Narayanan Gopalakrishna Iyer

This paper identifies a signature of anti-tumour activity in CD8+ T-cells across oral cancers using single-cell RNA and TCR sequencing, and develops a machine learning classifier to detect these cells from transcriptome data.

This study benchmarks Nanopore long read RNA sequencing in human cell lines, showing improved isoform resolution compared to short reads.

The paper constructs a comprehensive mass spectral library for human thyroid tissues to improve the detection of malignant nodules through proteomic analysis.

The paper identifies a novel mutational signature in Asian oral squamous cell carcinomas linked to bacterial infections, specifically colibactin.

The paper introduces DPHL, a pan-human protein mass spectrometry library built using DIA and PRM, and demonstrates its utility in identifying differentially expressed proteins in prostate cancer and DLBCL.

This paper develops a deep learning method using DIA tensor for phenotype prediction from mass spectrometry data, achieving high accuracy in cancer classification.

The paper identifies and functionally characterizes tRNA-derived small RNAs (tsRNAs) in cell state transitions, showing their role in regulating translation and stem cell states.