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:

Generative models for protein sequence modeling: recent advances and future directions
Mehrsa Mardikoraem, Zirui Wang, Nathaniel Pascual, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 6
Open Access | Times Cited: 19

Showing 19 citing articles:

Recent advances in deep learning and language models for studying the microbiome
Binghao Yan, Yunbi Nam, Lingyao Li, et al.
Frontiers in Genetics (2025) Vol. 15
Open Access | Times Cited: 2

Global insights and the impact of generative AI-ChatGPT on multidisciplinary: a systematic review and bibliometric analysis
Nauman Khan, Zahid A. Khan, Anis Koubâa, et al.
Connection Science (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 14

A comprehensive overview of recent advances in generative models for antibodies
Fanxu Meng, Na Zhou, Hu Guangchun, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 2648-2660
Open Access | Times Cited: 3

Research on Bitter Peptides in the Field of Bioinformatics: A Comprehensive Review
Shanghua Liu, Tianyu Shi, Junwen Yu, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 18, pp. 9844-9844
Open Access | Times Cited: 3

GenerRNA: A generative pre-trained language model for de novo RNA design
Yichong Zhao, Kenta Oono, Hiroki Takizawa, et al.
PLoS ONE (2024) Vol. 19, Iss. 10, pp. e0310814-e0310814
Open Access | Times Cited: 3

GenerRNA: A generative pre-trained language model forde novoRNA design
Yichong Zhao, Kenta Oono, Hiroki Takizawa, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2

Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations
Prem Singh Bist, Hilal Tayara, Kil To Chong
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 11, pp. 6974-6982
Closed Access | Times Cited: 1

Navigating the Promise and Perils of Generative AI in Healthcare
Shenson Joseph, Qurat ul-Ain, Sidra Nosheen, et al.
Advances in medical technologies and clinical practice book series (2024), pp. 91-110
Closed Access | Times Cited: 1

Integrating Computational Design and Experimental Approaches for Next-Generation Biologics
Ahrum Son, Jongham Park, Woojin Kim, et al.
Biomolecules (2024) Vol. 14, Iss. 9, pp. 1073-1073
Open Access | Times Cited: 1

Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties
Srivathsan Badrinarayanan, Chakradhar Guntuboina, Parisa Mollaei, et al.
Journal of Chemical Information and Modeling (2024) Vol. 65, Iss. 1, pp. 83-91
Open Access | Times Cited: 1

Deep-Learning Uncovers certain CCM Isoforms as Transcription Factors
Jacob Croft, Liyuan Gao, Victor S. Sheng, et al.
Frontiers in Bioscience-Landmark (2024) Vol. 29, Iss. 2
Open Access

How do Big Data and Generative AI dawn on Computational Biology?
Shaurya Jauhari
SSRN Electronic Journal (2024)
Closed Access

Semi-Supervised Learning in Bioinformatics
Alisha Parveen, Tikam Chand Dakal, Pankaj Yadav, et al.
Elsevier eBooks (2024)
Closed Access

Autoregressive neural network
Joachim Feger, S. L. Rivera
Radiopaedia.org (2024)
Closed Access

How Much Do DNA and Protein Deep Embeddings Preserve Biological Information?
Matteo Tolloso, Silvia Giulia Galfrè, Arianna Pavone, et al.
Lecture notes in computer science (2024), pp. 209-225
Closed Access

How Do Big Data and Generative AI Dawn on Computational Biology?
Shaurya Jauhari
(2024), pp. 193-228
Closed Access

EvoSeq-ML: Advancing Data-Centric Machine Learning with Evolutionary-Informed Protein Sequence Representation and Generation
Mehrsa Mardikoraem, Nathaniel Pascual, Patrick Finneran, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access

Page 1

Scroll to top