Attila Gábor

Mapping global transcript isoform landscapes of influenza A virus infection and interferon stimulation reveals RNA-binding protein networks associated with immune remodeling

The paper uses hybrid RNA sequencing to analyze transcript isoform changes during influenza infection and interferon treatment, identifying RNA-binding proteins involved in immune remodeling.

OmniPath: integrated knowledgebase for multi-omics analysis

OmniPath integrates molecular knowledge from 168 resources to support multi-omics analysis, offering curated data, predictions, and tools for causal modeling across bulk, single-cell, and spatial data.

Unified knowledge-driven network inference from omics data

The paper introduces CORNETO, a unified framework for knowledge-driven network inference from omics data, improving performance on biological tasks using simulated and real data.

Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results

This study evaluates how different transcriptomics analysis pipelines affect downstream functional enrichment results using FLOP, finding that data filtering significantly impacts gene set correlation.

Explainable multi-view framework for dissecting inter-cellular signaling from highly multiplexed spatial data

MISTy is a framework for analyzing spatial omics data to identify inter-cellular signaling interactions across different spatial contexts in breast cancer datasets.

Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd

The paper organizes a DREAM challenge to benchmark predictive models of single-cell signaling using mass cytometry data from breast cancer cell lines.

Deciphering the Signaling Network Landscape of Breast Cancer Improves Drug Sensitivity Prediction

The paper uses single-cell proteomics and perturbation experiments to improve drug sensitivity predictions in breast cancer and identify genomic features associated with treatment response.

Integrated intra- and intercellular signaling knowledge for multicelullar omics analysis

The paper integrates intra- and intercellular signaling knowledge into a database for multicellular omics analysis, demonstrating its application to SARS-CoV-2 infection and ulcerative colitis.

Causal integration of multi-omics data with prior knowledge to generate mechanistic hypotheses

COSMOS integrates multi-omics data with prior knowledge to generate mechanistic hypotheses about biological processes in renal cell carcinoma.

Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data

The paper predicts cellular positions in the Drosophila embryo using scRNA-seq data by benchmarking methods against spatially annotated genes.

Converting networks to predictive logic models from perturbation signalling data with CellNOpt

The paper introduces updates to CellNOpt, a tool for building logic models from perturbation data and prior knowledge networks, including new methods and an interactive interface.

Analysis of the human kinome and phosphatome reveals diseased signaling networks induced by overexpression

The paper analyzes the human kinome and phosphatome to identify signaling networks altered by protein overexpression, revealing novel relationships and mechanisms of cancer progression.