BioGist 作者： Oric Labs
Get the biological gist of any research paper. Auto-detects genes, variants, and datasets on any webpage.
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关于此扩展
BioGist is a research sidebar that scans any webpage for biological entities and provides instant context — no uploads, no server, no account.
HOW IT WORKS
Visit a paper on PubMed, bioRxiv, Nature, or any scientific website. Open the sidebar and click Scan. BioGist detects 18 types of biological entities on the page. Click any entity for details, database links, and related papers from PubMed.
WHAT IT DETECTS
BioGist recognizes genes, variants, dataset accessions, species, bioinformatics methods, genome builds, sample sizes, statistical methods, sequencing platforms, cell lines, tissues, drugs, clinical trial IDs, funding sources, code repositories, p-values, file links, and key findings — 18 entity types in total. Gene detection uses the full HGNC set of 44,959 human gene symbols.
DETAIL PANELS
Click any detected entity to see rich details pulled from public databases. Gene panels show summaries from NCBI and UniProt. Variant panels show allele frequencies from gnomAD and clinical significance from ClinVar. DOI panels show citation counts, authors, and open access links via OpenAlex, with citation export in APA, Vancouver, Harvard, BibTeX, or RIS format.
INLINE PUBMED SEARCH
Click "Find Related Papers" in any entity detail to see the top 5 PubMed results directly in the sidebar — titles, authors, journal, and year — without leaving the page.
DATABASE LINKS
Every entity links out to relevant databases including NCBI, Ensembl, UniProt, GeneCards, OMIM, ClinicalTrials.gov, DrugBank, Cellosaurus, bio.tools, NIH Reporter, PubMed, and Google Scholar.
RESEARCH TOOLS
- Compare two papers side by side to see shared and unique entities
- Co-occurrence matrix showing which entity types appear together across tabs
- Persistent entity history with search and type filter across sessions
- Batch scan up to 20 URLs at once
- Personal annotation notes on any entity
- Export as plain text, JSON, Markdown, CSV, or BibTeX with scope and type filters
ADDITIONAL FEATURES
- Adaptive toolbar that collapses into a menu on narrow sidebars
- Multi-tab scanning with per-tab result storage
- Pin important entities across sessions
- Keyboard shortcuts for sidebar toggle and scan
- Right-click context menu for quick lookups
- Paste button for scanning text from PDFs
- Entity type toggles to show or hide any of the 18 types
- Light and dark themes
- 24-hour local caching of API results
PRIVACY
All entity detection runs locally in your browser. No page content is uploaded anywhere. The extension only contacts public APIs (NCBI, UniProt, myvariant.info, CrossRef, OpenAlex) when you click an entity to view details. No analytics, no tracking, no account required.
Report issues: https://github.com/oriclabs/biolang/issues
Built by Oric Labs — https://lang.bio
HOW IT WORKS
Visit a paper on PubMed, bioRxiv, Nature, or any scientific website. Open the sidebar and click Scan. BioGist detects 18 types of biological entities on the page. Click any entity for details, database links, and related papers from PubMed.
WHAT IT DETECTS
BioGist recognizes genes, variants, dataset accessions, species, bioinformatics methods, genome builds, sample sizes, statistical methods, sequencing platforms, cell lines, tissues, drugs, clinical trial IDs, funding sources, code repositories, p-values, file links, and key findings — 18 entity types in total. Gene detection uses the full HGNC set of 44,959 human gene symbols.
DETAIL PANELS
Click any detected entity to see rich details pulled from public databases. Gene panels show summaries from NCBI and UniProt. Variant panels show allele frequencies from gnomAD and clinical significance from ClinVar. DOI panels show citation counts, authors, and open access links via OpenAlex, with citation export in APA, Vancouver, Harvard, BibTeX, or RIS format.
INLINE PUBMED SEARCH
Click "Find Related Papers" in any entity detail to see the top 5 PubMed results directly in the sidebar — titles, authors, journal, and year — without leaving the page.
DATABASE LINKS
Every entity links out to relevant databases including NCBI, Ensembl, UniProt, GeneCards, OMIM, ClinicalTrials.gov, DrugBank, Cellosaurus, bio.tools, NIH Reporter, PubMed, and Google Scholar.
RESEARCH TOOLS
- Compare two papers side by side to see shared and unique entities
- Co-occurrence matrix showing which entity types appear together across tabs
- Persistent entity history with search and type filter across sessions
- Batch scan up to 20 URLs at once
- Personal annotation notes on any entity
- Export as plain text, JSON, Markdown, CSV, or BibTeX with scope and type filters
ADDITIONAL FEATURES
- Adaptive toolbar that collapses into a menu on narrow sidebars
- Multi-tab scanning with per-tab result storage
- Pin important entities across sessions
- Keyboard shortcuts for sidebar toggle and scan
- Right-click context menu for quick lookups
- Paste button for scanning text from PDFs
- Entity type toggles to show or hide any of the 18 types
- Light and dark themes
- 24-hour local caching of API results
PRIVACY
All entity detection runs locally in your browser. No page content is uploaded anywhere. The extension only contacts public APIs (NCBI, UniProt, myvariant.info, CrossRef, OpenAlex) when you click an entity to view details. No analytics, no tracking, no account required.
Report issues: https://github.com/oriclabs/biolang/issues
Built by Oric Labs — https://lang.bio
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更多信息
- 版本
- 1.1.0
- 大小
- 224.17 KB
- 上次更新
- 2 个月前 (2026年3月18日)
- 许可证
- MIT 许可证
- 隐私政策
- 阅读此附加组件的隐私政策
- 版本历史
- 添加到收藏集
databases. All entity detection runs locally using bundled JavaScript and the HGNC gene symbol list (44,959 symbols).
Network requests are only made when the user clicks an entity to fetch details from public APIs (NCBI, UniProt, gnomAD, ClinVar, CrossRef,
OpenAlex). No page content is uploaded to any server.
No account required. No tracking. No analytics.