Adam Cain Resnick

The paper uses a convolutional neural network to predict chromatin organization disruptions caused by somatic structural variants in pediatric tumors, identifying high-impact SVs and regions associated with cancer.

The paper analyzes splicing in 729 pediatric brain tumors, identifies splicing-defined subgroups, and highlights CLK1 exon 4 as an oncofetal event linked to tumor prognosis.

The paper introduces a knowledge graph framework for integrating and querying biomedical data across domains, demonstrating its utility in eight use cases.

The paper identifies a NRCAM proteoform with skipped microexons as a targetable surface antigen in pHGG and demonstrates its utility in immunotherapy.

The paper introduces OpenPedCan, a harmonized multi-omic dataset of pediatric cancer patients, providing integrated genomic, transcriptomic, and proteomic data for research and clinical applications.

The paper introduces a web-based platform for building bioinformatics workflows using APIs, enabling hypothesis generation across multiple data sources.

AutoGVP classifies germline variants using ClinVar and modified InterVar criteria, enabling large-scale variant pathogenicity assessment in research.

OpenPBTA provides a collaborative platform to genomically characterize 1,074 pediatric brain tumors and 22 cell lines, offering analysis modules and somatic datasets for research and clinical applications.

The paper identifies four immune clusters in pediatric nervous system tumors using RNA-seq data and validates them with multiple methods, highlighting the need for personalized immunogenomic profiling.

annoFuse filters and prioritizes oncogenic gene fusions from RNA-Seq data, improving identification of clinically relevant fusions in cancer datasets.