Here you learn how to build your search queries. Please bear in mind that these queries are case sensitive, and this extends to all the syntax.
Search by string
Retrieve documents containing a specific string. Example:
Search by filename
Retrieve all files matching some filename, possibly with a wildcard.
Example, search all your pdf files:
Example, search a specific file with spaces:
filename:"My filename has some spaces.md"
Search filenames with spaces, special characters, and even emojis, just because you can! Example:
filename:"Grammatikübersicht abc ! 🧡' ㊔.pdf"
Search by document label
Find documents tagged with specific label and value.
label:number_issues:[10 TO 20]
Search by entity type
Retrieve all documents containing at least one entity that belongs to the given entity type. Example:
entity:disease, retrieves all documents with at least one entity of the type
If you add a term, e.g.
entity:disease:cancer, you can find all documents containing at least one entity using that term.
Only by using the entity type id, you can also perform more advanced queries as:
count_e_1:[2 TO *]): retrieve documents with at least 2 annotations of the type
norms_count_uniq_e_1:[2 TO *]retrieve documents with at least 2 annotations of the type
e_1that are normalized to different unique names (e.g Rezulin and Romozin - same diabetic drug sold under different commercial names - would be normalized to troglitazone, so it would count 1 unique entity normalized, not 2).
Search by normalization
Retrieve all documents containing at least one entity that normalizes to the given normalization. Example:
entity:genes:HER2, retrieves all documents with at least one entity
gene that normalizes to
Search by date
Retrieve all documents imported or updated in a given time frame.
created: documents imported in a given time frame. Examples:
created:[2013 TO NOW],
created:[2016-12 TO 2017-02],
created:[NOW-1DAY TO NOW] - documents imported since the previous day.
updated: documents updated in a given time frame. Examples:
updated:[2013 TO NOW],
updated:[2016-12 TO 2017-02],
updated:[NOW-1DAY TO NOW] - documents updated since the previous day.
Search by folder
You have three possibilities to search by folder:
- Search by folder index (
folder:INDEX): the folders' indexes (integer numbers) are written in the project settings JSON. Take note of the folder's index you want to search for, and then search like
folder:INDEX. For example, to search for the
pooldocuments (special folder, always created), search like:
- Search by folder path (
folder:PATH): for example, if the structure of your desired folder is pool > level1 > A, compose the folder path as in Unix:
folder:pool/level1/A. Note that any leading or trailing
/'s are discouraged, although accepted and ignored.
- Search by folder name (
folder:NAME): following the previous example, you could simply search by
folder:A. In case you have different folders with the same name, the folder closest to the root level (the pool), that is, the folder less deep in the folder tree, will be found. For instance, if you had the folders pool/level1/A and pool/level1/level2/A, the former folder will be found. Caveat: in case you have different folders with the same name at the same level of the folder tree, one will be arbitrarily chosen and returned.
Search confirmed documents
You can search which documents are confirmed with query:
You can search which documents are not confirmed with query:
Search which documents a user has confirmed
You can retrieve the documents a given member has confirmed with the query:
You can also retrieve all the documents that have been confirmed by at least one member with the query:
Create a query for a set of users following this example:
members_anncomplete:user1 AND members_anncomplete:user2 AND members_anncomplete:user3
To perform a single character wildcard search use
To perform a multiple character wildcard search use
Tip: find all documents by just searching for
Note that you cannot search the TODO list for other users; the filter is only available for the currently logged in user.
Find similar terms (string based search) based on the Levenshtein Distance, or Edit Distance algorithm. Use
~ at the end of a single word term. Example:
roam~ will also find terms as
You can fine tune the similarity level by adding, at the end, a number between
0 (less similar) and
1 (more similar). Example:
Finding words (string based search) within a specific distance away. Example:
"diabetes insulin"~10, to search documents with the terms
insulin within 10 words of each other.
Search queries can be combined using the operators
-. Some examples:
entity:GGP AND entity:Mutationsearch for documents that contain
"type 1 diabetes" OR insulinsearch for documents that contain "type 1 diabetes" or "insulin".
"type 1 diabetes" NOT insulinsearch for documents that contain "type 1 diabetes" but not "insulin". This operator cannot be used with just one term.
-entity:GGPsearch for documents that don't contain mentions of genes, i.e.
Escaping Special Characters
To escape these special characters use the
\ before the character. For example to search for
PD-L1 use the query: