Shuang Li

The paper introduces hmSEEKR, a k-mer-based hidden Markov model that identifies non-linear sequence similarities in transcriptomes, revealing functional RNA domains with biological relevance.

The paper examines non-redundant roles of paralogous proteins in yeast glucose-sensing pathways through gene deletion and multi-omics analyses.

The paper compares RNA-protein associations across lncRNAs Airn, Kcnq1ot1, and Xist, identifying HNRNPU's role in long-range Polycomb recruitment by Airn and Kcnq1ot1.

The paper introduces new functions in SEEKR to calculate p-values and visualize k-mer similarity, applying them to identify chromatin-enriched lncRNAs with XIST-like fragments.

This study investigates the role of Tead4 in mouse and bovine preimplantation development, finding it essential for blastocyst formation and regulating key genes like Krt8 and Yap.

The paper identifies sequence motifs conserved in paralogous proteins despite functional divergence in post-translational modification.

This study compares two glucose receptor systems in yeast, showing they regulate distinct metabolic processes and signaling pathways.

This paper investigates the roles of G protein subunits Gpa2 and Asc1/RACK1 in glucose signaling using transcriptomics and metabolomics in yeast, finding distinct contributions to sugar and amino acid metabolism.

The paper introduces PIE, a software tool for automatically tracking microbial colony growth in low-resolution images, enabling large-scale analysis of growth and fluorescence properties.

This study quantifies vertical and horizontal pleiotropy in yeast using single-cell phenotyping, revealing context-dependent trait correlations and implications for evolutionary medicine.

The paper characterizes cell types and circuit organization within neocortical radial clones using single-cell RNA-sequencing and electrophysiological recordings, finding that clones contain diverse cell types and exhibit specific connectivity patterns.