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Exome sequencing, also known as whole exome sequencing (WES), is a genomic technique for sequencing all of the protein-coding regions of genes in a genome (known as the exome). It consists of two steps: the first step is to select only the subset of DNA that encodes proteins. These regions are known as exons—humans have about 180,000 exons, constituting…
The analysis highlights Applications and Regions as prominent areas in the source structure around Exome sequencing.
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.
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 Exome sequencing shows recurring relationship patterns in the source. For example, Exome sequencing → BGI, CLIA-certified, Consumers, DNADTC, Gene, Genos, In June, In November, In October, Knome, Later, Multiple, September, The, This, WES Another extracted example is Exome sequencing → DNA, HiSeq, II, Illumina MiSeq, Illumina's Illumina Genome Analyzer, Life Technologies Ion Torrent, Life Technologies SOLiD, Next Generation Sequencing, NGS, NovaSeq, Other, Roche, Sanger, There, These. 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.
sequencing exome variants genes rare identify genetic whole genome dna gene disease used needed genomic common citation syndrome regions variant
TTTA extracted 94 structured relationships around Exome sequencing. Examples in this analysis include SNP arrays can only detect shared genetic variants that are common to many individuals in the wider population → instance of → techniques and whole genome sequencing → instance of → which can be found using other methods. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| SNP arrays can only detect shared genetic variants that are common to many individuals in the wider population | instance of | techniques | 0.80 | text |
| whole genome sequencing | instance of | which can be found using other methods | 0.80 | text |
| dbSNP | instance of | in public databases | 0.80 | text |
| exome sequencing | instance of | With approaches | 0.80 | text |
| it is possible to significantly enhance the data generated from individual genomes which has put forth a series of questions on how to deal with the vast amount of information | instance of | With approaches | 0.80 | text |
| non-synonymous mutations | instance of | They looked at variants that have the potential to be pathogenic | 0.80 | text |
| splice acceptor | instance of | They looked at variants that have the potential to be pathogenic | 0.80 | text |
| donor sites | instance of | They looked at variants that have the potential to be pathogenic | 0.80 | text |
| short coding insertions or deletions | instance of | They looked at variants that have the potential to be pathogenic | 0.80 | text |
| Exome sequencing | has application | By | 0.60 | section |
| Exome sequencing | has application | This | 0.60 | section |
| Exome sequencing | related to Clinical diagnostics | Exome | 0.60 | section |
The concept neighborhoods around Exome sequencing bring nearby vocabulary together. In this analysis, examples include Sequencing, Whole and Used. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Exome sequencing, one of the stronger structural bridges in this analysis connects Exome sequencing 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 Exome sequencing to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as 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 — Exome sequencing · EN edition · Analysis: TopicsToTalkAbout