FIMO

FIMO

FIMO is a software tool for motif discovery and searching. It finds overrepresented motifs in biological sequences and helps identify functional, transcription factor binding sites or regulatory elements.
FIMO image
motif-discovery transcription-factor-binding-site-prediction

FIMO: Motif Discovery and Searching Tool

Discover motifs in biological sequences with FIMO, a software tool that identifies overrepresented motifs and helps find functional transcription factor binding sites or regulatory elements.

What is FIMO?

FIMO (Find Individual Motif Occurrences) is a software tool part of the MEME Suite for discovering occurrences of known motifs in biological sequences. It searches DNA or protein sequences to find matches to predefined motifs from databases such as JASPAR or user-submitted motifs.

Some key features of FIMO include:

  • Searches sequences for matches to motif databases or user-submitted motif files
  • Supports motifs in MEME, MAST, or TRANSFAC format
  • Calculates motif p-values and q-values to assess motif match significance
  • Outputs motif match locations and scores
  • Can be used for motif enrichment analysis
  • Implemented in C++ and Python, with source code available

FIMO is often used in bioinformatics pipelines to identify functional transcription factor binding sites or regulatory elements in genomic regions. By matching DNA sequences to known motifs, FIMO can help discover functional elements that regulate gene expression and other processes in cells and organisms.

FIMO Features

Features

  1. Discovers motifs using probabilistic modeling
  2. Performs de novo motif discovery
  3. Searches sequence databases for matches to known motifs
  4. Supports various motif models including position weight matrices
  5. Analyzes DNA, RNA and protein sequences

Pricing

  • Open Source

Pros

Widely used and well-established for motif analysis

Provides both motif discovery and search capabilities

Offers different motif models to choose from

Integrates well with other MEME Suite tools

Cons

Limited to relatively simple motif models

Motif discovery can be slow for large datasets

Fewer customization options compared to some other tools


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