AI-powered protein structure predictions
AlphaFold Protein Structure Database (ebi.ac.uk) scores 64 out of 100 on Brand Analyzer, placing it in the Developing tier among Healthcare brands, Education brands, Technology brands, in the 11th percentile of 7414 Healthcare brands.
AlphaFold Protein Structure Database (AlphaFold DB) is an open-access online resource providing AI-generated predictions of protein three-dimensional structures. Developed through a collaboration between Google DeepMind and EMBL-EBI, it hosts over 200 million predicted structures with accuracy comparable to experimental methods. The database is designed to accelerate scientific research by giving scientists, researchers, and academic institutions free access to structural data for use in molecular biology, biochemistry, and drug discovery.
| Brand Name | AlphaFold Protein Structure Database |
|---|---|
| Domain | ebi.ac.uk |
| Industry | Healthcare, Education |
| Main Competitors | RCSB Protein Data Bank (88/100), UniProt (92/100), SWISS-MODEL, ESMFold (Meta AI) (63/100), RoseTTAFold (Institute for Protein Design) |
Moz Domain Authority 75/100 vs category average 40 / leader 95 - a strong backlink profile, so AI systems frequently encounter mentions of the brand.
No Wikipedia presence was found - a major gap, since Wikipedia is among the most heavily weighted sources in AI training data.
The homepage meta description reads "AlphaFold Protein Structure Database" (Meta description too short (4 words). No OG description (falling back to meta)) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: No structured data or Open Graph tags detected. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: robots.txt present, no AI bot restrictions - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Detected tech stack: Express, Ghost, Angular.
Social footprint: verified profiles on GitHub, X (Twitter), Instagram; no detected presence on LinkedIn, Facebook, YouTube - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
Live results from asking a general-purpose AI assistant about the brand, checked September 2026.
When asked "What is EMBL-EBI?", Claude could identify the brand as of September 2026. EMBL-EBI (European Bioinformatics Institute) is part of the European Molecular Biology Laboratory and provides freely available data and bioinformatics services to the scientific community, including databases like Ensembl, UniProt, and PDBe. Best known for Hosting and maintaining major open-access biological databases such as UniProt, Ensembl, and the European Nucleotide Archive.
When asked "Best brands similar to EMBL-EBI?", Claude would recommend AlphaFold Protein Structure Database as of September 2026. It's a leading, widely trusted resource in bioinformatics and life sciences education, so it would naturally come up when discussing top institutions for biological data and training.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
AlphaFold Protein Structure Database's main competitors in Healthcare: RCSB Protein Data Bank (88/100), UniProt (92/100), ESMFold (Meta AI) (63/100).
Sources: Brand Analyzer scan
AlphaFold Protein Structure Database (AlphaFold DB) is an open-access scientific database that provides AI-generated predictions of protein three-dimensional structures. It was developed jointly by Google DeepMind and EMBL-EBI and contains over 200 million predicted protein structures, offering accuracy competitive with experimental structural biology methods such as X-ray crystallography and cryo-EM.
AlphaFold Protein Structure Database has limited AI-search visibility, scoring 35/100 on Brand Analyzer's AI visibility composite (visibility 13, trust 37, recommendation 71). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
AlphaFold DB offers a searchable, open-access database of AI-predicted protein three-dimensional structures. Users can browse, search, and download predicted structural models for proteins across many organisms, supporting research applications such as molecular biology studies, biochemical analysis, and drug discovery efforts.
AlphaFold Protein Structure Database scores 71/100 on Brand Analyzer's AI recommendation signal, indicating it is reasonably likely to be surfaced when AI assistants like ChatGPT suggest Healthcare options. Recommendation depends on crawlability, structured data, and category authority.
AlphaFold DB is known for providing free access to over 200 million AI-predicted protein structures, generated using the AlphaFold deep learning system developed by Google DeepMind in partnership with EMBL-EBI. It is widely recognized for making highly accurate structural predictions available at a scale previously impossible with experimental methods alone, significantly expanding the known structural coverage of proteins across many species.
AlphaFold DB is considered a trustworthy scientific resource because it is maintained by EMBL-EBI, a respected public bioinformatics institute, in collaboration with Google DeepMind, and its predictions have been validated as competitive in accuracy with experimental structural methods. It is widely used and cited within the scientific research community, supporting its credibility as a reliable source of protein structure data.
AlphaFold Protein Structure Database can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
AlphaFold DB is used by scientists, researchers, and academic institutions working in molecular biology, biochemistry, and bioinformatics. It is particularly valuable to those involved in structural biology and drug discovery who need protein structure data for their research.
AlphaFold DB is popular because it offers free, open access to a massive collection of highly accurate AI-predicted protein structures, eliminating the need for time-consuming and expensive experimental methods. Its scale-over 200 million structures-and the scientific credibility of its developers, Google DeepMind and EMBL-EBI, have made it a valuable tool for researchers in molecular biology, biochemistry, and drug discovery worldwide.
AlphaFold Protein Structure Database scores 35/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
AlphaFold Protein Structure Database has a weak AI-visibility profile at 35/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is recommendation likelihood (71/100) and its weakest is visibility (13/100). It benefits from a Wikidata knowledge-graph entry, a Moz Domain Authority of 75/100 and open access for AI crawlers (GPTBot, ClaudeBot, etc.). The main gaps holding it back: no clear Wikipedia entity to anchor it in LLM training data, thin schema.org structured data and no llms.txt to steer AI to its best pages. In a live check, Claude could already identify AlphaFold Protein Structure Database from memory (September 2026) - a sign these signals are paying off.
The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark.
64 in September 2026, down from 79 in September 2026.
Ranked closest to AlphaFold Protein Structure Database: DysTech (64/100), DSO Market Watch (64/100), EceptionistCX (64/100), Elensia (64/100).
A step up - brands to learn from: ZT Corporate (71/100), Zaina AI (71/100).
Category leader: Booksy (96/100).
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