A5047117431- Single-cell and spatial transcriptomics
- Molecular Biology Techniques and Applications
- Cell Image Analysis Techniques
- 3D Printing in Biomedical Research
- RNA modifications and cancer
- Genetics, Aging, and Longevity in Model Organisms
- Molecular Communication and Nanonetworks
- Cancer-related molecular mechanisms research
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- RNA Research and Splicing
- Galectins and Cancer Biology
- Alzheimer's disease research and treatments
- CAR-T cell therapy research
- Epigenetics and DNA Methylation
- Immunodeficiency and Autoimmune Disorders
- Glycosylation and Glycoproteins Research
- Advanced Fluorescence Microscopy Techniques
- Eosinophilic Disorders and Syndromes
- Monoclonal and Polyclonal Antibodies Research
- Autoimmune Bullous Skin Diseases
- Prion Diseases and Protein Misfolding
- Advanced biosensing and bioanalysis techniques
- Gene expression and cancer classification
- Autoimmune and Inflammatory Disorders
Massachusetts Institute of Technology
2025
University of California, San Diego
2020-2024
Universidad Católica Santo Domingo
2023
University Hospital Heidelberg
2023
Heidelberg University
2023
University of California, San Francisco
2020-2021
Joint BioEnergy Institute
2018
Abstract Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, tissue microenvironment. Single-cell technologies measure the molecules mediating cell–cell communication, emerging computational tools can exploit these data to decipher communication. However, current methods either disregard context or rely on simple pairwise comparisons between samples, thus limiting ability complex across multiple...
Disabling pansclerotic morphea (DPM) is a rare systemic inflammatory disorder, characterized by poor wound healing, fibrosis, cytopenias, hypogammaglobulinemia, and squamous-cell carcinoma. The cause unknown, mortality high.We evaluated four patients from three unrelated families with an autosomal dominant pattern of inheritance DPM. Genomic sequencing independently identified heterozygous variants in specific region the gene that encodes signal transducer activator transcription 4 (STAT4)....
Cell-cell interactions shape cellular function and ultimately organismal phenotype. Interacting cells can sense their mutual distance using combinations of ligand-receptor pairs, suggesting the existence a spatial code, i.e., signals encoding properties organization. However, this code driving sustaining organization remains to be elucidated. Here we present computational framework infer underlying cell-cell from transcriptomes cell types across whole body multicellular organism. As core...
In recent years, data-driven inference of cell-cell communication has helped reveal coordinated biological processes across cell types. Here, we integrate two tools, LIANA and Tensor-cell2cell, which, when combined, can deploy multiple existing methods resources to enable the robust flexible identification programs samples. this work, show how integration our tools facilitates choice method infer subsequently perform an unsupervised deconvolution obtain summarize insights. We explain...
Both RNA-Seq and sample freeze-thaw are ubiquitous. However, knowledge about the impact of on downstream analyses is limited. The lack common quality metrics that sufficiently sensitive to RNA degradation, e.g. Integrity Score, makes such assessments challenging.Here we quantify repeated cycles reliability by examining poly(A)-enriched ribosomal depleted RNA-seq from frozen leukocytes drawn a toddler Autism cohort. To do so, estimate relative noise, or percentage random counts, separating...
Abstract Cancer metastasis, a process in which cancer cells migrate to secondary sites, accounts for 90% of deaths. While many machine learning models have been developed and applied predict they tend be restricted tumor types or classification tasks. Here, we apply pan-cancer model that is easily interpretable directly links the transcriptomic proteomic profiles hundreds cell lines with metastasis tissue-agnostic manner. We show that, relatively small sample size here, linear perform just...
Abstract Multiphoton microscopy is a powerful technique for deep in vivo imaging scattering samples. However, it requires precise, sample-dependent increases excitation power with depth order to generate contrast tissue, while minimizing photobleaching and phototoxicity. We show here how adaptive can optimize illumination at each point 3D volume as function of the sample’s shape, without need specialized fluorescent labeling. Our method relies on training physics-based machine learning model...
Abstract Cell-cell interactions shape cellular function and ultimately organismal phenotype. However, the code embedded in molecular driving sustaining spatial organization of cells remains to be elucidated. Here we present a computational framework infer underlying cell-cell from transcriptomes cell types across whole body multicellular organism. As core this framework, introduce our tool cell2cell , which uses coexpression ligand-receptor pairs compute potential for intercellular...
In recent years, data-driven inference of cell-cell communication has helped reveal coordinated biological processes across cell types. While multiple tools exist, results are specific to the tool choice, due diverse assumptions made computational frameworks. Moreover, often limited analyzing single samples or performing pairwise comparisons. As experimental design complexity and sample numbers continue increase in single-cell datasets, so does need for generalizable methods decipher such...
Abstract Cell-cell communication involves multiple classes of molecules, diverse interacting cells, and complex spatiotemporal dynamics. While this can be inferred from single-cell RNA-seq, no computational methods account for both protein metabolite ligands simultaneously, while also accounting the temporal We adapted Tensor-cell2cell here to study several time points simultaneously jointly incorporate ligand types. Our approach detects dynamics cell-cell during brain development, allowing...
Abstract Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, emerging computational tools can exploit these data to decipher communication. However, current methods either disregard context or rely on simple pairwise comparisons between samples, thus limiting ability complex across multiple...
Abstract The secretory pathway processes >30% of mammalian proteins, orchestrating their synthesis, modification, trafficking, and quality control. However, its complexity— spanning multiple organelles dependent on coordinated protein interactions—limits our ability to decipher how secretion is controlled in biomedical biotechnological applications. To advance such research, we present secRecon—a comprehensive reconstruction the pathway, comprising 1,127 manually curated genes organized...
Abstract A hallmark of amyloid disorders, such as Alzheimer’s disease, is aggregation secreted proteins. However, it largely unclear how the hundreds secretory pathway proteins contribute to formation. We developed a systems biology framework that integrates expression data with protein-protein interaction networks successfully estimate tissue’s fitness for producing specific Using this framework, we analyzed various brain regions and cell types synthesizing disease-associated...
Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by allows it manage these optimize their phenotypes. In fact, the management constraints (e.g., nutrient availability, bioenergetic capacity, macromolecular machinery production) shape activity ultimately impact mammalian systems, quantification provides important insights into higher-order...
Summary The anti-tumor function of engineered T cells expressing chimeric antigen receptors (CARs) is dependent on signals transduced through intracellular signaling domains (ICDs). Different ICDs are known to drive distinct phenotypes, but systematic investigations into how ICD architectures direct cell function—particularly at the molecular level—are lacking. Here, we use single-cell sequencing map diverse inputs transcriptional outputs, focusing a defined library clinically relevant...
Multiphoton microscopy is a powerful technique for deep in vivo imaging scattering samples. However, it requires precise, sample-dependent increases excitation power with depth order to maintain signal while minimizing photodamage. We show that cells identical fluorescent labels imaged situ can be used train physics-based machine learning model solves this problem. After training has been performed, the correct illumination predicted and adaptively adjusted at each point 3D volume on...
Abstract RNA-Seq is ubiquitous, but depending on the study, sub-optimal sample handling may be required, resulting in repeated freeze-thaw cycles. However, little known about how each cycle impacts downstream analyses, due to a lack of study and limitations common RNA quality metrics, e.g., RIN, at quantifying degradation following freeze-thaws. Here we quantify impact reliability analysis. To do so, developed method estimate relative noise between technical replicates independently RIN....