GUILDify v2.0 Web Server

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Example queries: [ "lung carcinoma" (TOGETHER) ] [ +alzheimer +disabetes (AND) ] [ alzheimer diabetes (OR) ] [ TP53; BRCA1; BRCA2 (GENES) ] [ erlotinib (DRUG) ]
If not 'quoted', whitespaces act as OR, you can convert them to AND by using a '+'. See quick start guide below for details.

Enter Job Id:

Note that only finished results can be retrieved!

The jobs will be removed in 6 months.

Job Id 1:   Job Id 2:


GUILDify uses network-topology based prioritization algorithms in GUILD to score relevance of gene products with respect to given keywords. First, BIANA knowledge base containing data integrated from publicly available major data repositories is queried for gene products associated with the keywords. Next, these gene products are fed to a species-specific interaction network (created using BIANA) as seed proteins. Finally, a score of relevance for each gene product in the network is calculated by the prioritization algorithm. See documentation page for details.

Querying tips
- Grouping multiple keywords TOGETHER using quotations
When the keywords are quoted together, GUILDify will only match entries that contain the quoted keywords together in their description. For instance, "lung carcinoma" (with quotation) will retrieve entries containing "lung carcinoma" together.
- Searching for a keyword AND another keyword using '+'
If we want to search entries containing multiple keywords but not necessarily together, we have to add '+' in front of the word. For instance, "+alzheimer +diabetes" will retrieve entries containing "alzheimer" AND "diabetes".
- Searching for a keyword OR another keyword using whitespaces
If we want to search entries containing at least one of the keywords specified, we have to separate them using whitespaces. For instance, "alzheimer diabetes" will retrieve entries containing "alzheimer" OR "diabetes".
- User-specified gene symbols using semicolons (';')
If the query contains ';', it will be considered as a list of genes separated by semicolons (e.g., TP53; BRCA1; BRCA2).
- User-specified gene symbols in a file
The user can introduce gene symbols in a text file separated by new lines ("\n").

The following examples have been calculated using all the seeds and the prioritization algorithm NetScore:

GUILDify is now available in R through the guildifyR package. Download it now! (Last update on 11-Dec-2019)

  • From tgz file:

    R CMD INSTALL guildifyR.tgz

  • From GitHub repository using devtools (in R):



Click here to download the manual.

Quick start guide:
  • query
    • Description: Get protein/gene info associated with the query keywords.
    • Usage:

      query(keywords, species = "9606", tissue = "all", network.source = "BIANA")

    • Example:

      result.table = query("alzheimer", species="9606", tissue="all", network.source = "BIANA")

  • submit.job
    • Description: Submit job using the guildifyR query result table.
    • Usage:

      submit.job(result.table, species, tissue, network.source, scoring.options = list(netcombo = T))

    • Example:




      scoring.options = list(netscore=T, repetitionSelector=3, iterationSelector=2) # NetScore

      scoring.options = list(netzcore=T, repetitionZelector=3) # NetZcore

      scoring.options = list(netshort=T) # NetShort

      scoring.options = list(netcombo=T) # NetCombo = submit.job(result.table, species, tissue, network.source, scoring.options)

  • retrieve.job
    • Description: Retrieve results using job id.
    • Usage:

      retrieve.job(, = NULL, fetch.files = F, output.dir = NULL)

    • Example:

      result = retrieve.job(


      head(gScores(result)) # Scores

      head(gFunctions(result)) # Functions

      head(gDrugs(result)) # Drugs

  • retrieve.overlap
    • Description: Retrieve overlap between two results using two job ids.
    • Usage:

      retrieve.overlap(job.id1, job.id2, top.validated = T, fetch.files = F, output.dir = NULL)

    • Example:

      result = retrieve.overlap(job.id1, job.id2)

      getSlots(class(result)) # Scores

      head(gFunctions(result)) # Functions

      head(gDrugs(result)) # Drugs

Num. genes/disease2.85.6
PPI interaction network sources16
Tissue-specific networks-22
Functional enrichment-Yes
Functional-based selection-Yes
Overlap of two sessions-Yes

Current version of GUILDify (2.0) uses BIANA integrated database release from May 2018 (includes UniProt, GO, OMIM, DisGeNET, Drugbank, HPRD, IntAct, DIP, BioGrid and HIPPIE databases). Please contact us in case you need to access data from the previous release of BIANA (from March 2013 ). Click here if you want to access to the previous version of GUILDify.

Database NameDatabase Version

Main articles:
  • GUILDify v2.0: A tool to identify the molecular networks underlying human diseases, their comorbidities and their druggable targets. Submitted (2018).
  • GUILDify: a web server for phenotypic characterization of genes through biological data integration and network-based prioritization algorithms. Bioinformatics. 2014 Jun 15;30(12):1789-90
Other references: