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Induced pluripotent stem cell: Research & Technology
Induced pluripotent stem cells (also known as iPS cells or iPSCs) are a type of pluripotent stem cell that can be generated directly from a somatic cell. The iPSC technology was pioneered by Shinya Yamanaka and Kazutoshi Takahashi in Kyoto, Japan, who together showed in 2006 that the introduction of four specific genes (named c-Myc, Oct4, Sox2 and KLF4)…
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Induced pluripotent stem cell topic overview
The analysis highlights Research and Technology as prominent areas in the source structure around Induced pluripotent stem cell. 3 topics appear in more than one source area, which can help identify connections that are less obvious in a linear reading.
Related topics
163
Source areas
5
Connected nodes
172
Extracted relationships
99
Concept neighborhoods
27
Bridge connections
172
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.
Medical research · 49 topics
Overview · 47 topics
Production · 42 topics
Identity · 27 topics
Safety · 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.
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 Induced pluripotent stem cell 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 Induced pluripotent stem cell shows recurring relationship patterns in the source. For example, Induced pluripotent stem cell → All, An, Araki, Concern, ES, ESC, FDA, Findings, Furthermore, However, In, IPS, IPSC, Much, Myc, Nevertheless, Other, Since, Some, Stem Cells Another extracted example is Induced pluripotent stem cell → Application, April, Archived, BSCRF, Cell Research, Cells, Center, Forced Expression, Future, Induced Pluripotent Stem, Induced Pluripotent Stem Cells, Klf42 Minute Video, Kyoto UniversityWith, MEFS, Myc, Oct-4, Oxford, SCNT, Sox-2, The Discovery. Use these groups to spot repeated connection types before inspecting the individual relationships.
Induced pluripotent stem cell
Top relations
related to Safety· 29
Induced pluripotent stem cell → All, An, Araki, Concern, ES, ESC, FDA, Findings, Furthermore, However, In, IPS, IPSC, Much, Myc, Nevertheless, Other, Since, Some, Stem Cells
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 99 structured relationships around Induced pluripotent stem cell. Examples in this analysis include lineage specifiers → instance of → or even non-related genes and C-MYC/L-MYC or repression of cell cycle checkpoints → instance of → It is also clear that pro-mitotic factors. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
lineage specifiers
instance of
or even non-related genes
0.80
text
C-MYC/L-MYC or repression of cell cycle checkpoints
instance of
It is also clear that pro-mitotic factors
0.80
text
such as p53
instance of
It is also clear that pro-mitotic factors
0.80
text
are conduits to creating a compliant cellular state for iPSC reprogramming.iPSC derivation is typically a slow
instance of
It is also clear that pro-mitotic factors
0.80
text
inefficient process
instance of
It is also clear that pro-mitotic factors
0.80
text
taking one
instance of
It is also clear that pro-mitotic factors
0.80
text
tumorgenesis
instance of
Alternate vectorsAnother key strategy for avoiding problems
0.80
text
low throughput has been to use alternate forms of vectors
instance of
Alternate vectorsAnother key strategy for avoiding problems
0.80
text
using adenoviruses or plasmids are generally thought to be safer than retroviral methods.An important area for future studies in the iPSC field is directly testing iPSC tumorigenicity using methods that mimic the approaches that would be used for regenerative medicine therapies
instance of
Other approaches
0.80
text
Down syndrome
instance of
including common disorders
0.80
text
polycystic kidney disease
instance of
including common disorders
0.80
text
PD-L1
instance of
while expressing immune-modulatory genes
0.80
text
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 Induced pluripotent stem cell bring nearby vocabulary together. In this analysis, examples include Pluripotent, Stem and Generation. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Induced pluripotent stem cell
Pluripotent
Stem
Generation
Embryonic
Pluripotency
Could
Mouse
Cells
Mice
Factors
Cell
Induced
induced pluripotent stem cell
Stem
Embryonic
Pluripotent
Ips
Type
Cells
Genes
Generation
Pluripotency
Mouse
Factors
Using
pluripotent
Stem
Embryonic
Type
Pluripotency
Factors
Generation
Using
Could
Klf4
Mouse
Expression
Somatic
stem cell
Embryonic
Stem
Ips
Type
Cells
Genes
Pluripotent
Pluripotency
Mouse
Using
Escs
Ipscs
somatic cell
Stem
Ips
Type
Cells
Pluripotent
Derived
Ipscs
Human
Mouse
Could
Ipsc
Embryonic
shinya yamanaka
Factors
Al
Et
Klf4
Demonstrated
Cells
Ips
Oct4
Sox2
Transcription
Reprogramming
Generation
sox2
Klf4
Nanog
Mouse
Transcription
Stem
Yamanaka
Factor
Expression
Reprogramming
Used
Efficiency
Fibroblasts
klf4
Oct4
Sox2
Mouse
Yamanaka
Transcription
Factor
Generation
Reprogramming
Efficiency
Pluripotent
Stem
Fibroblasts
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 Induced pluripotent stem cell, one of the stronger structural bridges in this analysis connects Induced pluripotent stem cell with Medical research. 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.
Induced pluripotent stem cell
Nodes173
Edges172
Triples99
Avg. degree1.99
Density0.011561
Components1
Source & methodology
TTTA analyzes the structure around Induced pluripotent stem cell to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Research & Technology, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
