Lincoln David Stein

Apollo 3: Multi-Species Genome Curation

Apollo 3 is a new manual genome annotation tool that integrates with JBrowse 2, enabling multi-genome editing and synteny visualization.

Medulloblastoma Forms Symbiotic Metabolic Partnerships with Macrophages to Establish Leptomeningeal Metastases

This study identifies metabolic partnerships between medulloblastoma and macrophages that drive leptomeningeal metastases and suggests targeting the CXCL12-SCARB1-cholesterol axis as a therapeutic strategy.

Ependymomas are cancers of the pre-neural crest/roof plate lineage

The paper identifies ependymomas as originating from the pre-neural crest/roof plate lineage using single-cell transcriptomics and lineage tracing.

Application of Large Language Models for Annotating Genes into Reactome Pathways

This paper applies large language models to assist in gene annotation into Reactome pathways, showing promising results in supporting curation workflows.

React-to-Me: A Conversational Interface for Interactive Exploration of the Reactome Pathway Knowledgebase.

React-to-Me, a retrieval-augmented chatbot grounding GPT-4o-mini in curated Reactome pathways with hyperlinked citations, earned higher blinded expert ratings than ungrounded GPT-4o-mini (odds ratio 2.01).

In silico generation of synthetic cancer genomes using generative AI

The paper introduces OncoGAN, a generative AI tool that creates synthetic cancer genomes to address the lack of gold-standard datasets for benchmarking cancer genome analysis tools.

OmniPert: A Deep Learning Foundation Model for Predicting Responses to Genetic and Chemical Perturbations in Single Cancer Cells

OmniPert predicts responses to genetic and chemical perturbations in single cancer cells using a deep learning model trained on diverse cellular profiles.

Interpreting Attention Mechanisms in Genomic Transformer Models: A Framework for Biological Insights

This paper introduces a framework to interpret attention mechanisms in genomic transformer models by correlating attention scores with biological annotations, showing how biological features are learned through pre-training and fine-tuning.

BRCA1 is a molecular correlate of cell proliferation in human brain development and in Group 3 and 4 medulloblastoma

The paper shows BRCA1 correlates with proliferation in human neural progenitor cells and medulloblastoma, particularly in Group 3 and 4 tumors, and is linked to worse prognosis.

Synergistic RAS-MAPK and AKT Activation in MYC-Driven Tumors via Adjacent PVT1 Rearrangements

This paper identifies how PVT1 rearrangements in MYC+ cancers generate oncogenic peptides that synergistically activate MYC, AKT, and RAS-MAPK pathways, enhancing tumor aggressiveness.

FAIR Header Reference genome: A TRUSTworthy standard

The paper introduces FHR, a metadata standard for reference genome data to improve interoperability and data provenance tracking across platforms.

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

The paper annotates disease variants in the context of biological pathways to infer molecular phenotypes and model variant impacts.

Drug Response Prediction and Biomarker Discovery Using Multi-Modal Deep Learning

This paper introduces a multi-modal deep learning algorithm for drug response prediction that improves generalizability by integrating diverse cell line data and addressing data skewness.

Updates to the Alliance of Genome Resources Central Infrastructure

The paper updates the Alliance of Genome Resources' central infrastructure, adding tools and enhancing data management and curation capabilities.

ChatGPT usage in the Reactome curation process

This paper explores using ChatGPT in Reactome curation to automate pathway annotation, comparing its outputs to manual curation and identifying challenges and improvements.

Illuminating Dark Proteins using Reactome Pathways

The paper predicts functional interactions of dark proteins with Reactome pathways using a random forest classifier and develops a web portal to visualize these interactions.

JBrowse 2: A modular genome browser with views of synteny and structural variation

JBrowse 2 is a genome browser with enhanced views for structural variation and synteny, offering modular design and multiple usage options.

JBrowse Jupyter: A Python interface to JBrowse 2

JBrowse Jupyter provides a Python interface to JBrowse 2 for interactive genomic visualization within Jupyter notebooks.

Reconstructing complex cancer evolutionary histories from multiple bulk DNA samples using Pairtree

Pairtree reconstructs clone trees from multiple bulk DNA samples to infer cancer evolutionary histories with higher accuracy and scalability.

JBrowse Connect: A server API to connect JBrowse instances and users

JBrowse Connect enables live messaging, notifications, and user-initiated analyses in JBrowse via WebSockets, with JBlast as an example application for BLAST searches integrated with Galaxy.

Quantifying Immune-Based Counterselection of Somatic Mutations

The paper quantifies immune-based counterselection of somatic mutations by analyzing their depletion in MHC class I-displayed peptides and shows that MHC alleles are incompletely dominant.

Tumor mutational landscape is a record of the pre-malignant state

The paper predicts cancer cell-of-origin from DNA sequences by matching mutational landscapes to chromatin modification patterns in normal tissues.

Whole Genomes Define Concordance of Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer

The paper compares whole-genome data from primary pancreatic cancer, xenografts, and organoids to assess genetic concordance across different models.

Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes

The paper identifies and characterizes coding and non-coding driver mutations across 2,500 cancer genomes, revealing new candidates and questioning previous findings.

DriverPower: Combined burden and functional impact tests for cancer driver discovery

DriverPower identifies cancer driver mutations by combining mutational burden and functional impact scores, outperforming existing methods in coding and non-coding driver discovery.

Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments

The paper describes the PCAWG project's large-scale analysis of cancer whole genomes across multiple computing environments, producing validated consensus variants for downstream research.