Sarath Chandra Janga

The paper maps m6A modifications and polyadenylation events in Plasmodium falciparum mRNAs, identifying stage-specific m6A sites and their potential role in 3' end processing.

Higher WFS1 genotype scores (variant frame, transmembrane location) tracked earlier diabetes mellitus and optic atrophy onset in 324 Wolfram patients, not hearing loss or diabetes insipidus.

This study identifies AZIN1 A-to-I editing as a marker of kidney recovery potential following inflammation.

Penguin is a tool that uses machine learning to predict pseudouridine sites in direct RNA nanopore sequencing data, achieving high accuracy compared to existing methods.

CASowary predicts CRISPR-Cas13 guide RNA efficacy using machine learning and transcriptome data from HEK293 cells.

Nm-Nano predicts Nm sites in Nanopore RNA sequencing data with high accuracy, identifying frequently modified genes in human cell lines and their biological roles.

The paper identifies a unique long-range RNA-RNA interaction between Spike and ORF8 in SARS-CoV-2 that is not present in SARS-CoV, supported by sequence variation and in-silico predictions.

Sequoia is a visualization tool for analyzing nanopore sequencing data, using dynamic time warping and t-SNE to display signal similarities and enabling interactive exploration and export of raw signals.

The paper introduces POP-seq, a method for unbiased protein-RNA occupancy profiling, and shows it identifies interaction sites across various RNA types and associates with genomic variants.

This study systematically analyzes how SARS-CoV-2 alters RNA binding protein and miRNA-directed post-transcriptional regulatory networks in human tissues.

The paper investigates how lncRNA knockdown affects alternative splicing and RBP binding in three human cell lines, revealing cell-type specific impacts on gene regulation and function.