Author

T.-T. Lin

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Microbiology· 3 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 4 Research Focus:drug response / drug discovery· 4 Assay:protein sequence· 2 Assay:proteomics· 1

Frequent Co-Authors

C.-Y. Lin· 4 shared S.-H. Chen· 4 shared I.-H. Lu· 3 shared W.-C. Cheng· 3 shared L.-Y. Yang· 2 shared Y.-Y. Sun· 2 shared C.-F. Ko· 1 shared C.-T. Wang· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

4 shared papersMicrobiology

C.-Y. Lin

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Peptide-based drug predictions for cancer therapy using deep learning

Y.-Y. Sun, T.-T. Lin, W.-C. Cheng, I.-H. Lu, S.-H. Chen, C.-Y. Lin

This paper develops AI4ACP, a web-server for predicting anticancer peptides, showing improved performance over existing predictors.

bioRxiv · Feb 1, 2022Cancer Biology

Developing an Antiviral Peptides Predictor with Generative Adversarial Network Data Augmentation

T.-T. Lin, Y.-Y. Sun, W.-C. Cheng, I.-H. Lu, S.-H. Chen, C.-Y. Lin

The paper develops a binary classifier for identifying antiviral peptides using a GAN-augmented dataset and achieves high performance on a test set.

bioRxiv · Nov 29, 2021 · PreprintMicrobiology

Discovering Novel Antimicrobial Peptides in Generative Adversarial Network

T.-T. Lin, L.-Y. Yang, C.-T. Wang, G.-W. Lai, C.-F. Ko, Y.-H. Shih, S.-H. Chen, C.-Y. Lin

This study uses a deep convolutional GAN to generate novel antimicrobial peptides, which show antibacterial activity, including against antibiotic-resistant strains.

bioRxiv · Nov 22, 2021 · PreprintMicrobiology

AI4AMP: Sequence-based antimicrobial peptides predictor using physicochemical properties-based encoding method and deep learning

T.-T. Lin, L.-Y. Yang, I.-H. Lu, W.-C. Cheng, Z.-R. Hsu, S.-H. Chen, C.-Y. Lin

AI4AMP predicts antimicrobial activity of protein sequences using physicochemical properties encoding and deep learning, outperforming existing predictors.

bioRxiv · Dec 17, 2020 · PreprintMicrobiology