Mikaela Koutrouli

NORMA 3.0 provides enhanced visualization and analysis of annotated biological networks with improved group representation and layout algorithms.

This study performs a single-nucleus transcriptome-wide association study to identify gene-trait associations in brain disorders, revealing cell-type-specific genetic regulation and ancestry-specific patterns.

The paper constructs a single-nucleus atlas of genetic regulation in the human brain, identifying cell-type-specific regulatory effects and disease-associated genes.

The paper introduces spatialproteomics, a Python toolbox for analyzing highly multiplexed fluorescence images, demonstrating its use on lymph node and lymphoma data.

The paper constructs a single-cell transcriptomic atlas of the human dorsolateral prefrontal cortex across neurodegenerative and neuropsychiatric diseases, revealing shared and distinct molecular mechanisms.

This study uses a ubiquitin replacement strategy to show K29-linked ubiquitylation regulates SUV39H1 stability and H3K9me3 levels in human cells.

The paper develops a Lifestyle Factor Ontology and annotated corpus for detecting lifestyle factors in biomedical texts, achieving 76% F-score with a transformer-based NER system.

The paper improves dictionary-based named entity recognition by using a Transformer model to automatically generate block lists, increasing precision in text mining.

FAVA infers high-quality functional protein interaction networks from scRNA-seq and proteomics data, outperforming existing methods and identifying interactions for understudied proteins.

This paper introduces a high-resolution spatial transcriptomics technology for mouse liver analysis, achieving 2 micrometer resolution and demonstrating significant advancements in spatial sequencing.

The paper introduces CoNECo, a corpus for NER and NEN of protein complexes, achieving F1-scores of 73.7% and 61.2% with transformer-based and dictionary-based taggers, respectively.

U-CIE encodes high-dimensional data as colors using UMAP and CIELAB to preserve structure for visualization.

NORMA-2.0 is a web tool that uses layout strategies to group annotated network elements, improving visualization of network heterogeneity.

NORMA is a web tool that visualizes and analyzes networks with annotations, allowing users to interactively explore and compare multiple networks.

The paper introduces NAP v2.0, a web tool for comparing topological features of multiple networks, offering 2D/3D visualization and interactive analysis.