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FASTA is a DNA and protein sequence alignment software package first described by David J. Lipman and William R. Pearson in 1985. Its legacy is the FASTA format which is now ubiquitous in bioinformatics.
The analysis highlights History, Applications and Regions as prominent areas in the source structure around FASTA.
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.
A focused starting point derived from the topic graph, ranked independently of the source article order.
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 FASTA shows recurring relationship patterns in the source. For example, FASTA → Because, DNA, FAST-All, FAST-N, FAST-P, Nowadays, Smith, The, There, Waterman Another extracted example is FASTA → DNA, In, Recent, Smith, SSEARCH, The, Waterman. 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.
sequence alignment protein sequences score package program regions blast dna similarity search statistical significance bioinformatics searches programs database using used
TTTA extracted 37 structured relationships around FASTA. Examples in this analysis include FASTA → Developers → William R. Pearson and FASTA → Developers → David J. Lipman. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| FASTA | Developers | William R. Pearson | 1.00 | infobox |
| FASTA | Developers | David J. Lipman | 1.00 | infobox |
| FASTA | License | apache2.0 | 1.00 | infobox |
| FASTA | Operating system | UNIX | 1.00 | infobox |
| FASTA | Operating system | Linux | 1.00 | infobox |
| FASTA | Operating system | Mac | 1.00 | infobox |
| FASTA | Operating system | MS-Windows | 1.00 | infobox |
| FASTA | Repository | github.com/wrpearson/fasta36 | 1.00 | infobox |
| FASTA | Stable release | 36 | 1.00 | infobox |
| FASTA | Type | Bioinformatics | 1.00 | infobox |
| FASTA | Website | fasta.bioch.virginia.edu | 1.00 | infobox |
| FASTA | Website | www.ebi.ac.uk/Tools/sss/fasta | 1.00 | infobox |
| FASTA | is a | DNA and protein sequence alignment software package first described by David J | 0.90 | text |
The concept neighborhoods around FASTA bring nearby vocabulary together. In this analysis, examples include Protein, Sequence and Package. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For FASTA, one of the stronger structural bridges in this analysis connects FASTA 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.
TTTA analyzes the structure around FASTA to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Applications & Regions, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — FASTA · EN edition · Analysis: TopicsToTalkAbout