James J. Collins

This paper introduces AminoX, a platform for programmable covalent protein design using non-standard amino acids, enabling efficient screening and functional validation of covalent warheads and multifunctional proteins.

This study investigates how DNA methylation and H3K9me3 maintain transgene silencing and shows that targeted DNA demethylation can reverse it in mammalian cells.

This paper engineers synthetic phosphorylation signaling networks in human cells to enable dynamic sensing and suppression of activated T cells.

This study demonstrates that O-glycosylation contributes to sialoglycoRNA biogenesis and shows increased sialylation in ulcerative colitis-derived organoids.

The paper identifies OCT4 trajectories critical for reprogramming human fibroblasts to iPSCs and develops a synthetic genetic circuit to enforce these trajectories, improving reprogramming efficiency.

The paper identifies DiSCs, regions co-bound by SETDB1 and Cohesin, which regulate genome topology and stem cell fate in mouse embryonic stem cells.

This study uses scRNA-Seq and scATAC-Seq to show that human reprogramming occurs through asynchronous, diverse trajectories with distinct regulatory networks.

A cell-free platform pairing T7 RNA polymerase, allosteric transcription factors and DNA templates yields fluorescent RNA output to detect antibiotics, small molecules and metals in water.

The paper introduces ASTAR-Seq, a method for parallel single-cell transcriptome and chromatin accessibility sequencing, and uses it to analyze mESCs, human cell lines, and erythroblast differentiation.

This paper develops a deep learning model to extract evolutionary information from glycans, revealing insights into host-pathogen interactions and phenotypic diversity.

This paper develops a language model for glycans, SweetTalk, to analyze substructure motifs, classify linkages, and predict immunogenicity with 92% accuracy.

This paper designs de-novo RNA-based translational repressors with multi-input logic capabilities for synthetic biology applications.

This study shows that compositional context in synthetic gene networks significantly affects gene expression levels and key regulatory properties.