Itai Yanai

The paper shows cancer cells adapt along a proliferation-robustness axis in response to TME components, leading to pro-tumor phenotypes.

This study shows that lymph nodes actively drive melanoma evolution and immune evasion, linking regional metastasis to poor patient outcomes.

This study shows mechanical confinement drives phenotype switching in melanoma via chromatin remodeling mediated by HMGB2.

This study identifies genotype-specific immune and metabolic vulnerabilities in lung adenocarcinoma through cross-species analysis of human and mouse tumors.

The paper shows that desmosome mutations in keratinocytes of the tumor microenvironment promote melanoma proliferation through reduced desmosome gene expression and increased melanoma cell growth.

This study uses scRNA-seq to analyze transcriptional changes in human macrophages and Encephalitozoon intestinalis parasites during infection, revealing parasite developmental dynamics and host response.

The paper identifies 119 cell-states in C. elegans embryos during early development, revealing lineage-specific gene regulatory programs that encode cell position and fate.

This study introduces a genome-wide classification of regulatory modes in bacteria by analyzing transcription-replication interactions, revealing new insights into gene expression dynamics and regulatory context.

The paper transplants the human adenine de novo pathway into yeast to study regulatory mechanisms, finding that PPAT/ADE4 is a central regulatory node influenced by metabolites and mutations.

The paper introduces APA-seq to analyze alternative polyadenylation isoforms in C. elegans embryos, finding that distinct 3' UTR isoforms correlate with developmental stages and selective pressures.

This paper introduces ENHANCE, a denoising method for single-cell RNA-Seq data using PCA with a cell aggregation step, showing improved accuracy over existing methods.

This study integrates single-cell RNA-Seq and spatial transcriptomics data from pancreatic cancer tissue to map cell type spatial distributions and infer tissue architecture.

Chained linear SVMs on kNN-smoothed, PCA-transformed scRNA-seq classify closely related PBMC subtypes across 10x chemistries, plus a 'mirror validation' check that estimates accuracy without ground truth.

Aggregating UMI counts from a cell's nearest neighbours, chosen step-wise on variance-stabilised profiles, cuts technical noise enough that PCA and hierarchical clustering resolve cell types and T cell subsets.