Shuhei Noguchi

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.

The paper identifies widespread transcription initiation at microsatellites across species and develops deep learning models to predict STR-associated transcription and its impact on disease variants.

Functional Annotation of Human Long Non-Coding RNAs via Molecular Phenotyping

The paper functionally annotates human long non-coding RNAs by systematically knocking down 285 lncRNAs and analyzing molecular phenotypes using CAGE sequencing.

Assessment of mapping strategies for determining the 5'-end of mRNAs and long-noncoding RNAs with short read sequences

The paper evaluates mapping strategies for CAGE reads to determine 5'-end sequences of mRNAs and long-noncoding RNAs, finding that strategy choice affects alignment accuracy and biological interpretation.

RADICL-seq identifies general and cell type-specific principles of genome-wide RNA-chromatin interactions

RADICL-seq maps genome-wide RNA-chromatin interactions in intact nuclei, revealing general and cell type-specific patterns of transcript occupancy and the role of transcription in chromatin structure.

Quality assessment of single-cell RNA sequencing data by coverage skewness analysis

The paper introduces SkewC, a method to identify poor quality cells in scRNA-seq by analyzing gene coverage skewness, and validates it across 37,993 cells from 15 protocols.

Combinatorial perturbation analysis reveals divergent regulations of mesenchymal genes during epithelial-to-mesenchymal transition

The paper uses combinatorial perturbations to study EMT gene regulation, finding that mesenchymal genes show diverse dependencies on TGF-β and ZEB1, with functional differences in motility and cancer survival.