MatrixDB

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MatrixDB topic overview

The analysis highlights Overview, Related Topics and Entities as prominent areas in the source structure around MatrixDB.

Related topics: 12
Source areas: 1
Connected nodes: 13
Extracted relationships: 9
Related term clusters: 12
Bridge connections: 13

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.

Overview · 12 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.

Authors: Emilie Chautard, Guillaume Launay, Nicolas Thierry-Mieg, Romain Salza, Franck Peysselon, Marie Fatoux-Ardore, Sofiane Badaoui, Sylvain Vallet, Lionel Ballut, Dorian Multedo, Syl…
Data types captured: Interactions DataBase, Biochemestry, Biacore, SPR
Description: extracellular matrix interactions database.
Laboratory: IBCP - UMR5086 CNRS / Univ Lyon1 - FRANCE
Organisms: All (Human only possible)
Standards: PSI-MI

Start with your topic. Discover where to go next.

Explore different angles and find fresh ideas to shape your next piece of content.

MatrixDB

5Biological database · Extracellular · Proteins

7UniGene · Human Protein Atlas · Cytoscape

Explore all related topics Closing gaps

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.

Overview

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How MatrixDB connects Entity context

The extracted context around MatrixDB shows recurring relationship patterns in the source. For example, MatrixDB → active member of the International Molecular Exchange Consortium, biological database focused on molecular interactions between extracellular proteins and polysaccharides Another extracted example is MatrixDB → Emilie Chautard, Guillaume Launay, Nicolas Thierry-Mieg, Romain Salza, Franck Peysselon, Marie Fatoux-Ardore, Sofiane Badaoui, Sylvain Vallet, Lionel Ballut, Dorian Multedo, Syl…. Use these groups to spot repeated connection types before inspecting the individual relationships.

Top relations

is a · 2

MatrixDB → active member of the International Molecular Exchange Consortium, biological database focused on molecular interactions between extracellular proteins and polysaccharides

Authors · 1

MatrixDB → Emilie Chautard, Guillaume Launay, Nicolas Thierry-Mieg, Romain Salza, Franck Peysselon, Marie Fatoux-Ardore, Sofiane Badaoui, Sylvain Vallet, Lionel Ballut, Dorian Multedo, Syl…

Data types captured · 1

MatrixDB → Interactions DataBase, Biochemestry, Biacore, SPR

Description · 1

MatrixDB → extracellular matrix interactions database.

Laboratory · 1

MatrixDB → IBCP - UMR5086 CNRS / Univ Lyon1 - FRANCE

Organisms · 1

MatrixDB → All (Human only possible)

Standards · 1

MatrixDB → PSI-MI

Website · 1

MatrixDB → http://matrixdb.univ-lyon1.fr

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

interaction database extracellular data imex proteins molecular databases human interactions group protein also consortium sylvie ricard-blum http univ-lyon1 fr polysaccharides

MatrixDB relationships Subject–Predicate–Object triples

TTTA extracted 9 structured relationships around MatrixDB. Examples in this analysis include MatrixDB → Authors → Emilie Chautard, Guillaume Launay, Nicolas Thierry-Mieg, Romain Salza, Franck Peysselon, Marie Fatoux-Ardore, Sofiane Badaoui, Sylvain Vallet, Lionel Ballut, Dorian Multedo, Syl… and MatrixDB → Data types captured → Interactions DataBase, Biochemestry, Biacore, SPR. The table shows each extracted connection, where it came from and its confidence.

Subject	Predicate	Object	Confidence	Src
MatrixDB	Authors	Emilie Chautard, Guillaume Launay, Nicolas Thierry-Mieg, Romain Salza, Franck Peysselon, Marie Fatoux-Ardore, Sofiane Badaoui, Sylvain Vallet, Lionel Ballut, Dorian Multedo, Syl…	1.00	infobox
MatrixDB	Data types captured	Interactions DataBase, Biochemestry, Biacore, SPR	1.00	infobox
MatrixDB	Description	extracellular matrix interactions database.	1.00	infobox
MatrixDB	Laboratory	IBCP - UMR5086 CNRS / Univ Lyon1 - FRANCE	1.00	infobox
MatrixDB	Organisms	All (Human only possible)	1.00	infobox
MatrixDB	Standards	PSI-MI	1.00	infobox
MatrixDB	Website	http://matrixdb.univ-lyon1.fr	1.00	infobox
MatrixDB	is a	biological database focused on molecular interactions between extracellular proteins and polysaccharides	0.90	text
MatrixDB	is a	active member of the International Molecular Exchange Consortium	0.90	text

Related concept clusters Related term clusters

The concept neighborhoods around MatrixDB bring nearby vocabulary together. In this analysis, examples include Extracellular, Human and Proteins. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

MatrixDB
- Extracellular
- Human
- Proteins
- Data
- Interactions
- Protein
- Molecular
- Imex
- Interaction
- Account
- Collagens
- Example
matrixdb
- Extracellular
- Human
- Proteins
- Data
- Interactions
- Protein
- Molecular
- Imex
- Interaction
- Account
- Collagens
- Example
extracellular
- Proteins
- Matrixdb
- Interactions
- Human
- Data
- Account
- Collagens
- Example
- Focused
- Laminins
- Multimeric
- Multimers
biological database
- Focused
- Polysaccharides
- Extracellular
- Interactions
- Ricard-blum
- Sylvie
- Matrixdb
- Databases
- Human
- Molecular
- Proteins
- Data
human protein reference database
- Protein
- Extracellular
- Matrixdb
- Unigene
- Interactions
- Ricard-blum
- Sylvie
- Data
- Databases
- Human
- Molecular
- Proteins
human protein atlas
- Protein
- Matrixdb
- Unigene
- Data
- Databases
- Interactions
- Proteins
- Ricard-blum
- Sylvie
- Imex
- Interaction
proteins
- Multimers
- Takes
- Thrombospondins
- Protein
- Databases
- Human
- Imex
- Data
- Interaction
international molecular exchange
- Biogrid
- Polysaccharides
- Interaction
- Consortium
- Group
- Databases
- Proteins
- Imex
- Data

Connections between topic areas Semantic bridges

Bridges highlight paths between different parts of the MatrixDB map and can reveal research angles that are easy to miss in a flat list.

Min side: 3

Map overview Semantic statistics

MatrixDB

Nodes14

Edges13

Triples9

Avg. degree1.86

Density0.142857

Components1

Source & methodology

TTTA analyzes the structure around MatrixDB 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 — MatrixDB · EN edition · Analysis: TopicsToTalkAbout

MatrixDB: Overview, Related Topics & Entities

MatrixDB topic overview

What this topic covers Research coverage

Key facts & relationships

Start with your topic. Discover where to go next.

Questions to explore

Explore all related topics Closing gaps

Overview

For the semantics nerds

Advanced semantic analysis

How MatrixDB connects Entity context

MatrixDB

Top relations

Important terminology

Important terminology

MatrixDB relationships Subject–Predicate–Object triples

Related concept clusters Related term clusters

Connections between topic areas Semantic bridges

Map overview Semantic statistics

MatrixDB

Source & methodology