Article

Unannotated Genes in Genomics: Challenges, Opportunities, and AI Solutions

2026-04-13

Abstract excerpt

The rapid proliferation of next-generation sequencing (NGS) technologies has generated an unprecedented volume of genomic data, yet a substantial fraction of these sequenced genomes remains functionally uncharacterized, a phenomenon collectively termed " genomic dark matter." Unannotated genes, including hypothetical proteins (HPs), orphan and de novo genes, small open reading frames (smORFs), and non-ca...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: bfcc6c87-33c9-53cc-a9ba-b12ac44370af
DOI: 10.20944/preprints202604.0792.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Unannotated Genes in Genomics: Challenges, Opportunities, and AI SolutionsDOI 10.20944/preprints202604.0792.v1Read

Limitations of Current Machine-Learning Models in Predicting Enzymatic Functions for Uncharacterized ProteinsSemantic proximity Read

AI and Machine Learning in Biology: From Genes to ProteinsSemantic proximity Read

AGNOSTOS-DB: a resource to unlock the uncharted regions of the coding sequence spaceSemantic proximity Read

Mining high-throughput experimental data to link gene and function.Semantic proximity Read

Targeted ortholog search in unannotated genome assemblies with fDOG-AssemblySemantic proximity Read

Breaking Through Biology's Data Wall: Expanding the Known Tree of Life by Over 10x using a Global Biodiscovery PipelineSemantic proximity Read

Functional unknomics: closing the knowledge gap to accelerate biomedical researchSemantic proximity Read

Artificial Intelligence as Accelerator for Genomic Medicine and Planetary HealthSemantic proximity Read

Thousands of missed genes found in bacterial genomes and their analysis with COMBREX.Semantic proximity Read

Real or fake? Verifying protein domain gain and loss events by an automated fact-checking approachSemantic proximity Read

Ultra-Accurate Classification and Discovery of Functional Protein-Coding Genes from Microbiomes Using FunGeneTyper: An Expandable Deep Learning-Based FrameworkSemantic proximity Read

Nearly all new protein-coding predictions in the CHESS database are not protein-codingSemantic proximity Read