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Regulatory Associations:
- Search for TFs
- Search for Genes
- Search for Associations

Group genes:
- Group by TF
- Group by GO

Pattern Matching:
- Search by DNA Motif
- Find TF Binding Site(s)
- Search Motifs on Motifs

- ORF List ⇔ Gene List
- IUPAC Code Generation
Generate Regulation Matrix

- TF-Consensus List
- Evidence Code List
- Upstream Sequence
- Flat files

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Group Genes by TF - Help



  1. Summary
  2. Input
  3. Options
  4. Output

1. Summary

This query allows the user to group a given list of genes (e.g., a set of co-activated genes from a microarray experiment) according to the TFs which are their documented or potential regulators.

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2. Input

This query requires a list of genes and, optionally, a list of transcription factors as input.

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3. Options

The TFs considered in this query can be either those in the input list, or all the TFs in the YEASTRACT database (by selecting the option Check for all TFs). Either documented or potential regulations can be considered (by selecting Documented Regulations  or Potential Regulations, respectively). Furthermore, for each established regulon, the percentage value representing the proportion of genes regulated by each TF can be calculated relative to:

  1. The total number of genes in the input list; this may identify the TFs involved in the regulation of the given gene list.

  2. The number of genes, in the whole yeast genome, documented as being regulated by the same TF; this may identify the TF networks predominantly involved in the regulation of the referred gene list.

Furthermore, the user may restrict its search to the regulatory associations identified based on direct or indirect evidences. Direct Evidence was considered to be provided through experiments such as Chromatine ImmunoPrecipitation (ChIP), ChIP-on-chip and Electrophoretic Mobility Shift Assay (EMSA), that prove the direct binding of the TF to the target gene's promoter region, or such as the analysis of the effect on target-gene expression of the site-directed mutation of the TF binding site in its promoter region, which strongly suggests that the TF interacts with that specific target promoter. The classification Indirect Evidence was attributed to experiments such as the comparative analysis of gene expression changes occurring in response to the deletion, mutation or over-expression of a given TF. The complete enumeration of the experimental approaches considered to provide direct or indirect evidences is provided in Table Evidence code list.

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4. Output

Depending on the options selected, the output is a table containing the input genes, grouped by TF and ordered by the percentage of genes regulated by the respective TF, as exemplified in the figure below:


By selecting or deselecting each of the checkboxes, one can include or exclude a specific transcription factor from the generated regulatory network. There two possible types of regulation graph images: static, which provides several types of image file extensions; and interactive, which permits the selection of a single regulator or regulation target.

4.1. Static image

The edges going out of each TF have the same color for readability reasons. Also, TFs are colored in grey and target genes in white.
If the checkboxes corresponding to the TFs Abf1p, Rap1p, Stp2 and Gcr1 are selected, these TFs will be included in the generated image, as shown in the figure below:

4.2. Interactive image

The regulations are represented within a circle, with transcription factors (TFs) on the left half and target genes on the half right. By selecting a gene from the right half, the edges to the regulating TFs are highlighted in blue. Similarly, by selecting a TF from the left half, the edges connecting to target genes are highlighted, as well as edges from regulators. This effect can also be obtained by mouse-overing a gene or a TF. If a TF turns to pink when selected or mouse-overed, then it regulates itself. After a set of interactive analyses, the user can always return to the original image by clicking in any area outside the circle.
The TFs are sorted in decreasing order of the percentage of regulated genes from top to bottom.
At anytime of the interactive analysis, the user can get a network snapshot by taking a screenshot using the tool of its preference, or the PrintScreen key, when available.

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