Genome Understanding

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (6 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome
  26 Jun 2023 6 repositories listed Syntology ran 8 of 23 samples · 15 unverified
  Decoding the linguistic intricacies of the genome is a crucial problem in biology, and pre-trained foundational models such as DNABERT and Nucleotide Transformer have made significant strides in this area.
• GenoArmory: A Unified Evaluation Framework for Adversarial Attacks on Genomic Foundation Models
  16 May 2025 1 repository listed
  We propose the first unified adversarial attack benchmark for Genomic Foundation Models (GFMs), named GenoArmory.
• Fast and Low-Cost Genomic Foundation Models via Outlier Removal
  1 May 2025 1 repository listed Syntology ran 5 of 10 samples · 5 unverified
  Unlike existing GFM benchmarks, GERM offers the first comprehensive evaluation framework to systematically assess the vulnerability of GFMs to adversarial attacks.
• Efficient and Scalable Fine-Tune of Language Models for Genome Understanding
  12 Feb 2024 1 repository listed
  Impressively, applying these adapters on natural language foundation models matched or even exceeded the performance of DNA foundation models.
• SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study
  14 Apr 2022 1 repository listed
  We apply SNP2Vec to perform long-sequence genomics modeling, and we evaluate the effectiveness of our approach on predicting Alzheimer's disease risk in a Chinese cohort.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.