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Polygraph: A Software Framework for the Systematic Assessment of Synthetic Regulatory DNA Elements

Authors: Avantika Lal; Laura Gunsalus; Anay Gupta; Tommaso Biancalani; Gokcen Eraslan;

Polygraph: A Software Framework for the Systematic Assessment of Synthetic Regulatory DNA Elements

Abstract

Abstract The design of regulatory elements is pivotal in gene and cell therapy, where DNA sequences are engineered to drive elevated and cell-type specific expression. However, the systematic assessment of synthetic DNA sequences without robust metrics and easy-to-use software remains challenging. Here, we introduce Polygraph, a Python framework that evaluates synthetic DNA elements, based on features like diversity, motif and k-mer composition, similarity to endogenous sequences, and screening with predictive and foundational models. Polygraph is the first instrument for assessing synthetic regulatory sequences, enabling faster progress in therapeutic interventions and improving our understanding of gene regulatory mechanisms.

Keywords

QH301-705.5, DNA, QH426-470, Regulatory Sequences, Nucleic Acid, Sequence modeling, machine learning, regulatory genomics, Sequence design, Machine learning, Genetics, Regulatory genomics, Humans, Biology (General), sequence design, Synthetic biology, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
4
Top 10%
Average
Top 10%
6
1
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gold