Ali Hashemi Gheinani

The paper identifies novel biomarkers for bladder outlet obstruction using transcriptomic and proteomic data from rodent models and human patients.

This study identifies a lymphoid tissue chemokine checkpoint that regulates CD8+ T cell release from dendritic cells, preventing loss of effector function.

The paper identifies essential cardiac enhancer modules and regulatory mechanisms governing heart development, revealing resilience in cis-regulatory architectures and the role of Hand2 upstream regulatory intervals.

This paper introduces a method for real-time visualization of microrobots using Color Flow Mapping ultrasound, enabling localization and activation of bubble-based microrobots.

The paper uses multi-omics analysis to study molecular changes in the bladder after spinal cord injury in rats and identifies DNA damage response pathways modulated by inosine treatment.

The paper investigates how bromodomain inhibition affects cytoskeleton stability and contraction by analyzing transcriptomic changes and the effects of MYC inhibitor JQ1 on smooth muscle cells and fibroblasts.

This paper uses machine learning to identify a three-gene mRNA signature that distinguishes non-ulcerative bladder pain syndrome from controls and detrusor overactivity patients.

MLme simplifies machine learning for researchers by integrating data exploration, AutoML, and visualization, showing promising performance across datasets and identifying cell population markers.

SpheroScan is a deep learning tool for automated spheroid image analysis that improves reproducibility and throughput in 3D spheroid assays.

The paper introduces MLcps, a Python package that combines multiple performance metrics into a single score for classification problems, tested on biological datasets to assess model robustness.