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Related papers: Protein as a Second Language for LLMs

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We propose ProtLLM, a versatile cross-modal large language model (LLM) for both protein-centric and protein-language tasks. ProtLLM features a unique dynamic protein mounting mechanism, enabling it to handle complex inputs where the natural…

Biomolecules · Quantitative Biology 2024-03-14 Le Zhuo , Zewen Chi , Minghao Xu , Heyan Huang , Heqi Zheng , Conghui He , Xian-Ling Mao , Wentao Zhang

Protein language models learn powerful representations directly from sequences of amino acids. However, they are constrained to generate proteins with only the set of amino acids represented in their vocabulary. In contrast, chemical…

Biomolecules · Quantitative Biology 2023-08-21 Daniel Flam-Shepherd , Kevin Zhu , Alán Aspuru-Guzik

Current Large Language Models (LLMs) for understanding proteins primarily treats amino acid sequences as a text modality. Meanwhile, Protein Language Models (PLMs), such as ESM-2, have learned massive sequential evolutionary knowledge from…

Machine Learning · Computer Science 2024-12-17 Nuowei Liu , Changzhi Sun , Tao Ji , Junfeng Tian , Jianxin Tang , Yuanbin Wu , Man Lan

Existing Protein Language Models (PLMs) often suffer from limited adaptability to multiple tasks and exhibit poor generalization across diverse biological contexts. In contrast, general-purpose Large Language Models (LLMs) lack the…

Machine Learning · Computer Science 2026-02-23 Yujia Wang , Jihong Guan , Wengen Li , Shuigeng Zhou , Xuhong Wang

Protein language models (pLMs), pre-trained via causal language modeling on protein sequences, have been a promising tool for protein sequence design. In real-world protein engineering, there are many cases where the amino acids in the…

Machine Learning · Computer Science 2023-03-30 Youhan Lee , Hasun Yu

Understanding protein sequences is vital and urgent for biology, healthcare, and medicine. Labeling approaches are expensive yet time-consuming, while the amount of unlabeled data is increasing quite faster than that of the labeled data due…

Computation and Language · Computer Science 2021-11-01 Liang He , Shizhuo Zhang , Lijun Wu , Huanhuan Xia , Fusong Ju , He Zhang , Siyuan Liu , Yingce Xia , Jianwei Zhu , Pan Deng , Bin Shao , Tao Qin , Tie-Yan Liu

Protein language models are a powerful tool for learning protein representations through pre-training on vast protein sequence datasets. However, traditional protein language models lack explicit structural supervision, despite its…

Biomolecules · Quantitative Biology 2024-02-09 Zuobai Zhang , Jiarui Lu , Vijil Chenthamarakshan , Aurélie Lozano , Payel Das , Jian Tang

Protein language models (PLMs) have shown promise in improving the understanding of protein sequences, contributing to advances in areas such as function prediction and protein engineering. However, training these models from scratch…

Machine Learning · Computer Science 2024-12-19 Shivasankaran Vanaja Pandi , Bharath Ramsundar

Protein research is crucial in various fundamental disciplines, but understanding their intricate structure-function relationships remains challenging. Recent Large Language Models (LLMs) have made significant strides in comprehending…

Computational Engineering, Finance, and Science · Computer Science 2025-01-24 Chao Wang , Hehe Fan , Ruijie Quan , Yi Yang

Protein language models (PLMs) have emerged as powerful tools to detect complex patterns of protein sequences. However, the capability of PLMs to fully capture information on protein sequences might be limited by focusing on single…

Machine Learning · Computer Science 2025-05-27 Hazem Alsamkary , Mohamed Elshaffei , Mohamed Elkerdawy , Ahmed Elnaggar

Protein language models (PLMs) have demonstrated remarkable success in protein modeling and design, yet their internal mechanisms for predicting structure and function remain poorly understood. Here we present a systematic approach to…

Biomolecules · Quantitative Biology 2024-12-18 Elana Simon , James Zou

Protein language models (pLMs) pre-trained on vast protein sequence databases excel at various downstream tasks but often lack the structural knowledge essential for some biological applications. To address this, we introduce a method to…

Protein design aims to compose amino-acid sequences that fold into stable three-dimensional structures while satisfying targeted functional properties. The field is increasingly shifting toward vibe protein design, where a single model is…

Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models taken from NLP. These LMs reach for new prediction frontiers at low inference costs. Here, we trained two…

Proteins are essential macromolecules defined by their amino acid sequences, which determine their three-dimensional structures and, consequently, their functions in all living organisms. Therefore, generative protein modeling necessitates…

Machine Learning · Computer Science 2024-10-18 Xinyou Wang , Zaixiang Zheng , Fei Ye , Dongyu Xue , Shujian Huang , Quanquan Gu

Current protein language models (PLMs) learn protein representations mainly based on their sequences, thereby well capturing co-evolutionary information, but they are unable to explicitly acquire protein functions, which is the end goal of…

Biomolecules · Quantitative Biology 2023-07-06 Minghao Xu , Xinyu Yuan , Santiago Miret , Jian Tang

At the intersection of the rapidly growing biological data landscape and advancements in Natural Language Processing (NLP), protein language models (PLMs) have emerged as a transformative force in modern research. These models have achieved…

Biomolecules · Quantitative Biology 2025-02-12 Lei Wang , Xudong Li , Han Zhang , Jinyi Wang , Dingkang Jiang , Zhidong Xue , Yan Wang

Proteins are fundamental biological entities that play a key role in life activities. The amino acid sequences of proteins can be folded into stable 3D structures in the real physicochemical world, forming a special kind of…

Machine Learning · Computer Science 2023-01-04 Lirong Wu , Yufei Huang , Haitao Lin , Stan Z. Li

The 21st century is presenting humankind with unprecedented environmental and medical challenges. The ability to design novel proteins tailored for specific purposes could transform our ability to respond timely to these issues. Recent…

Biomolecules · Quantitative Biology 2022-08-24 Noelia Ferruz , Birte Höcker

Given usefulness of protein language models (LMs) in structure and functional inference, RNA LMs have received increased attentions in the last few years. However, these RNA models are often not compared against the same standard. Here, we…

Biomolecules · Quantitative Biology 2025-05-15 He Wang , Yikun Zhang , Jie Chen , Jian Zhan , Yaoqi Zhou