Results: Here, we propose a novel computational method for predicting DNA Motif Pairs
based on Composite Heterogeneous Graph (MPCHG). This approach leverages a …

Deep neural networks (DNNs) have greatly advanced the ability to predict genome function
from sequence. Interpreting genomic DNNs in terms of biological mechanisms, however …

The advent of single-cell sequencing techniques has not only revolutionized the
investigation of biological processes but also significantly contributed to unraveling cellular …

Single nucleus ATAC-seq (snATAC-seq) experimental designs have become increasingly
complex with multiple factors that might affect chromatin accessibility, including genotype …

The Myb proto-oncogene encodes the transcription factor c-MYB, which is critical for
hematopoiesis. Distant enhancers of Myb form a hub of interactions with the Myb promoter …

Summary Transcription factor (TF)-cofactor (COF) interactions define dynamic, cell-specific
networks that govern gene expression; however, these networks are understudied due to a …

Machine learning methods that fully exploit the dual modality of single-cell RNA+ ATAC-seq
techniques are still lacking. Here, we developed ChromatinHD, a pair of models that uses …

An important and largely unsolved problem in synthetic biology is how to target gene
expression to specific cell types. Here, we apply iterative deep learning to design synthetic …

Regulatory elements are important constituents of plant genomes that have shaped ancient
and modern crops. Their identification, function, and diversity in crop genomes however are …

Transcription factors often regulate numerous target genes. However, ZNF410 controls only
a single gene, CHD4, in human erythroid cells by its highly restricted chromatin occupancy …