Research any topic before you write.
Find related topics. | Discover entities. | See connections. | Build a topical map.
PICRUSt is a bioinformatics software package. The name is an abbreviation for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States.
Measurement, Genome prediction algorithm & Metagenome prediction algorithm
Explore the main themes, entities and connections around PICRUSt. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. 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.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
gene 16s sequenced rrna tool prediction genomes copy sequences samples genome metagenome sample reference family numbers phylogenetic based nearest predictions
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| PICRUSt | Developers | Morgan Langille, Jesse Zaneveld, Daniel McDonald, Greg Caporaso, Gavin Douglas | 1.00 | infobox |
| PICRUSt | Original authors | Morgan Langille, Jesse Zaneveld, Dan Knights, Joshua A Reyes, Jose C Clemente, Deron E Burkepile, Rebecca L Vega Thurber, Rob Knight, Robert G Beiko, Curtis Huttenhower | 1.00 | infobox |
| PICRUSt | Release | 29 July 2013; 13 years ago (2013-07-29) | 1.00 | infobox |
| PICRUSt | Website | picrust.github.io/picrust/ | 1.00 | infobox |
| PICRUSt | Written in | Python, R | 1.00 | infobox |
| PICRUSt | is a | bioinformatics software package | 0.90 | text |
| PICRUSt | is a | sample by functional-gene-count matrix | 0.90 | text |
| PICRUSt | related to Genome prediction algorithm | In | 0.60 | section |
| PICRUSt | related to Genome prediction algorithm | More | 0.60 | section |
| PICRUSt | related to Genome prediction algorithm | These | 0.60 | section |
| PICRUSt | related to Genome prediction algorithm | Brownian Motion | 0.60 | section |
| PICRUSt | related to Genome prediction algorithm | Maximum Likelihood | 0.60 | section |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.