Research any topic before you write.
Find related topics. | Discover entities. | See connections. | Build a topical map.
In bioinformatics, miRBase is a biological database that acts as an archive of microRNA sequences and annotations. As of September 2010 it contained information about 15,172 microRNAs. This number has risen to 38,589 by March 2018. The miRBase registry provides a centralised system for assigning new names to microRNA genes.
The analysis highlights Overview, Related Topics and Entities as prominent areas in the source structure around MiRBase.
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 MiRBase shows recurring relationship patterns in the source. For example, MiRBase → Ana Kozomara Another extracted example is MiRBase → microRNA database. 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.
microrna sequences release mirnas species viridiplantae information micrornas march 2018 registry system sam griffiths-jones database ana kozomara primary bioinformatics alveolata
TTTA extracted 7 structured relationships around MiRBase. Examples in this analysis include MiRBase → Authors → Ana Kozomara and MiRBase → Description → microRNA database. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| MiRBase | Authors | Ana Kozomara | 1.00 | infobox |
| MiRBase | Description | microRNA database | 1.00 | infobox |
| MiRBase | Primary citation | Kozomara & al. (2011) | 1.00 | infobox |
| MiRBase | Release date | 2010 | 1.00 | infobox |
| MiRBase | Research center | University of Manchester | 1.00 | infobox |
| MiRBase | Website | www.mirbase.org | 1.00 | infobox |
| MiRBase | is a | biological database that acts as an archive of microRNA sequences and annotations | 0.90 | text |
The concept neighborhoods around MiRBase bring nearby vocabulary together. In this analysis, examples include Ana, Griffiths-jones and Kozomara. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Bridges highlight paths between different parts of the MiRBase map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around MiRBase to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Overview, Related Topics & Entities, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — MiRBase · EN edition · Analysis: TopicsToTalkAbout