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Virofág: Druhy, Systematika & Význam
Virofágy (z latinského virus – jed a řeckého φάγειν fágein – jíst) jsou malé viry s dvouřetězcovou DNA, které pro infekci hostitele vyžadují spoluinfekci jiného viru. Spoluinfikující viry jsou obvykle obří viry. Virofágy se při vlastní replikaci spoléhají na replikační aparát spoluinfikujícího obřího viru. Jednou z vlastností virofágů je jejich…
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Virofág topic overview
The analysis highlights Druhy, Systematika and Význam as prominent areas in the source structure around Virofág.
Related topics
57
Source areas
5
Connected nodes
62
Extracted relationships
69
Concept neighborhoods
31
Bridge connections
62
What this topic covers Research coverage
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.
Druhy · 35 topics
Systematika · 13 topics
Overview · 5 topics
Význam · 3 topics
Odkazy · 1 topics
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.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Kmen
Preplasmiviricota
Realm
Varidnaviria
Skupina
I (dsDNA viry)
Třída
Maveriviricetes
Říše
Bamfordvirae
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
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.
How Virofág connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Virofág shows recurring relationship patterns in the source. For example, Virofág → Burquivirus, BurtonviroviridaeRod, Cafeteriavirus-dependent, DishuiviroviridaeRod, DivpeviralesČeleď, Essdubovirus, GulliviroviridaeRod, ICTV, Invirovirus, Ke, LavidaviralesČeleď, Maveriviricetes, MaveriviricetesŘád, MaviroviridaeRod, Mavirus, Mimivirus-dependent, MividaviralesČeleď, OmnilimnoviroviridaeRod, Oviruvirus, Panaquavirovirus Another extracted example is Virofág → Acanthamoeba, DNA, Do, Dosud, Je, Jeho, Lentille, Mamaviru, Mamavirus, Miers Valley, Mimiviridae, Mimivirus, Mont1, Obsahuje, Phaeocystis, První, Sputnik, Zamilon. Use these groups to spot repeated connection types before inspecting the individual relationships.
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 69 structured relationships around Virofág. Examples in this analysis include Virofág → Kmen → Preplasmiviricota and Virofág → Realm → Varidnaviria. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Virofág
Kmen
Preplasmiviricota
1.00
infobox
Virofág
Realm
Varidnaviria
1.00
infobox
Virofág
Skupina
I (dsDNA viry)
1.00
infobox
Virofág
Třída
Maveriviricetes
1.00
infobox
Virofág
Říše
Bamfordvirae
1.00
infobox
Virofág
related to Aktuální podoba systému
Ke
0.60
section
Virofág
related to Aktuální podoba systému
ICTV
0.60
section
Virofág
related to Aktuální podoba systému
Všechny
0.60
section
Virofág
related to Aktuální podoba systému
Maveriviricetes
0.60
section
Virofág
related to Aktuální podoba systému
Třída
0.60
section
Virofág
related to Aktuální podoba systému
MaveriviricetesŘád
0.60
section
Virofág
related to Aktuální podoba systému
DivpeviralesČeleď
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Virofág bring nearby vocabulary together. In this analysis, examples include Objeven, Sputnik and Objevený. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
ace lake mavirus
Virophage
Yellowstone
Sputnik
Virus
Dishui
Zamilon
Virophages
Virofágy
Virofágů
Později
Rodu
Stejné
dishui lake virophages
Virophage
Yellowstone
Dishui
Lake
Rodu
Virofágy
Čeledi
Jeho
Virophages
Jsou
Virofágů
Později
phaeocystis globosa virus virophage
Lake
Mavirus
Dishui
Yellowstone
Zamilon
Druhy
Linie
Sputnik
Vývojové
Viru
Virophage
Virus
organic lake virophage
Lake
Virophage
Yellowstone
Dishui
Virophages
Virus
Virofágy
Virofágů
Později
Rodu
Stejné
Čeledi
qinghai lake virophage
Lake
Virophage
Yellowstone
Dishui
Virophages
Virus
Virofágy
Virofágů
Později
Rodu
Stejné
Čeledi
dna
Hostitele
Jsou
Viru
Viry
Virů
Obřího
Replikaci
Spoluinfikující
Bp
Genom
Ke
Jako
dna polymerázy
Hostitele
Jsou
Viru
Viry
Virů
Obřího
Replikaci
Spoluinfikující
Bp
Genom
Ke
Jako
sekvence dna
Hostitele
Jsou
Viru
Viry
Virů
Obřího
Replikaci
Spoluinfikující
Bp
Genom
Ke
Jako
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Virofág, one of the stronger structural bridges in this analysis connects Virofág with Druhy. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Virofág
Nodes63
Edges62
Triples69
Avg. degree1.97
Density0.031746
Components1
Source & methodology
TTTA analyzes the structure around Virofág to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Druhy, Systematika & Význam, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
