Research any topic before you write.
Find related topics. | Discover entities. | See connections. | Build a topical map.
Peter Agre (* 30. ledna 1949) je americký biolog a chemik. V roce 2003 získal spolu s Roderickem MacKinnonem Nobelovu cenu za chemii za objevy týkající se akvaporinů, tedy kanálů v buněčných membránách.
The analysis highlights Život and Overview as prominent areas in the source structure around Peter Agre.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Peter Agre shows recurring relationship patterns in the source. For example, Peter Agre → NC, Obrázky, Wikimedia CommonsPeter Agre Another extracted example is Peter Agre → Augsburg University Roosevelt High School Lékařská škola Johnse Hopkinse Univerzita Johnse Hopkinse. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
30 ledna chemii 1949 chemik agre commons biolog 2003 university peter získal nobelova cena datové položky augsburg wikimedia americký akvaporinů
TTTA extracted 10 structured relationships around Peter Agre. Examples in this analysis include Peter Agre → Alma mater → Augsburg University Roosevelt High School Lékařská škola Johnse Hopkinse Univerzita Johnse Hopkinse and Peter Agre → Narození → 30. ledna 1949 (77 let) Northfield. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Peter Agre | Alma mater | Augsburg University Roosevelt High School Lékařská škola Johnse Hopkinse Univerzita Johnse Hopkinse | 1.00 | infobox |
| Peter Agre | Narození | 30. ledna 1949 (77 let) Northfield | 1.00 | infobox |
| Peter Agre | Nábož. vyznání | luteránství | 1.00 | infobox |
| Peter Agre | Občanství | Spojené státy americké | 1.00 | infobox |
| Peter Agre | Ocenění | Nobelova cena za chemii (2003) Karl Landsteiner Memorial Award (2005) společník Americké asociace pro rozvoj vědy (2005) čestná doktor Univerzity Bordeaux II (2009) George M. Ko… | 1.00 | infobox |
| Peter Agre | Povolání | chemik, molekulární biolog, vysokoškolský učitel, lékař, mikrobiolog a výzkumník | 1.00 | infobox |
| Peter Agre | Zaměstnavatelé | Univerzita Johnse Hopkinse Dukeova univerzita Lékařská škola Johnse Hopkinse | 1.00 | infobox |
| Peter Agre | related to Externí odkazy | Obrázky | 0.60 | section |
| Peter Agre | related to Externí odkazy | Wikimedia CommonsPeter Agre | 0.60 | section |
| Peter Agre | related to Externí odkazy | NC | 0.60 | section |
The concept neighborhoods around Peter Agre bring nearby vocabulary together. In this analysis, examples include Commons, Peter and Americký. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Peter Agre, one of the stronger structural bridges in this analysis connects Peter Agre with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Peter Agre to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Život & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Peter Agre · CS edition · Analysis: TopicsToTalkAbout