Jessica C. Mar

Assessing tissue-specific gene expression of essential genes from human and mouse.

The paper develops a computational method to assess tissue-specific gene expression of essential genes in human and mouse using scRNA-seq data and finds that essential genes show consistent expression across cell types with significant co-expression networks and pathway enrichment.

Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology.

This study shows senolytic drugs reduce brain aging and COVID-19-related neuropathology by targeting senescent cells in human brain organoids and mice.

Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell ageing

This study evaluates 14 metrics for measuring cell-to-cell expression variability in scRNA-seq data and applies the best-performing metric to analyze changes in variability during B cell ageing.

scShapes: A statistical framework for identifying distribution shapes in single-cell RNA-sequencing data

scShapes identifies distribution shape differences in scRNA-seq data, detecting genes with distinct expression patterns beyond mean shifts.

How does data structure impact cell-cell similarity? Evaluating the influence of structural properties on proximity metric performance in single cell RNA-seq data

This study evaluates how structural properties of scRNA-seq data affect proximity metric performance and recommends tailored approaches for improved clustering.

Deconstructing replicative senescence heterogeneity of human mesenchymal stem cells at single cell resolution reveals therapeutically targetable senescent cell sub-populations

This study identifies three distinct senescent subpopulations in human mesenchymal stem cells using single-cell RNA sequencing, revealing potential drug targets for senescence delay.

The shape of gene expression distributions matter: how incorporating distribution shape improves the interpretation of cancer transcriptomic data

This study shows that gene expression distributions in cancer data are often non-Normal, and using this information improves survival classification in cancer patients.

Aneuvis: Web-based exploration of numerical chromosomal variation in single cells

Aneuvis is a web tool that quantifies numerical chromosomal variation in single cells and compares it between treatment groups.

Single-cell analysis of Non-CpG methylation dynamics and gene expression in human oocyte maturation

The paper investigates non-CpG methylation dynamics and gene expression in human oocyte maturation, finding that non-CG DMRs correlate with gene expression changes and transcription factor binding.

A novel approach to modeling transcriptional heterogeneity identifies the oncogene candidate CBX2 in invasive breast carcinoma

The paper develops a statistical method to model transcriptional heterogeneity in breast tumors, identifying CBX2 as an oncogene overexpressed in invasive breast carcinoma and linked to poorer survival.