Laraib Iqbal Malik

This paper develops a method to generate functional human pruriceptors from pluripotent stem cells using transcription factors, showing they respond to itch stimuli and drugs like ABT-317.

This study generates DRG-like neurons from hiPSCs using NGN2 overexpression and patterning factors, which respond to type 2 cytokines involved in itch.

The paper evaluates how alignment and mapping methods affect transcript quantification accuracy and introduces a new method called selective alignment.

The paper introduces a Bayesian framework for improving dscRNA-seq quantification by sharing information across cells and modalities, enhancing gene abundance estimates for multi-mapping reads.

Alevin improves gene abundance estimation in droplet-based single-cell RNA sequencing by accurately handling UMI deduplication for both gene-unique and gene-ambiguous reads.

GRASS improves de novo transcriptome annotation by using graph regularization and semi-supervised learning to enhance completeness and accuracy.

The paper introduces a method to predict hierarchical chromatin domains from Hi-C data, showing conservation across cell types and species.