eScholarship
metadata only
motifDiverge: a model for assessing the statistical significance of gene regulatory motif divergence between two DNA sequences
Next-generation sequencing technology enables the identification of thousands of gene regulatory sequences in many cell types and organisms. We consider the problem of testing if two such sequences differ in their number of binding site motifs for a given transcription factor (TF) protein. Binding s
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Motif-cluster: Motif driven prioritization of transcription factor binding clusters#431421
- Identification of cis-regulatory modules in promoters of human genes exploiting mutual positioning of transcription factors#1312699
- Identification of promoter sequences using archaeal genomic sequences#385081
- Inferring Combinatorial Regulation of Binding Sites and Transcription Factors on Gene Expression#70516
- Nonconsensus flanking sequence of hundreds of base pairs around in vivo binding sites: statistical beacons for transcription factor scanning.#392975
Record · ID 1358225
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive