Article

Performance Attribution in pLM-Based Biological Relation Prediction

2026-07-02

Abstract excerpt

Protein language models (pLMs) have enabled strong performance in biological relation-prediction benchmarks, yet aggregate predictive metrics do not reveal which sources of information support that performance. We examined three pLM-based case studies—MetaESI, Deep-GNHV, and SAGEPhos—using frozen pLM-derived full-input baselines, component-restricted controls, train-derived endpoint or site priors, and selector-ma...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e11a33cc-3a12-5434-b303-441c0bd3b703
DOI: 10.64898/2026.06.28.735130

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Performance Attribution in pLM-Based Biological Relation PredictionDOI 10.64898/2026.06.28.735130Read

MINA: linear probes reveal coding-sequence family signal in frozen DNA encoders up to protein compositionSemantic proximity Read

Emergence of Biological Structural Discovery in General-Purpose Language ModelsSemantic proximity Read

Pool PaRTI: A PageRank-Based Pooling Method for Identifying Critical Residues and Enhancing Protein Sequence RepresentationsSemantic proximity Read

PIPENN-EMB: ensemble net and protein embeddings generalise protein interface prediction beyond homologySemantic proximity Read

Genomic Touchstone: Benchmarking Genomic Language Models in the Context of the Central DogmaSemantic proximity Read

BioReason-Pro: Advancing Protein Function Prediction with Multimodal Biological ReasoningSemantic proximity Read

Do Single-Cell Models Learn Real Biology? An Empirical Analysis of Physical Interaction Signal in Pretrained scGPT Gene EmbeddingsSemantic proximity Read

PIPENN-EMB: ensemble net and protein embeddings generalise protein interface prediction beyond homologySemantic proximity Read

A flaw in using pre-trained pLLMs in protein-protein interaction inference modelsSemantic proximity Read

Rapid and Reproducible Multimodal Biological Foundation Model Development with AIDO.ModelGeneratorSemantic proximity Read

BioGraphX-RNA: A Universal Physicochemical Graph Encoding for Interpretable RNA Subcellular Localization PredictionSemantic proximity Read

Counterfactual Consistency as a Metric for Biological Foundation ModelsSemantic proximity Read