Zhichao Miao

The paper constructs a single-cell atlas of the human lung across the lifespan, identifying new cell types and regenerative mechanisms linked to lung diseases.

The paper shows short RNAs can form complex structures like icosahedrons and filaments, expanding the known RNA quaternary structures and supporting RNA-based self-assembly in an RNA world.

The paper develops a CSF proteomic aging clock that predicts age and disease progression, identifying opposing aging programs associated with neurological disorders.

The paper determines the structure and catalytic mechanism of two new HDV ribozymes from a nematode and a virus, revealing a unique Lewis acid mechanism distinct from other ribozymes.

scDenorm reverts normalized single-cell omics data to raw counts to improve integration and reduce biases in downstream analysis.

The paper describes a Kaggle competition for RNA 3D structure prediction, showing that template-based methods can outperform deep learning approaches.

This study shows that influenza infection in juvenile mice causes lifelong multi-organ damage and Parkinsonian changes in aging, with persistent inflammation and secreted proteins mediating systemic effects.

RNAcentral integrates literature and gene-level data to enhance non-coding RNA sequence analysis and functional understanding.

This study identifies 5,053 novel virus long non-coding RNAs (vlncRNAs) across 25 viral species and finds that many structurally mimic host lncRNAs, potentially acting as miRNA sponges.

RPcontact predicts RNA-protein contacts using RNA and protein language models, outperforming existing methods on contact prediction.

This study analyzes the virome in SLE patients and controls, finding higher viral positivity in patients and suggesting viral infections may worsen disease severity.

This study shows that a CTCF R567W mutation causes developmental disorders by altering 3D genome structure and neurodevelopmental pathways in mouse and human models.

This paper evaluates 31 cell-type deconvolution methods across human and mouse tissues, identifies regression-based methods as effective, and introduces the CATD pipeline for reproducible analysis.

This study benchmarks cross-species integration methods for single-cell RNA-seq data, finding that scANVI, scVI, and SeuratV4 balance species mixing and biology conservation.

This study creates a single-cell atlas of human liver development, identifying pathways and factors that guide hepatic cell fates and improving hepatocyte-like cell functionality.

The paper reports RNA 3D structure prediction results for SARS-CoV-2 5'- and 3'-UTRs using computational methods and expert analysis.

The paper evaluates the stereochemical quality of RNA 3D models from RNA-Puzzles submissions and identifies deviations from standard RNA stereochemistry.

The paper performs a meta-analysis of single-cell RNA data from 9 studies to identify consistent immune response patterns in COVID-19 patients, finding consistent upregulation of type I interferon and downregulation of mitochondrial genes.

The paper introduces an interactive scRNA-Seq analysis environment based on Galaxy, integrating ~70 functions for scalable and accessible single-cell data analysis.

BBKNN integrates multiple mouse single cell RNA-Seq datasets into a unified landscape by efficiently removing batch effects and revealing cell type and organ-specific markers.

The paper uses single-cell transcriptomics to map hematopoiesis in human fetal liver, identifying cell differentiation trajectories and shifts in hematopoietic composition during development.

This paper introduces kBET, a new metric to assess batch effects in scRNA-seq data and evaluates its effectiveness compared to existing methods.

This study compares the sensitivity and accuracy of the BGISEQ-500 and Illumina HiSeq platforms for single-cell RNA sequencing using a standardized resource of 468 unique single-cells and 1,297 matched single cDNA samples.