Alireza Fotuhi Siahpirani

Integrated RNA-seq analysis identifies ABC transporters mediating taxane export in Taxus species

The paper evaluates RNA-seq preprocessing pipelines to identify ABC transporters involved in taxane export in Taxus species, showing the importance of batch correction for accurate gene discovery.

sCIN: A Contrastive Learning Framework for Single-Cell Multi-omics Data Integration

sCIN integrates single-cell multi-omics data using contrastive learning, outperforming existing methods on paired and unpaired datasets.

Uncovering Functional Gene Regulatory Networks in Bulk and Single-Cell Data through Robust Transcription Factor Activity Estimation and Model-Guided Experimental Validation

The paper introduces MERLIN+P+TFA to robustly estimate transcription factor activity and infer gene regulatory networks from bulk and single-cell data, showing improved accuracy in yeast and mammalian systems.

Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq data

The paper benchmarks eleven network inference methods on scRNA-seq datasets to evaluate their performance in recovering gene regulatory networks.

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

This paper introduces scMTNI, a framework to infer cell type-specific gene regulatory networks on cell lineages using scRNA-seq and scATAC-seq data, showing its effectiveness on simulated and real datasets.

Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder

The paper identifies novel risk genes for autism spectrum disorder using transcriptome-wide transmission disequilibrium analysis across 7,805 ASD proband-parent trios.

Dynamic regulatory module networks for inference of cell type-specific transcriptional networks

This paper introduces DRMN, a method to infer cell type-specific transcriptional networks from multi-omic data, showing it accurately predicts cis-regulators and models network dynamics.

Human iPSC modeling reveals mutation-specific responses to gene therapy in Best disease

This study uses iPSC-RPE models to evaluate gene augmentation and editing for Best disease, finding that some mutations respond to gene therapy while others require genome editing.

Defining reprogramming checkpoints from single-cell analysis of induced pluripotency

This study identifies reprogramming checkpoints in iPSC generation by analyzing single-cell transcriptomes and reveals key gene interactions and regulatory mechanisms.

Imputed gene associations identify replicable trans-acting genes enriched in transcription pathways and complex traits

The paper identifies trans-acting genes associated with complex traits by correlating cis-predicted gene expression with observed expression across tissues.