Evaluating Protein Transfer Learning with TAPE

Cited by (723)

Items 601–700 of 723

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3. LMDTA: Molecular Pre-trained and Interaction Fine-tuned Attention Neural Network for Drug-Target Affinity Prediction
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4. Boost Protein Language Model with Injected Structure Information Through Parameter Efficient Fine-tuning
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5. Position Specific Scoring Is All You Need? Revisiting Protein Sequence Classification Tasks
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6. Can Deep Learning Solve the Cas9 Dilemma?
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7. Adaptive Residue-wise Profile Fusion for Low Homologous Protein Secondary Structure Prediction Using External Knowledge
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8. A Review of Protein Structure Prediction using Deep Learning
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9. PENSAMIENTO CRÍTICO EN LA INVESTIGACIÓN CIENTÍFICA Y ACADÉMICA
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10. DeepPSC (protein structure camera): computer vision-based protein backbone structure reconstruction from alpha carbon trace as a case study
    Xing Zhang, Junwen Luo, Yi Cai, Wei Zhu, Xiaofeng Yang, Hongmin Cai, Zhanglin Lin · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
11. WITHDRAWN: ToxVec: Deep Language Model-Based Representation Learning for Venom Peptide Classification
    Meisam Ahmadi, Mohammad Reza Jahed‐Motlagh, Ehsaneddin Asgari, Adel Torkaman Rahmani, Alice Carolyn McHardy · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
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13. Deep learning model for the prediction and classification of protein toxins across all domains of life
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14. In silico protein science: from sequence to network
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15. Identification of Enzymatic Active Sites with Unsupervised Language Modeling
    Loıc Kwate Dassi, Matteo Manica, Daniel Probst, Philippe Schwaller, Yves Gaëtan Nana Teukam, Teodoro Laino · 2022 · ChemRxiv
16. Predicting SARS-CoV-2 epitope-specific TCR recognition using pre-trained protein embeddings
    Youngmahn Han, Aeri Lee · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
17. Fast and Accurate Prediction of Intrinsically Disordered Protein by Protein Language Model
    Shijie Xu, Akira Onoda · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
18. A robust deep learning platform to predict CD8+ T-cell epitopes
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19. Discriminating Ion Channels from Non-Ion Channel Membrane Proteins Using Machine Learning and Deep Learning Classifiers with Protein Language Model Representations
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20. Co-evolution integrated deep learning framework for variants generation and fitness prediction
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21. SENSE-PPI reconstructs protein-protein interactions of various complexities, within, across, and between species, with sequence-based evolutionary scale modeling and deep learning
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22. A cross-attention transformer encoder for paired sequence data
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23. Protein Language Models in Directed Evolution
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24. TooT-PLM-P2S: Incorporating Secondary Structure Information into Protein Language Models
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25. Integration of protein and coding sequences enables mutual augmentation of the language model
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26. ProtHGT: Heterogeneous Graph Transformers for Automated Protein Function Prediction Using Biological Knowledge Graphs and Language Models
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27. Sequence-aware Prediction of Point Mutation-induced Effects on Protein-Protein Binding Affinity using Deep Learning
    Jian Zhuang, Zonghui Li, Suhui Wang, Ren‐Chao Zheng, Guijun Zhang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
28. Quantitative mapping of antigen specificity in adaptive immune repertoire embedding spaces
    Marina Frolenkova, Niccolò Cardente, Jahn Zhong, Evgeniy S. Egorov, Giulio Isacchini, Julien P. Limenitakis, Philipp Fleig, Puneet Rawat, Milena Pavlović, Caterina Sanetti et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
29. Fast, accurate construction of multiple sequence alignments from protein language embeddings
    Minh Hoang, Isabel Armour-Garb, Mona Singh · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
30. RF_Bert: A Classification Model of Golgi Apparatus Based on TAPE_BERT Extraction Features
    Qingyu Cui, Wenzheng Bao, Yi Cao, Bin Yang, Yuehui Chen · 2021 · Lecture notes in computer science
31. Computational approaches to discover novel enzymes for fragrance and flavour
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32. Peer Review #1 of "Navigating the amino acid sequence space between functional proteins using a deep learning framework (v0.1)"
    2021 · PeerJ Computer Science
33. Identification of Enzymatic Active Sites with Unsupervised Language Modeling
    Loıc Kwate Dassi, Matteo Manica, Daniel Probst, Philippe Schwaller, Yves Gaëtan Nana Teukam, Teodoro Laino · 2021
34. Learning representations for molecular sequences
    Dhananjay Kimothi · 2021 · Queensland University of Technology
35. Peer Review #2 of "Navigating the amino acid sequence space between functional proteins using a deep learning framework (v0.1)"
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36. Faculty Opinions recommendation of Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences.
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37. BiRDS - Binding Residue Detection from Protein Sequences using Deep ResNets
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38. Identification of Enzymatic Active Sites with Unsupervised Language Modeling
    Loıc Kwate Dassi, Matteo Manica, Daniel Probst, Philippe Schwaller, Yves Gaëtan Nana Teukam, Teodoro Laino · 2021 · ChemRxiv
39. ZeroFold-Understanding Mutations of SARS-CoV-2 Spike Protein base on Secondary Structure Event Extracting for guiding Vaccine development
    Weibin Chen, Zhiyuan Xu · 2020
40. Identification of Enzymatic Active Sites with Unsupervised Language Modeling
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41. Pre-training Protein Models with Molecular Dynamics Simulations for Drug Binding
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42. COVID-19 and SARS Virus Function Sites Classification with Machine Learning Methods
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43. Deep Learning Methods For Prediction of HLA-Peptide Interactions in IDB
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44. Automated Detection of Sockpuppet Accounts in Wikipedia
    Mostofa Najmus Sakib · 2022
45. Source Identification for Exosomal Communication via Protein Language Models
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46. APIP: Attention-based Protein Representation Learning for Protein-Ligand Interface Prediction
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47. CELL-E: zero-shot sequence-to-image synthesis for protein localization prediction
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48. T4SEpp: a pipeline integrated with protein language models effectively predicting bacterial type IV secreted effectors
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49. TAPE-Pero: Using Deep Representation Learning Model to Identify and Localize Peroxisomal Proteins
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50. Domain-PFP: Protein Function Prediction Using Function-Aware Domain Embedding Representations
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51. Hist2Vec: Kernel-Based Embeddings for Biological Sequence Classification
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52. Attention Based Approach for Molecular Property Prediction
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53. Deep-USIpred: identifying substrates of ubiquitin protein ligases E3 and deubiquitinases with pretrained protein embedding and bayesian neural network
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55. Deep Manifold Transformation for Protein Representation Learning
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56. Deep Learning-Driven Protein Design
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57. Latent-based Directed Evolution accelerated by Gradient Ascent for Protein Sequence Design
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58. Protein Design
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61. Boosting Protein Language Models with Negative Sample Mining
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62. ProTeM: Unifying Protein Function Prediction via Text Matching
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63. Recursive Cleaning for Large-scale Protein Data via Multimodal Learning
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64. VIEPred: Predicting Viral Immune Evasion with Multimodal Representation Learning
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