Emek Demir

scOPE identifies which driver-associated expression programs transfer from bulk tumors to single cells

scOPE transfers driver-associated expression programs from bulk tumors to single cells, identifying selective programs with high predictive accuracy.

MiroSCOPE: An AI-driven digital pathology platform for annotating functional tissue units

MiroSCOPE is an AI platform for annotating functional tissue units in digital pathology, enabling efficient annotation of over 71,900 units across prostate cancer samples.

Unifying multimodal single-cell data with a mixture-of-experts β-variational autoencoder framework

UniVI integrates multimodal single-cell data using a mixture-of-experts β-variational autoencoder, improving cross-modal alignment and label transfer across various data types and study designs.

Selective enrichment of plasma cell-free messenger RNA in cancer-associated extracellular vesicles

The paper analyzes cf-mRNA in EVs and non-vesicular carriers from cancer patients and healthy donors, finding EVs selectively enrich cf-mRNA associated with specific biological pathways.

Predicting transcription factor activity using prior biological information

This paper introduces Priori, a method to predict transcription factor activity from RNA sequencing data, showing it outperforms existing methods in detecting aberrant activity and identifying disease-related factors.

Capturing scientific knowledge in computable form

The paper introduces Biofactoid, a tool that crowdsources structured biological knowledge from authors, enabling efficient human-computer interaction and expanding existing pathway databases.

Causal interactions from proteomic profiles: molecular data meets pathway knowledge

The paper introduces a computational method to generate causal explanations for proteomic profiles by integrating molecular data with prior biological pathway knowledge, demonstrating its application in various biological contexts.

Systematic interrogation of mutation groupings reveals divergent downstream expression programs within key cancer genes

The paper systematically examines mutation groupings in cancer genes to identify downstream expression programs and reveals functional divergence among mutations within the same gene.

Pathway Commons: 2019 Update

Pathway Commons updates its resource with integrated pathway data, tools, and software for biological pathway analysis.

PaxtoolsR: Pathway Analysis in R Using Pathway Commons

PaxtoolsR provides R access to pathway data from Pathway Commons, enabling extraction, merging, validation, and integration with local BioPAX datasets.

Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations

The paper identifies cancer driver pathways by detecting mutual exclusivity patterns in genomic alterations across TCGA datasets, revealing previously unreported driver events.

Cancer-associated recurrent mutations in RNase III domains of DICER1

The paper identifies recurrent DICER1 mutations in cancer that disrupt miRNA processing and cause mRNA expression imbalances, contributing to oncogenesis.

Perturbation biology models predict c-Myc as an effective co-target in RAF inhibitor resistant melanoma cells

The paper uses perturbation biology to predict c-Myc as a co-target with BRAF/MEK inhibitors to overcome RAF inhibitor resistance in melanoma.