Protein Language Models
PulseAugur coverage of Protein Language Models — every cluster mentioning Protein Language Models across labs, papers, and developer communities, ranked by signal.
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Lightweight Murmur2Vec embeddings match heavy PLMs in biological classification
Researchers have developed Murmur2Vec, a lightweight and efficient embedding method for biological sequence classification that rivals the performance of larger, computationally intensive protein language models (PLMs) …
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New method uses geometry to interpret protein language model features
Researchers have developed a new method to interpret the latent features within protein language models (pLMs) by using geometric annotations of protein backbones. This approach, applied to the ESM-2 model, reveals that…
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New method interprets protein language model embeddings for fitness prediction
Researchers have developed a novel method using orthogonal projection to interpret the embeddings generated by protein language models (PLMs). This technique aims to identify which biochemical properties are encoded wit…
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New 'off-manifold collapse' issue found in protein language models
Researchers have identified a critical issue in guided protein language models, termed "off-manifold collapse." This phenomenon occurs when the model's internal representations degrade to a state indistinguishable from …
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Protein language models' information distribution across layers revealed
A new study analyzing 13 protein language models (PLMs) across 15 downstream tasks has revealed that the final layers of these models do not always contain the most informative embeddings for optimal performance. Resear…
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New preference-based learning framework enhances antibody design
Researchers have developed a novel preference-based learning framework to improve antibody expression ranking, a crucial step in antibody design. This method leverages scarce quantitative expression data alongside a lar…
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Protein language models' allergen explanations lack biological grounding
A new study published on arXiv questions the biological relevance of explanations provided by protein language models used in allergenicity classification. While models like ESM-2 and DeepPlantAllergy demonstrate strong…
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New method enables protein model steering without human feedback · 2 sources tracked
Researchers have developed a new framework called unsupervised reward optimization for protein language models (PLMs). This method allows for steerable protein generation without the need for costly wet-lab validation o…
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SurfDesign framework advances protein design using surface geometry
Researchers have developed SurfDesign, a new framework for protein design that focuses on molecular surface geometry and physicochemical properties. This method integrates continuous geometric manifold modeling of surfa…
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New protein language models enhance molecular dynamics and design
Researchers are developing advanced protein language models (pLMs) to improve molecular dynamics simulations and protein design. One approach, PLaTITO, integrates protein language model embeddings to enhance the general…
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Protein language models use specialized mechanisms to detect sequence repeats
Researchers have investigated how protein language models (PLMs) identify repeating segments within protein sequences. Their findings indicate that PLMs first create feature representations using general positional atte…
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ProteinOPD framework enhances protein design alignment with 8x speedup
Researchers have developed ProteinOPD, a new framework for aligning protein language models (PLMs) with desired functions. This method adapts pretrained PLMs into specialized teachers and distills their knowledge into a…