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ELife: Science & Products
eLife is a not-for-profit, peer-reviewed, open access, science publisher for the biomedical and life sciences. It was established at the end of 2012 by the Howard Hughes Medical Institute, Max Planck Society, and Wellcome Trust, following a workshop held in 2010 at the Janelia Farm Research Campus. Together, these organizations provided the initial…
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ELife topic overview
The analysis highlights Science and Products as prominent areas in the source structure around ELife.
Related topics
39
Source areas
7
Connected nodes
46
Extracted relationships
69
Concept neighborhoods
19
Bridge connections
46
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 · 16 topics
Abstracting and indexing · 10 topics
Controversial decisions · 5 topics
Reviewing process · 4 topics
Business model · 2 topics
ELife digests · 1 topics
Other partners · 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.
Publisher
eLife Sciences Publications Ltd
CODEN
ELIFA8
Discipline
Biomedicine, life sciences
Edited by
Tim Behrens
Frequency
Continuous
History
2012–present
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 ELife 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 ELife shows recurring relationship patterns in the source. For example, ELife → According, BIOSIS Previews, Chemical Abstracts Service, Don't, Howard Hughes Medical Institute, In, In December, In October, Journal Citation Reports, Medline, President Robert Tjian, Science, Science Citation Index Expanded, Scopus, The, They, We, Web Another extracted example is ELife → At, Berkeley, California, Dying Gazans Criticized For, Eisen, Eisen's, Following, Michael Eisen, Not Using Last Words, Oct, October, Other, Randy Schekman, The, The Onion, TheOnion, To Condemn Hamas, University. Use these groups to spot repeated connection types before inspecting the individual relationships.
ELife
Top relations
related to Abstracting and indexing· 18
ELife → According, BIOSIS Previews, Chemical Abstracts Service, Don't, Howard Hughes Medical Institute, In, In December, In October, Journal Citation Reports, Medline, President Robert Tjian, Science, Science Citation Index Expanded, Scopus, The, They, We, Web
related to Controversial decisions· 18
ELife → At, Berkeley, California, Dying Gazans Criticized For, Eisen, Eisen's, Following, Michael Eisen, Not Using Last Words, Oct, October, Other, Randy Schekman, The, The Onion, TheOnion, To Condemn Hamas, University
related to Reviewing process· 7
ELife → At, Cell, During, In June, Nature, Randy Schekman, Science
related to eLife digests· 4
ELife → Insights, Medium, Most, Since December
related to Business model· 3
ELife → Authors, This, US
related to Other partners· 3
ELife → In April, Initiative, Open Citations
related to External links· 2
ELife → MediumeLife Insights, Official
CODEN· 1
ELife → ELIFA8
Discipline· 1
ELife → Biomedicine, life sciences
Edited by· 1
ELife → Tim Behrens
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
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 ELife. Examples in this analysis include ELife → CODEN → ELIFA8 and ELife → Discipline → Biomedicine, life sciences. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
ELife
CODEN
ELIFA8
1.00
infobox
ELife
Discipline
Biomedicine, life sciences
1.00
infobox
ELife
Edited by
Tim Behrens
1.00
infobox
ELife
Frequency
Continuous
1.00
infobox
ELife
History
2012–present
1.00
infobox
ELife
Impact factor
N/A (2024)
1.00
infobox
ELife
ISO 4
eLife
1.00
infobox
ELife
ISSN
2050-084X
1.00
infobox
ELife
Language
English
1.00
infobox
ELife
License
CC BY 3.0, CC BY 4.0, and CC0
1.00
infobox
ELife
OCLC no.
813236730
1.00
infobox
ELife
Open access
Yes
1.00
infobox
ELife
Publisher
eLife Sciences Publications Ltd
1.00
infobox
ELife
is a
not-for-profit
0.90
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 ELife bring nearby vocabulary together. In this analysis, examples include Journal, Announced and Open. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
ELife
Journal
Announced
Open
Review
Model
Access
December
Digests
Papers
Published
Would
October
elife
Journal
Announced
Open
Review
Model
Access
December
Digests
Papers
Published
Would
October
business model
New
Life
Organizations
Publisher
Sciences
Behrens
Digests
Reviewing
Announced
Publishing
Review
Decisions
elife digests
Open
Journal
Life
Publisher
Sciences
Announced
Review
December
Research
Reviewing
Model
Factor
journal citation reports
Science
December
Factor
Impact
Citation
Journal
Papers
Publication
Published
Research
Announced
October
controversial decisions
Reviewing
Model
Life
Publisher
Sciences
Behrens
Digests
Papers
Published
Scientists
Announced
Factor
open access
Open
Life
Publisher
Sciences
Digests
Business
Behrens
Reviewing
Decisions
Factor
One
Science
science publisher
Sciences
Citation
Business
Behrens
Digests
Reviewing
Decisions
Factor
Science
Editor-in-chief
Impact
October
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 ELife, one of the stronger structural bridges in this analysis connects ELife 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.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
ELife
Nodes47
Edges46
Triples69
Avg. degree1.96
Density0.042553
Components1
Source & methodology
TTTA analyzes the structure around ELife to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Science & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — ELife · EN edition · Analysis: TopicsToTalkAbout
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