Biomedical subjects

Ziwei Chen

Publications and source records attributed to Ziwei Chen.

4 recordsLinked to original sources

PubMed2026

Bayesian inference of lineage trees by joint analysis of single-cell multimodal lineage-tracing data with BiLinT.

The advent of single-cell lineage-tracing technologies has enabled the simultaneous profiling of gene expression and lineage barcodes. However, accurate, high-resolution reconstruction of cell lineage trees remains challenging because most existing approaches treat these modalities separately and therefore fail to fully exploit their complementary information. Here we present BiLinT, a Bayesian framework that jointly models multimodal single-cell lineage-tracing data for lineage tree reconstruction. BiLinT integrates barcode evolution (a continuous-time Markov chain) with gene expression dynamics (an Ornstein-Uhlenbeck process) within a unified probabilistic model. Across synthetic and real data sets, BiLinT provides accurate lineage-tree reconstruction and reveals differentiation-associated clonal structure and developmental fate biases.

Journal Article↗

PubMed2026

Internal Bayesian precision modulates the neural representation of social attention: Disentangling implicit and explicit components via model-informed multivariate EEG analysis.

Social attention integrates sensory cues with high-level cognitive expectations, yet the generative mechanisms through which implicit orienting and explicit belief-driven modulation interact remain poorly understood. This ambiguity complicates the distinction between specialized social modules and domain-general attentional processes. We combined a dynamic cueing task with hierarchical Bayesian modeling and model-informed multivariate EEG decoding to address this. Behavioral results revealed a computational double dissociation: symbolic arrow cues elicited heterogeneous strategies, whereas averted gaze recruited a consistent, surprise-driven computational phenotype. At the neural level, time-resolved decoding and temporal generalization revealed a critical representational shift starting approximately 400 ms post-cue. Initial activity related to physical cue features was rapidly replaced by stable neural templates of predicted spatial intent. Crucially, topographical activation patterns showed that this intentional template, characterized by a lateralized temporo-occipital distribution, emerged exclusively under high internal certainty. Furthermore, partial representational similarity analysis demonstrated that late-stage neural manifolds were overwhelmingly organized around integrated spatial goals rather than isolated sensory or motivational signals. These findings suggest that social attention is a specialized generative process, where internal certainty modulates the transformation of social perceptions into actionable top-down intentions.

Bayesian computational modeling↗

PubMed2026

Massively parallel characterization and predictive modelling of neuronal regulatory variation.

Disease-associated variants reside frequently in noncoding cis-regulatory elements (CREs), yet their functional consequences remain poorly understood. We performed a large-scale lentiMPRA in human excitatory neurons, quantifying the impact of >46,000 naturally occurring variants across >27,000 candidate CREs near 524 disease-associated genes. These data improved regulatory variant effect predictions beyond state-of-the-art models. Significant allelic effects occurred at comparable rates across common, rare, and singleton variants, demonstrating that, within MPRA-measurable effects, population frequency carries limited information about per-variant regulatory impact. Variant effect detectability and magnitude were governed primarily by baseline activity of the enclosing regulatory element and local sequence context. Regulatory effects were distributed across numerous transcription factors rather than concentrated in master regulators, consistent with a combinatorial enhancer architecture. We establish a large-scale functional variant catalog and provide a complementary benchmark and resource for developing and evaluating models of noncoding regulatory variation.

Journal Article↗

PubMed2026

Quantitative molecular cartography of emergency myelopoiesis reveals conserved modules of hematopoietic activation.

Hematopoietic stem and progenitor cells (HSPCs) respond to infections, inflammation, and regenerative challenges using emergency myelopoiesis (EM) pathways to amplify myeloid cell production. However, it remains unclear how various EM inducers regulate HSPCs using shared or distinct molecular mechanisms. Here, we generate a comprehensive and generalizable cell annotation method (HemaScribe) and a refined quantitative model of hematopoietic differentiation (HemaScape) using single-cell RNA sequencing (scRNA-seq) of murine HSPCs, which we apply to a broad range of EM modalities. We uncover multiple strategies for enhancing myelopoiesis that act at different levels of the HSPC hierarchy and are associated with both unique and shared transcriptional response modules. In particular, we identify a myeloid progenitor-based EM activation module across diverse inflammatory challenges that is conserved in humans and informs outcomes in adult and pediatric acute myeloid leukemia. Our work illuminates fundamental regulatory mechanisms in hematopoietic regeneration that have direct translational applications in disease contexts.

Animals↗