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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Related Experiment Video

Updated: Jul 24, 2025

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution.

Eric Nguyen, Michael Poli, Marjan Faizi

    Arxiv
    |July 10, 2023
    PubMed
    Summary

    HyenaDNA, a new genomic foundation model, processes DNA sequences at single nucleotide resolution with unprecedented long-context capabilities. This model achieves state-of-the-art performance on multiple benchmarks, outperforming previous methods significantly.

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    Area of Science:

    • Genomics
    • Computational Biology
    • Machine Learning

    Background:

    • Genomic sequences contain vast information for gene regulation and protein synthesis.
    • Foundation models in genomics aim to learn generalizable features from unlabeled genome data.
    • Previous Transformer-based models had limited context length (4k tokens) and lost single nucleotide resolution.

    Conclusions:

    • HyenaDNA significantly advances genomic sequence modeling through extended context and single nucleotide resolution.
    • The model offers superior performance with fewer parameters and less pretraining data.
    • HyenaDNA unlocks new possibilities in genomics, including in-context learning.