source software for atomic force microscopy microrheology data analysis
Javier López-Alonso, Mar Eroles, Sébastien Janel, et al.
Open Research Europe (2023) Vol. 3, pp. 187-187
Open Access | Times Cited: 3
Some considerations in nanoindentation measurement and analysis by atomic force microscopy
Irit Rosenhek‐Goldian, Sidney Cohen
Journal of Vacuum Science & Technology A Vacuum Surfaces and Films (2023) Vol. 41, Iss. 6
Open Access | Times Cited: 3
Locating critical events in AFM force measurements by means of one-dimensional convolutional neural networks
Javier Sotres, Hannah Boyd, Juan F. González-Martínez
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 5
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