Shreya V. Mishra

This study identifies tonic signaling as a key factor in CAR-T cell efficacy for diffuse midline glioma, showing that restrained tonic signaling improves therapeutic outcomes.

The paper maps chromatin interactions in mouse fetal tissues and links them to gene expression and disease risk variants in humans.

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

SnapFISH identifies chromatin loops from multiplexed DNA FISH data with high sensitivity and accuracy in mouse embryonic stem cells.

scEpiSearch enables accurate matching of single-cell open-chromatin profiles to large reference datasets, improving co-embedding and classification of epigenomic states across species and platforms.

The paper introduces a graph-wavelet model to predict protein biophysical properties and assess mutational effects by analyzing amino-acid features in protein structures.

This paper collects and provides EEG data from students exposed to audio-visual content to analyze engagement and attention during learning.

The paper predicts gene functions using epigenomic patterns and TF binding, achieving high accuracy and validating results with CRISPR screens and PubMed data.

The paper develops a method to predict both local and long-range chromatin interactions using single-cell open-chromatin profiles, revealing insights into cis-regulatory elements in the human brain.

FITs recovers true signals from sparse and noisy single-cell open-chromatin profiles by using a forest of imputation trees to avoid bias and preserve cell-type-specific activity.

This paper introduces GWNet, a graph-wavelet method for gene-network inference that improves consistency in single-cell transcriptome analysis, revealing age-related regulatory changes in lung cells.