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:

Predicting mechanical properties of silk from its amino acid sequences via machine learning
Yoonjung Kim, Taeyoung Yoon, Woo B. Park, et al.
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials (2023) Vol. 140, pp. 105739-105739
Closed Access | Times Cited: 12

Showing 12 citing articles:

Sequence-based data-constrained deep learning framework to predict spider dragline mechanical properties
Akash Pandey, Wei Chen, Sinan Keten
Communications Materials (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 4
Unraveling the Mechanical Property Decrease of Electrospun Spider Silk: A Molecular Dynamics Simulation Study
Hongchul Shin, Taeyoung Yoon, Wooboum Park, et al.
ACS Applied Bio Materials (2024) Vol. 7, Iss. 3, pp. 1968-1975
Closed Access | Times Cited: 3
Overview and Evolution of Insect Fibroin Heavy Chain (FibH)
Tong Zhang, Sanyuan Ma, Ziyang Zhang, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 13, pp. 7179-7179
Open Access | Times Cited: 2
Upcycled PET–Ag-Nanocoated Silk Functional Fabric for Enhanced Filtration Efficiency and Germicidal Efficacy
Md. Tanvir Hossaın, Md. Abdus Shahid, Md. Golam Mortuza Limon
ACS Chemical Health & Safety (2024) Vol. 31, Iss. 5, pp. 404-413
Open Access | Times Cited: 2
Could an Anterior Cruciate Ligament Be Tissue-Engineered from Silk?
Judith Hahn, Clemens Gögele, Gundula Schulze‐Tanzil
Cells (2023) Vol. 12, Iss. 19, pp. 2350-2350
Open Access | Times Cited: 3
Evaluation of the deteriorating effects of microbial primary metabolites on silk fibres
Chuanmiao Ding, Lindan Pan, Yichang Li, et al.
Analytical Sciences (2024) Vol. 40, Iss. 7, pp. 1339-1347
Open Access
A study of forecasting the Nephila clavipes silk fiber's ultimate tensile strength using machine learning strategies
Hongchul Shin, Taeyoung Yoon, Juneseok You, et al.
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials (2024) Vol. 157, pp. 106643-106643
Closed Access
Recent Advances in the Integration of Protein Mechanics and Machine Learning
Yen‐Lin Chen, Shu‐Wei Chang
Extreme Mechanics Letters (2024), pp. 102236-102236
Closed Access
Progress in Multiscale Modeling of Silk Materials
Harry D. A. Brough, David Cheneler, John G. Hardy
Biomacromolecules (2024) Vol. 25, Iss. 11, pp. 6987-7014
Closed Access
Artificial Intelligence Techniques to Predict the Behavior of Silk Fibroin
Bhavana Shanmughan, Balasubramanian Kandasubramanian
Engineering materials (2024), pp. 193-206
Closed Access
A Physically‐Based Machine Learning Approach Inspires an Analytical Model for Spider Silk Supercontraction
Vincenzo Fazio, Ali D. Malay, Keiji Numata, et al.
Advanced Functional Materials (2024)
Open Access
Sequence-based data-constraint deep learning framework to predict spider dragline mechanical properties
Sinan Keten, Akash Pandey, Wei Chen
Research Square (Research Square) (2023)
Open Access
Page 1

Scroll to top