REPOGEO REPORT · LITE
lucidrains/alphafold2
Default branch main · commit 931466e4 · scanned 5/28/2026, 11:07:00 PM
GitHub: 1,633 stars · 266 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface lucidrains/alphafold2, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Clarify current purpose as the PyTorch translation in README opening
Why:
CURRENTTo eventually become an unofficial working Pytorch implementation of Alphafold2, the breathtaking attention network that solved CASP14. Will be gradually implemented as more details of the architecture is released. Once this is replicated, I intend to fold all available amino acid sequences out there in-silico and release it as an academic torrent, to further science. If you are interested in replication efforts, please drop by #alphafold at this Discord channel Update: Deepmind has open sourced the official code in Jax, along with the weights 🙏! This repository will now be geared towards a straight pytorch translation with some improvements on positional encoding
COPY-PASTE FIXThis repository provides a straight PyTorch translation of DeepMind's AlphaFold2, with improvements on positional encoding, making the groundbreaking protein structure prediction model accessible to the PyTorch ecosystem.
- mediumabout#2Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIXhttps://github.com/lucidrains/alphafold2
- lowtopics#3Add 'pytorch' and 'protein-structure-prediction' to repository topics
Why:
CURRENTartificial-intelligence, attention-mechanism, deep-learning, protein-folding
COPY-PASTE FIXartificial-intelligence, attention-mechanism, deep-learning, protein-folding, pytorch, protein-structure-prediction
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- OpenFold · recommended 2×
- RoseTTAFold · recommended 2×
- ESMFold · recommended 2×
- OmegaFold · recommended 1×
- AlphaFold · recommended 1×
- CATEGORY QUERYHow can I use deep learning to predict protein structures from amino acid sequences?you: #1AI recommended (in order):
- AlphaFold2 ← you
- OpenFold
- RoseTTAFold
- ESMFold
- OmegaFold
- AlphaFold
- trRosetta
Show full AI answer
- CATEGORY QUERYLooking for a PyTorch-based solution for protein structure prediction using attention mechanisms.you: not recommendedAI recommended (in order):
- OpenFold
- ESMFold
- RoseTTAFold
- DeepMind's AlphaFold
- TrRosetta
AI recommended 5 alternatives but never named lucidrains/alphafold2. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of lucidrains/alphafold2?passAI did not name lucidrains/alphafold2 — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts lucidrains/alphafold2 in production, what risks or prerequisites should they evaluate first?passAI named lucidrains/alphafold2 explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo lucidrains/alphafold2 solve, and who is the primary audience?passAI named lucidrains/alphafold2 explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of lucidrains/alphafold2. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
[](https://repogeo.com/en/r/lucidrains/alphafold2)<a href="https://repogeo.com/en/r/lucidrains/alphafold2"><img src="https://repogeo.com/badge/lucidrains/alphafold2.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
lucidrains/alphafold2 — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite