{"schema_version":"onlylabs.public_signal.v1","title":"Google (DeepMind / Gemini) Repo: google-deepmind/nuclease_design","description":"Google (DeepMind / Gemini) repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/30b8652f-9e37-482e-bd57-1933b1128a3f","json_url":"https://onlylabs.fyi/signals/30b8652f-9e37-482e-bd57-1933b1128a3f/signal.json","generated_at":"2026-06-11T03:56:52.676378+00:00","org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/google-deepmind","dossier_json_url":"https://onlylabs.fyi/labs/google-deepmind/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/30b8652f-9e37-482e-bd57-1933b1128a3f","signal_json":"https://onlylabs.fyi/signals/30b8652f-9e37-482e-bd57-1933b1128a3f/signal.json","source":"https://github.com/google-deepmind/nuclease_design","lab_dossier":"https://onlylabs.fyi/labs/google-deepmind","lab_dossier_json":"https://onlylabs.fyi/labs/google-deepmind/dossier.json","analysis":"https://onlylabs.fyi/analysis/google-deepmind","analysis_json":"https://onlylabs.fyi/analysis/google-deepmind/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/google-deepmind/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"Google (DeepMind / Gemini) published google-deepmind/nuclease_design (Jupyter Notebook). This repository signal exposes tooling, eval, infrastructure, or model-adjacent work before it may appear in a launch post. 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repositories can expose organization build priorities early, especially around internal tooling, eval infrastructure, data systems, deployment, and agent workflows.","required_sources":[{"label":"signal_json","url":"https://onlylabs.fyi/signals/30b8652f-9e37-482e-bd57-1933b1128a3f/signal.json","required":true},{"label":"source","url":"https://github.com/google-deepmind/nuclease_design","required":true},{"label":"dossier_json","url":"https://onlylabs.fyi/labs/google-deepmind/dossier.json","required":true},{"label":"analysis_evidence_json","url":"https://onlylabs.fyi/analysis/google-deepmind/evidence.json","required":true},{"label":"topic_signals_json","url":null,"required":false},{"label":"data_radar_json","url":null,"required":false}],"expected_output":["one-paragraph source-grounded interpretation","category-specific implication","confidence and missing evidence","recommended next source to inspect"],"prompt_seed":"Using only the linked onlylabs JSON, captured source context, and 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infrastructure, model-adjacent, or product work before it appears in polished launch channels.."},{"subject":"google-deepmind/nuclease_design","predicate":"has source host","object":"github.com","text":"google-deepmind/nuclease_design has source host github.com."},{"subject":"google-deepmind/nuclease_design","predicate":"has lab","object":"Google (DeepMind / Gemini)","text":"google-deepmind/nuclease_design has lab Google (DeepMind / Gemini)."},{"subject":"google-deepmind/nuclease_design","predicate":"has signal desk","object":"repos","text":"google-deepmind/nuclease_design has signal desk repos."},{"subject":"google-deepmind/nuclease_design","predicate":"has source host","object":"github.com","text":"google-deepmind/nuclease_design has source host github.com."},{"subject":"google-deepmind/nuclease_design","predicate":"has repository","object":"google-deepmind/nuclease_design","text":"google-deepmind/nuclease_design has repository 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This repository signal exposes tooling, eval, infrastructure, or model-adjacent work before it may appear in a launch post. 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Analyzing our enzyme activity dataset You can use our dataset of estimated enzyme activity for 55,760 NucB variants to develop new machine learning models or to generate new insights about NucB. A csv of the dataset can be found in [data/landscape.csv](data/landscape.csv) A simple notebook has been provided to load and analyze the data: [](https://colab.research.google.com/github/google-deepmind/nuclease_design/blob/main/notebooks/plot_landscape_analysis.ipynb )
..."},"evidence_pages":[{"url":"https://github.com/google-deepmind/nuclease_design","final_url":"https://github.com/google-deepmind/nuclease_design","title":"google-deepmind/nuclease_design repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T03:56:52.676378+00:00","bytes":14782,"raw_path":"c251cf97d12cb460e24e5b7f2b00b3a4691b3defed3bbd4375b6d6752ae301a0.json","content_hash":"060d13def70afd176aa1e1e09ae6bbabd6ddebd3e7a02afb0532cbff1f6a2ca1","excerpt_chars":1200,"truncated":true,"excerpt":"google-deepmind/nuclease_design Description: ML-guided enzyme engineering Language: Jupyter Notebook License: Apache-2.0 Stars: 84 Forks: 20 Open issues: 1 Created: 2024-02-21T00:14:12Z Pushed: 2026-04-13T22:37:16Z Default branch: main Fork: no Archived: no README: ML-Guided Directed Evolution for Engineering a Better Nuclease Enzyme This repository accompanies the paper: [Engineering highly active and diverse nuclease enzymes by combining machine learning and ultra-high-throughput screening](https://doi.org/10.1101/2024.03.21.585615)
Analyzing our enzyme activity dataset You can use our dataset of estimated enzyme activity for 55,760 NucB variants to develop new machine learning models or to generate new insights about NucB. A csv of the dataset can be found in [data/landscape.csv](data/landscape.csv) A simple notebook has been provided to load and analyze the data: [](https://colab.research.google.com/github/google-deepmind/nuclease_design/blob/main/notebooks/plot_landscape_analysis.ipynb )
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