Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

RAxML: Historie & Overview

RAxML (zkratka Randomized Axelerated Maximum Likelihood, volně přeloženo: Náhodně akcelerovaná metoda maximální věrohodnosti) je populární bioinformatický program určený k rekonstrukci fylogenetických stromů na základě molekulárních dat (např. DNA, RNA nebo proteinových sekvencí). Využívá metodu maximální věrohodnosti (Maximum Likelihood, ML), která…

Language: Czech [CS]
Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.
100%
More settings
100% 100% 100% 100% 100%

RAxML topic overview

The analysis highlights Historie and Overview as prominent areas in the source structure around RAxML.

Related topics
17
Source areas
2
Connected nodes
19
Extracted relationships
36
Concept neighborhoods
5
Bridge connections
19

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 · 9 topics
Historie · 8 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.

Aktuální verze
RAxML-NG 1.2.2
Operační systém
Linux / Unix macOS Windows
První vydání
2019
Vývojář
Alexey M. Kozlov, Diego Darriba, Tomáš Flouri, Benoit Morel, Alexandros Stamatakis

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

Historie

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How RAxML connects Entity context

The extracted context around RAxML shows recurring relationship patterns in the source. For example, RAxML → Aberer, Bioinformatics, Darriba, ExaML, Flouri, Ludwig, Maximum, Meier, Morel, RAxML-III, RAxML-NG, RAxML-VI-HPC, Stamatakis Another extracted example is RAxML → Ačkoli, Cílem, Maximum Likelihood, Metoda, Parallel, PAxML, Program RAxML, Při, RAxML-III, Výsledkem. Use these groups to spot repeated connection types before inspecting the individual relationships.

RAxML

Top relations

related to Literatura · 13
RAxML → Aberer, Bioinformatics, Darriba, ExaML, Flouri, Ludwig, Maximum, Meier, Morel, RAxML-III, RAxML-NG, RAxML-VI-HPC, Stamatakis
related to Historie · 10
RAxML → Ačkoli, Cílem, Maximum Likelihood, Metoda, Parallel, PAxML, Program RAxML, Při, RAxML-III, Výsledkem
related to Algoritmus · 9
RAxML → DNA Parsimony, Jádrem, Na, Náhodné, Následně, Parsimoniální, PHYLIP, Podstromy, Tato
Aktuální verze · 1
RAxML → RAxML-NG 1.2.2
Operační systém · 1
RAxML → Linux / Unix macOS Windows
První vydání · 1
RAxML → 2019
Vývojář · 1
RAxML → Alexey M. Kozlov, Diego Darriba, Tomáš Flouri, Benoit Morel, Alexandros Stamatakis

Important terminology

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

Important terminology

maximum bioinformatics raxml-ng verze likelihood stamatakis dat stromů programu navíc program examl maximální věrohodnosti roce díky https doi org 10

RAxML relationships Subject–Predicate–Object triples

TTTA extracted 36 structured relationships around RAxML. Examples in this analysis include RAxML → Aktuální verze → RAxML-NG 1.2.2 and RAxML → Operační systém → Linux / Unix macOS Windows. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
RAxMLAktuální verzeRAxML-NG 1.2.21.00infobox
RAxMLOperační systémLinux / Unix macOS Windows1.00infobox
RAxMLPrvní vydání20191.00infobox
RAxMLVývojářAlexey M. Kozlov, Diego Darriba, Tomáš Flouri, Benoit Morel, Alexandros Stamatakis1.00infobox
RAxMLrelated to AlgoritmusNa0.60section
RAxMLrelated to AlgoritmusDNA Parsimony0.60section
RAxMLrelated to AlgoritmusPHYLIP0.60section
RAxMLrelated to AlgoritmusParsimoniální0.60section
RAxMLrelated to AlgoritmusNáhodné0.60section
RAxMLrelated to AlgoritmusJádrem0.60section
RAxMLrelated to AlgoritmusPodstromy0.60section
RAxMLrelated to AlgoritmusNásledně0.60section

Related concept clusters Concept neighborhoods

The concept neighborhoods around RAxML bring nearby vocabulary together. In this analysis, examples include Examl, Vznikl and Version. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • RAxML
    • Examl
    • Vznikl
    • Version
    • Raxml-ng
    • Jako
    • Superpočítačích
    • Vyšší
    • Roce
    • Program
    • Dat
    • Navíc
    • Programu
  • raxml
    • Examl
    • Vznikl
    • Version
    • Raxml-ng
    • Jako
    • Superpočítačích
    • Vyšší
    • Roce
    • Program
    • Dat
    • Navíc
    • Programu
  • metodu maximální věrohodnosti
    • Maximální
    • Věrohodnosti
    • Likelihood
    • Maximum
    • Data
    • Např
    • První
    • Stromu
    • Díky
    • Program
    • Dat
    • Programu
  • fylogenetických stromů
    • Jako
    • Verze
    • Algoritmus
    • Data
    • První
    • Vznikl
    • Funkce
    • Umožňuje
    • Věrohodnosti
    • Raxml-ng
    • Stamatakis
  • dna
    • Programu
    • Verze

Connections between topic areas Semantic bridges

For RAxML, one of the stronger structural bridges in this analysis connects RAxML 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.

Min side: 3
RAxMLOverview · splits 10 ⟂ 10
RAxMLHistorie · splits 11 ⟂ 9

Map overview Semantic statistics

RAxML

Nodes20
Edges19
Triples36
Avg. degree1.9
Density0.1
Components1

Source & methodology

TTTA analyzes the structure around RAxML to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Historie & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — RAxML · CS edition · Analysis: TopicsToTalkAbout

For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.