Comparing k-mer Methods and Language Model Embeddings Under Cross-Species Evaluation

This narrative review compares k-mer-based representations and biological language-model embeddings for biological sequence analysis. It focuses on homology leakage, pretraining overlap, benchmark design, and cross-species evaluation, and proposes practical recommendations for more reliable model assessment.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-30
DOI
https://doi.org/10.5281/zenodo.21711165
Primary Topic
Bioinformatics and Genomic Networks
Type
preprint
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preprint

Comparing k-mer Methods and Language Model Embeddings Under Cross-Species Evaluation

Shivansh Sahni, Prasiddha Subedi
Zenodo (CERN European Organization for Nuclear Research)
Bioinformatics and Genomic Networks
preprint

Comparing k-mer Methods and Language Model Embeddings Under Cross-Species Evaluation

Shivansh Sahni, Prasiddha Subedi
preprint en

Abstract

This narrative review compares k-mer-based representations and biological language-model embeddings for biological sequence analysis. It focuses on homology leakage, pretraining overlap, benchmark design, and cross-species evaluation, and proposes practical recommendations for more reliable model assessment.

Zenodo (CERN European Organization for Nuclear Research)
Memorial Hermann Institute for Rehabilitation and Research Foundation (US)
Life in Land
Bioinformatics and Genomic Networks
DOIOpen Access PDFOpenAlex
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Comparing k-mer Methods and Language Model Embeddings Under Cross-Species Evaluation — Shivansh Sahni, Prasiddha Subedi · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS