tfNet is a computational tool that identifies putative regulatory regions and genomic signal interactions in a genome-wide scale.
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Updated
Jan 22, 2019 - C#
tfNet is a computational tool that identifies putative regulatory regions and genomic signal interactions in a genome-wide scale.
Scripts for reproducing the poster: Co-regulation of RKIP and autophagy genes by VEZF1 and ERCC6 in prostate cancer
Phylogeny and classification of Azolla filiculoides MYB genes
A research compendium: Transcriptional regulation of autophagy during adipocyte differentiation
The Soybean Genomic Variations Explorer (Soybean GenVarX) is a toolset that consists of promoter region component and CNV component for users to perform queries, visualize data, and conduct annotations using genotypic and phenotypic differences.
Prediction of the binding sites of multiple transcription factors in a whole genome
Chiang, S., Shinohara, H., Huang, J. H., Tsai, H. K. & Okada, M. Inferring the transcriptional regulatory mechanism of signal-dependent gene expression via an integrative computational approach. FEBS Lett. (2020).
Master's project - identification of trans-eQTL clusters resulting from changes in transcription factor binding site preference.
CRAFT: Cellular Reprogramming Analysis with Integrated Framework and Mechanistic Insight
R package to predict gene feed forward loops using mediation analysis. Analyses integrate observed miRNA and mRNA expression data and database information on gene interactions.
Comprehensive human PPI network and TF network
ATAC-Seq Transcription Factor Footprint Discovery and Analysis
target: An R Package to Predict Combined Function of Transcription Factors (workflow article)
All code generated for Loupe et al. 2023
Data challenge with kernel methods - MVA MSc
The Genomic Variations Explorer (GenVarX) is a toolset that consists of promoter region component and CNV component for users to perform queries, visualize data, and conduct annotations using genotypic and phenotypic differences.
Ligand-Receptor Interaction map based on scRNA-seq and pathway enrichment
Django-based web application to explore and analyse Human Transcription Factors
Discover transcription factor (TF) binding specificities/sites (TFBS) using binding site motif sequence and structural information.
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