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Updated: Jul 12, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

GUANinE v1.0: Benchmark Datasets for Genomic AI Sequence-to-Function Models.

Eyes S Robson¹, Nilah M Ioannidis²

¹Center for Computational Biology, UC Berkeley, Berkeley, CA 94720.

Biorxiv : the Preprint Server for Biology

|October 31, 2023

Summary

This summary is machine-generated.

We introduce GUANinE, a large-scale genomic AI benchmark for evaluating model generalization. This benchmark aids in advancing genomic artificial intelligence (AI) by providing de-noised tasks for functional genomics and evolutionary biology.

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Area of Science:

Computational genomics
Artificial Intelligence (AI)
Bioinformatics

Background:

Machine learning is crucial for genome interpretation, but lacks standardized evaluation methods.
Advancements in AI fields like benchmarking and auditing are needed for genomic AI.
Existing benchmarks are insufficient for evaluating modern neural sequence-to-function models.

Conclusions:

GUANinE addresses the need for standardized, large-scale evaluation in genomic AI.
The benchmark supports the assessment of self-supervised learning methods in genomics.
GUANinE offers a platform for future refinement and expansion as genomic AI matures.