As all of the articles published in our journal are open access, you have free and unlimited access to the full text. We welcome you to read our most highly cited papers published in 2023 and 2024, which are listed below:

1. “Advances in AI for Protein Structure Prediction: Implications for Cancer Drug Discovery and Development”
by Xinru Qiu, Han Li, Greg Ver Steeg and Adam Godzik
Biomolecules 2024, 14(3), 339; https://doi.org/10.3390/biom14030339
Full text available online: https://www.mdpi.com/2218-273X/14/3/339

2. “Identification of an Autophagy-Related Signature for Prognosis and Immunotherapy Response Prediction in Ovarian Cancer”
by Jinye Ding, Chunyan Wang, Yaoqi Sun, Jing Guo, Shupeng Liu and Zhongping Cheng
Biomolecules 2023, 13(2), 339; https://doi.org/10.3390/biom13020339
Full text available online: https://www.mdpi.com/2218-273X/13/2/339

3. “Graph Random Forest: A Graph Embedded Algorithm for Identifying Highly Connected Important Features”
by Leqi Tian, Wenbin Wu and Tianwei Yu
Biomolecules 2023, 13(7), 1153; https://doi.org/10.3390/biom13071153
Full text available online: https://www.mdpi.com/2218-273X/13/7/1153

4. “Using GPT-3 to Build a Lexicon of Drugs of Abuse Synonyms for Social Media Pharmacovigilance”
by Kristy A. Carpenter and Russ B. Altman
Biomolecules 2023, 13(2), 387; https://doi.org/10.3390/biom13020387
Full text available online: https://www.mdpi.com/2218-273X/13/2/387

5. “In Silico Screening and Optimization of Cell-Penetrating Peptides Using Deep Learning Methods”
by Hyejin Park, Jung-Hyun Park, Min Seok Kim, Kwangmin Cho and Jae-Min Shin
Biomolecules 2023, 13(3), 522; https://doi.org/10.3390/biom13030522
Full text available online: https://www.mdpi.com/2218-273X/13/3/522

6. “Quality Control—A Stepchild in Quantitative Proteomics: A Case Study for the Human CSF Proteome”
by Svitlana Rozanova, Julian Uszkoreit, Karin Schork, Bettina Serschnitzki, Martin Eisenacher, Lars Tönges, Katalin Barkovits-Boeddinghaus and Katrin Marcus
Biomolecules 2023, 13(3), 491; https://doi.org/10.3390/biom13030491
Full text available online: https://www.mdpi.com/2218-273X/13/3/491

7. “Quantitative Proteomic Characterization of Foreign Body Response towards Silicone Breast Implants Identifies Chronological Disease-Relevant Biomarker Dynamics”
by Ines Schoberleitner, Klaus Faserl, Bettina Sarg, Daniel Egle, Christine Brunner and Dolores Wolfram
Biomolecules 2023, 13(2), 305; https://doi.org/10.3390/biom13020305
Full text available online: https://www.mdpi.com/2218-273X/13/2/305

8. “On the Best Way to Cluster NCI-60 Molecules”
by Saiveth Hernández-Hernández and Pedro J. Ballester
Biomolecules 2023, 13(3), 498; https://doi.org/10.3390/biom13030498
Full text available online: https://www.mdpi.com/2218-273X/13/3/498

9. “Hybrid Multitask Learning Reveals Sequence Features Driving Specificity in the CRISPR/Cas9 System”
by Dhvani Sandip Vora, Shashank Yadav and Durai Sundar
Biomolecules 2023, 13(4), 641; https://doi.org/10.3390/biom13040641
Full text available online: https://www.mdpi.com/2218-273X/13/4/641

10. “BSA Binding and Aggregate Formation of a Synthetic Amino Acid with Potential for Promoting Fibroblast Proliferation: An In Silico, CD Spectroscopic, DLS, and Cellular Study”
by Hayarpi Simonyan, Rosanna Palumbo, Satenik Petrosyan, Anna Mkrtchyan, Armen Galstyan, Ashot Saghyan, Pasqualina Liana Scognamiglio, Caterina Vicidomini, Marta Fik-Jaskólka and Giovanni N. Roviello
Biomolecules 2024, 14(5), 579; https://doi.org/10.3390/biom14050579
Full text available online: https://www.mdpi.com/2218-273X/14/5/579