Evaluating Protein Transfer Learning with TAPE

19 June 2019

Roshan Rao

Nicholas Bhattacharya

Pieter Abbeel

Papers citing "Evaluating Protein Transfer Learning with TAPE"

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Title
Training self-supervised peptide sequence models on artificially chopped proteins Gil Sadeh Zichen Wang J. Grewal Huzefa Rangwala Layne Price 24 2 0 09 Nov 2022
Learning the shape of protein micro-environments with a holographic convolutional neural network Michael N. Pun Andrew Ivanov Quinn Bellamy Zachary Montague Colin H. LaMont P. Bradley J. Otwinowski Armita Nourmohammad 16 12 0 05 Nov 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 29 12 0 04 Nov 2022
Antibody Representation Learning for Drug Discovery Lin Li Esther Gupta J. Spaeth Leslie Shing Tristan Bepler R. Caceres 8 6 0 05 Oct 2022
Improving Generative Flow Networks with Path Regularization A. Do Duy-Tung Dinh T. Nguyen Khuong N. Nguyen Stanley Osher Nhat Ho AI4CE 23 4 0 29 Sep 2022
ImmunoLingo: Linguistics-based formalization of the antibody language Mai Ha Vu Philippe A. Robert Rahmad Akbar B. Swiatczak G. K. Sandve Dag Trygve Tryslew Haug Victor Greiff AI4CE 28 8 0 26 Sep 2022
Group Activity Recognition in Basketball Tracking Data -- Neural Embeddings in Team Sports (NETS) Sandro Hauri Slobodan Vučetić 13 8 0 31 Aug 2022
HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternative Xiaomin Fang Fan Wang Lihang Liu Jingzhou He Dayong Lin Yingfei Xiang Xiaonan Zhang Hua-Hong Wu Hui Li Le Song 14 50 0 28 Jul 2022
Learning Hierarchical Protein Representations via Complete 3D Graph Networks Limei Wang Haoran Liu Yi Liu Jerry Kurtin Shuiwang Ji GNN 33 55 0 26 Jul 2022
Linguistically inspired roadmap for building biologically reliable protein language models Mai Ha Vu Rahmad Akbar Philippe A. Robert B. Swiatczak Victor Greiff G. K. Sandve Dag Trygve Tryslew Haug 44 35 0 03 Jul 2022
ProGen2: Exploring the Boundaries of Protein Language Models Erik Nijkamp Jeffrey A. Ruffolo Eli N. Weinstein Nikhil Naik Ali Madani AI4TS 24 282 0 27 Jun 2022
PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction Sirui Liu Jun Zhang Haotian Chu Min Wang Boxin Xue ... Zidong Wang Lijiang Yang Fan Yu Lei Chen Y. Gao 3DV 16 13 0 24 Jun 2022
SSM-DTA: Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction Qizhi Pei Lijun Wu Jinhua Zhu Yingce Xia Shufang Xia Tao Qin Haiguang Liu Tie-Yan Liu Rui Yan 13 20 0 20 Jun 2022
Evaluating Self-Supervised Learning for Molecular Graph Embeddings Hanchen Wang Jean Kaddour Shengchao Liu Jian Tang Joan Lasenby Qi Liu 27 20 0 16 Jun 2022
Exploring evolution-aware & -free protein language models as protein function predictors Min Hu Fajie Yuan Kevin Kaichuang Yang Fusong Ju Jingyu Su Hongya Wang Fei Yang Qiuyang Ding 21 36 0 14 Jun 2022
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding Minghao Xu Zuobai Zhang Jiarui Lu Zhaocheng Zhu Yang Zhang Chang Ma Runcheng Liu Jian Tang 11 98 0 05 Jun 2022
Contrastive Representation Learning for 3D Protein Structures Pedro Hermosilla Timo Ropinski 3DV 46 51 0 31 May 2022
Approximate Conditional Coverage & Calibration via Neural Model Approximations A. Schmaltz Danielle Rasooly UQCV 8 0 0 28 May 2022
Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval Pascal Notin M. Dias J. Frazer Javier Marchena-Hurtado Aidan N. Gomez D. Marks Y. Gal 55 177 0 27 May 2022
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution Lixue Cheng Ziyi Yang Chang-Yu Hsieh Ben Liao Shengyu Zhang 25 6 0 19 May 2022
RITA: a Study on Scaling Up Generative Protein Sequence Models Daniel Hesslow Niccoló Zanichelli Pascal Notin Iacopo Poli D. Marks 18 91 0 11 May 2022
Structure-aware Protein Self-supervised Learning Can Chen Jingbo Zhou Fan Wang Xue Liu Dejing Dou SSL 15 65 0 06 Apr 2022
Multi-Scale Representation Learning on Proteins Vignesh Ram Somnath Charlotte Bunne Andreas Krause 32 91 0 04 Apr 2022
Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs Jiying Zhang Fuyang Li Xi Xiao Tingyang Xu Yu Rong Junzhou Huang Yatao Bian GNN 13 24 0 31 Mar 2022
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders Samuel Stanton Wesley J. Maddox Nate Gruver Phillip M. Maffettone E. Delaney Peyton Greenside A. Wilson BDL 36 89 0 23 Mar 2022
Protein Representation Learning by Geometric Structure Pretraining Zuobai Zhang Minghao Xu Arian R. Jamasb Vijil Chenthamarakshan A. Lozano Payel Das Jian Tang SSL 13 217 0 11 Mar 2022
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization Brandon Trabucco Xinyang Geng Aviral Kumar Sergey Levine OffRL 26 95 0 17 Feb 2022
Improving Molecular Representation Learning with Metric Learning-enhanced Optimal Transport Fang Wu Nicolas Courty Shuting Jin Stan Z. Li OOD OT 21 8 0 13 Feb 2022
Prompt-Guided Injection of Conformation to Pre-trained Protein Model Qiang Zhang Zeyuan Wang Yuqiang Han Haoran Yu Xurui Jin Huajun Chen 28 3 0 07 Feb 2022
Regression Transformer: Concurrent sequence regression and generation for molecular language modeling Jannis Born Matteo Manica 13 91 0 01 Feb 2022
ReLSO: A Transformer-based Model for Latent Space Optimization and Generation of Proteins Egbert Castro Abhinav Godavarthi Julian Rubinfien Kevin B. Givechian Dhananjay Bhaskar Smita Krishnaswamy 38 5 0 24 Jan 2022
OntoProtein: Protein Pretraining With Gene Ontology Embedding Ningyu Zhang Zhen Bi Xiaozhuan Liang Shuyang Cheng Haosen Hong Shumin Deng J. Lian Qiang Zhang Huajun Chen 99 90 0 23 Jan 2022
Mitigating cold start problems in drug-target affinity prediction with interaction knowledge transferring T. Nguyen Thin Nguyen T. Tran 8 14 0 16 Jan 2022
Multimodal Pre-Training Model for Sequence-based Prediction of Protein-Protein Interaction Yang Xue Zijing Liu Xiaomin Fang Fan Wang 9 8 0 09 Dec 2021
An Effective GCN-based Hierarchical Multi-label classification for Protein Function Prediction Kyudam Choi Yurim Lee Cheongwon Kim MinSung Yoon 16 7 0 06 Dec 2021
Meta-Learning to Improve Pre-Training Aniruddh Raghu Jonathan Lorraine Simon Kornblith Matthew B. A. McDermott David Duvenaud 19 30 0 02 Nov 2021
Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model Liang He Shizhuo Zhang Lijun Wu Huanhuan Xia Fusong Ju ... Jianwei Zhu Pan Deng Bin Shao Tao Qin Tie-Yan Liu 26 31 0 29 Oct 2021
Pre-trained Language Models in Biomedical Domain: A Systematic Survey Benyou Wang Qianqian Xie Jiahuan Pei Zhihong Chen Prayag Tiwari Zhao Li Jie Fu LM&MA AI4CE 37 163 0 11 Oct 2021
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 31 13 0 06 Oct 2021
Machine learning modeling of family wide enzyme-substrate specificity screens Samuel Goldman Ria Das Kevin Kaichuang Yang Connor W. Coley 17 54 0 08 Sep 2021
Deep Generative Modeling for Protein Design Alexey Strokach Philip M. Kim AI4CE 179 90 0 31 Aug 2021
Modeling Protein Using Large-scale Pretrain Language Model Yijia Xiao J. Qiu Ziang Li Chang-Yu Hsieh Jie Tang 11 28 0 17 Aug 2021
Adaptive Residue-wise Profile Fusion for Low Homologous Protein SecondaryStructure Prediction Using External Knowledge Qin Wang JunChao Wei Boyuan Wang Zhen Li Sheng Wang Shuguang Cui 13 1 0 05 Aug 2021
Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers Dan Rothermel Margaret Li Tim Rocktaschel Jakob N. Foerster 17 6 0 26 Jul 2021
Conservative Objective Models for Effective Offline Model-Based Optimization Brandon Trabucco Aviral Kumar Xinyang Geng Sergey Levine OffRL 42 86 0 14 Jul 2021
Dual-view Molecule Pre-training Jinhua Zhu Yingce Xia Tao Qin Wen-gang Zhou Houqiang Li Tie-Yan Liu AI4CE 27 51 0 17 Jun 2021
A Novel Framework Integrating AI Model and Enzymological Experiments Promotes Identification of SARS-CoV-2 3CL Protease Inhibitors and Activity-based Probe F. Hu Lei Wang Yishen Hu Dongqi Wang Weijie Wang J. Jiang Nan Li P. Yin 14 11 0 29 May 2021
Protein sequence-to-structure learning: Is this the end(-to-end revolution)? É. Laine Stephan Eismann A. Elofsson Sergei Grudinin OOD 3DV 23 34 0 16 May 2021
Random Embeddings and Linear Regression can Predict Protein Function Tianyu Lu Alex X. Lu Alan M. Moses SSL 14 5 0 25 Apr 2021
Protein sequence design with deep generative models Zachary Wu Kadina E. Johnston F. Arnold Kevin Kaichuang Yang 19 134 0 09 Apr 2021