Convolutional Neural Network-based Sequence-to-Expression Prediction Tool (CoNSEPT)

Payam Dibaeinia (Creator)
Saurabh Sinha (Creator)

Siebel School of Computing and Data Science

Dataset

Description

CoNSEPT is a tool to predict gene expression in various cis and trans contexts. Inputs to CoNSEPT are enhancer sequence, transcription factor levels in one or many trans conditions, TF motifs (PWMs), and any prior knowledge of TF-TF interactions.

Date made available	Jan 8 2026
Publisher	University of Illinois Urbana-Champaign

Keywords

software
gene expression

DOI
10.13012/B2IDB-8692568_V1

1 Article

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks
Dibaeinia, P. & Sinha, S., Oct 11 2021, In: Nucleic acids research. 49, 18, p. 10309-10327 19 p.
Research output: Contribution to journal › Article › peer-review

Open Access

Convolutional Neural Network-based Sequence-to-Expression Prediction Tool (CoNSEPT)

Description

Keywords

DOI

Research output

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks

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