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Keyword: Pepe ×Clear all

2 claims from 1 paper

1. Biochemistry, Genetics and Molecular Biology › Machine Learning in Bioinformatics

   PEPE: scalable extraction of multi-modal protein language model representations

   Zhong, Cardente, Sandve, Bashour, Abbate and Greiff · Bioinformatics · 2026

   The paper presents PEPE, a command-line tool and Python library for fast, memory-stable, multimodal extraction of embeddings from protein language models.

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   1. UncheckedThe PEPE tool's parallel, streaming design is reported to run several orders of magnitude faster than sequential approaches for protein embedding extraction.“PEPE’s parallelized and streaming-based architecture achieves runtimes several orders of magnitude faster than sequential approaches.”
   2. UncheckedPEPE keeps memory use low and stable when extracting protein embeddings, even beyond available RAM, whereas conventional methods' memory grows with output size.“Unlike conventional methods—whose peak memory usage scales linearly with output size and fails when memory capacity is exceeded—PEPE maintains stable, low memory consumption, enabling multimodal embedding extraction even beyond available RAM.”