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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:

Umami-MRNN: Deep learning-based prediction of umami peptide using RNN and MLP
Lulu Qi, Jialuo Du, Yue Sun, et al.
Food Chemistry (2022) Vol. 405, pp. 134935-134935
Closed Access | Times Cited: 41

Showing 26-50 of 41 citing articles:

Generation, Characterisation and Identification of Bioactive Peptides from Mesopelagic Fish Protein Hydrolysates Using In Silico and In Vitro Approaches
María Hayes, Azza Silotry Naik, Leticia Mora, et al.
Marine Drugs (2024) Vol. 22, Iss. 7, pp. 297-297
Open Access | Times Cited: 3
Screening and characterization of umami peptides from enzymatic and fermented products of wheat gluten using machine learning
Haowen Chen, Chunxia Zhou, Guili Jiang, et al.
LWT (2024) Vol. 208, pp. 116700-116700
Open Access | Times Cited: 3
Unlocking the Potential of the Umami Taste-Presenting Compounds: A Review of the Health Benefits, Metabolic Mechanisms and Intelligent Detection Strategies
Rongrong Xia, Yitong Qiao, Heran Xu, et al.
Food Reviews International (2024), pp. 1-21
Closed Access | Times Cited: 3
DeepBP: Ensemble deep learning strategy for bioactive peptide prediction
Ming Zhang, Jianling Zhou, Xiaohua Wang, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 3
Bioinformatics and bioactive peptides from foods: Do they work together?
Anna Iwaniak, Piotr Mińkiewicz, Małgorzata Darewicz
Advances in food and nutrition research (2024), pp. 35-111
Closed Access | Times Cited: 2
Generation, characterisation and identification of bioactive peptides from Mesopelagic fish protein hydrolysates using in silico and in vitro approaches.
María Hayes, Azza Silotry Naik, Leticia Mora, et al.
(2024)
Open Access | Times Cited: 2
Recent progress and prospects in production and identification of umami peptides from marine proteins
Di Hu, Zhenxiao Zheng, Botao Liang, et al.
Food Innovation and Advances (2024) Vol. 3, Iss. 3, pp. 256-267
Open Access | Times Cited: 2
Identification of Novel Umami Peptides from Yeast Protein through Enzymatic, Sensory, and In Silico Approaches
Yuxiang Gu, Yajie Niu, Jingcheng Zhang, et al.
Journal of Agricultural and Food Chemistry (2024) Vol. 72, Iss. 36, pp. 20014-20027
Closed Access | Times Cited: 2
High-throughput discovery of umami peptides from pork bone and elucidation of their molecular mechanism for umami taste perception
Yuxiang Gu, Yajie Niu, Jingcheng Zhang, et al.
Food & Function (2024) Vol. 15, Iss. 19, pp. 9766-9778
Closed Access | Times Cited: 2
Umami-gcForest: Construction of a predictive model for umami peptides based on deep forest
Shuaiqi Ji, Junrui Wu, Feiyu An, et al.
Food Chemistry (2024) Vol. 464, pp. 141826-141826
Closed Access | Times Cited: 2
Identification of Novel Umami Peptides in Termitornyces albuminosus (Berk) Heim Soup by In Silico Analyses Combined with Sensory Evaluation: Discovering Potential Mechanism of Umami Taste Formation with Molecular Perspective
Haixia Yu, Shuai Zhao, Junjie Yi, et al.
Journal of Agricultural and Food Chemistry (2023)
Closed Access | Times Cited: 6
Computational screening of umami tastants using deep learning
Prantar Dutta, Kishore Gajula, Nitu Verma, et al.
Molecular Diversity (2024)
Closed Access | Times Cited: 1
Screening and Characterization of Umami Peptides from Enzymatic and Fermented Products of Wheat Gluten Using Machine Learning
Haowen Chen, Chunxia Zhou, Guili Jiang, et al.
(2024)
Closed Access
Rapid screening of novel umami peptides in high-umami scored air-dried chicken under low-salt processing based on molecular sensory techniques
Zhenzhen Yu, Mingzhen Liu, Ju Xu, et al.
Food Bioscience (2024), pp. 105479-105479
Closed Access
Characterization and peptide identification of umami fractions from rusip—a traditional fermented anchovy product
Vania Amelia, Lutfi Yulmiftiyanto Nurhamzah, Hanifah Nuryani Lioe, et al.
Journal of Food Science (2024)
Closed Access
VirtuousMultiTaste: Predicting Multiple Taste Sensations with a Multi- objective ML-driven Method
Lampros Androutsos, Lorenzo Pallante, Agorakis Bompotas, et al.
(2023)
Open Access | Times Cited: 1
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