URL: https://github.com/aertslab/TF-MInDi
Proper Citation: TF-MInDi (RRID:SCR_027436)
Description: Software Python package for analyzing transcription factor binding patterns from deep learning model attribution scores. It identifies and clusters sequence motifs from contribution scores, maps them to DNA-binding domains, and provides comprehensive visualization tools for regulatory genomics analysis. Used for transcription factor motifs and instances discovery.
Resource Type: software resource, software toolkit, source code
Keywords: Transcription Factor Motifs, instances discovery, analyzing transcription factor binding patterns, attribution scores, identify and cluster sequence motifs,
Availability: Free, Available for download, Freely available
Resource Name: TF-MInDi
Resource ID: SCR_027436
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Source: SciCrunch Registry (RRID:SCR_005400)
Description: Interactive portal for finding and submitting biomedical resources. Resources within SciCrunch have assigned RRIDs which are used to cite resources in scientific manuscripts. SciCrunch Registry, formerly NIF Registry, provides resources catalog. Allows to add new resources. Allows edit existing resources after registration. Curators are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping contents current.
URL: https://rrid.site/rin/sources/SCR_005400
