TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval
The article presents TIGER, a framework designed for enzyme-reaction retrieval in computational biology. It addresses challenges in existing methods, such as poor generalization and asymmetry in retrieval directions. TIGER utilizes a Dynamic Gating Network and a Structure-Shared Feature Projector to enhance enzyme representations and improve retrieval performance.
- ▪TIGER stands for Text-Informed Generalized Enzyme-Reaction Retrieval.
- ▪The framework improves enzyme-reaction mapping by leveraging protein-to-text generation models.
- ▪Extensive experiments show that TIGER outperforms state-of-the-art methods across various distributions.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.24489 |
| Publication time | Tue, 26 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-26T04:07:43.013Z |
| Last seen | 2026-05-26T04:07:43.013Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | vWM56nFtuez1 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.24489 (cs) [Submitted on 23 May 2026] Title:TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval Authors:Yuhang Zhang, Keyan Ding, Peilin Chen, Han Liu, Can Lin, Ruixi Chen, Shiqi Wang, Qi Song View a PDF of the paper titled TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval, by Yuhang Zhang and 6 other authors View PDF HTML (experimental) Abstract:Enzyme-reaction retrieval is a fundamental problem in computational biology, underpinning enzyme characterization, reaction mechanism elucidation, and the rational design of metabolic pathways and biocatalysts. As a bidirectional task, it entails both enzyme-to-reaction and reaction-to-enzyme mapping.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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