George M. Spyrou

Multi-omics dissection of Parkinson's patient subgroups associated with motor and cognitive severity

The paper uses multi-omics data to identify molecular factors associated with motor and cognitive severity in Parkinson's disease and stratifies patients into subgroups with distinct severity profiles.

Machine Learning Models for Predicting Multiple Myeloma Staging and MGUS Progression Using Gene Expression Data

This study develops ML models to predict multiple myeloma staging and MGUS progression using gene expression data, achieving AUC values above 0.8 with ElasticNet and other algorithms.

Stage-specific gene ratios highlight genes and mechanisms related to presymptomatic and symptomatic Multiple Myeloma

The paper identifies stage-specific genes and pathways in Multiple Myeloma using monotonic expressed genes (MEGs) and gene pair ratios, showing their potential as biomarkers for disease progression.

DReAmocracy: A Method to Capitalize on Prior Drug Discovery Efforts to Highlight Candidate Drugs for Repurposing

DReAmocracy aggregates drug repurposing data to generate disease suitability scores for candidate drugs, identifying top-ranked drugs for neurodegenerative diseases.

Ranking of cell clusters in a single-cell RNA-sequencing analysis framework using prior knowledge

The paper introduces a method to rank cell clusters in scRNA-seq using prior knowledge and user input, enhancing biological relevance.

Immediate-Early Genes as Influencers in Genetic Networks and their Role in Alzheimer's Disease

The paper investigates the role of immediate-early genes (IEGs) in genetic networks and identifies MARK4 as a potential therapeutic target for Alzheimer's disease using network analysis and GWAS data.

Machine Learning for Predicting Therapeutic Outcomes in Acute Myeloid Leukemia Patients

This paper uses machine learning to predict drug sensitivity in AML patients using the BeatAML dataset, finding RNA sequencing data provides better predictive power than whole exome sequencing or clinical data.

In depth analysis of Cyprus-specific mutations of SARS-CoV-2 strains using computational approaches

This study identifies a Cyprus-specific SARS-CoV-2 mutation (S6059F) and assesses its potential association with increased viral virulence using computational methods.

Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches

The paper identifies viral-mediated pathogenic mechanisms in multiple sclerosis using network-based analysis of virus-host and disease-related protein interactions.

Generalized linear models provide a measure of virulence for specific mutations in SARS-CoV-2 strains

This paper uses generalized linear models to identify SARS-CoV-2 mutations associated with changes in viral virulence, highlighting two mutations with opposing effects on deaths and cases per million.

Drug Repurposing Through a Bioinformatics Pipeline Applied on Fibrotic Diseases

The paper identifies shared and unique genes, pathways, and drug candidates across nine fibrotic diseases using transcriptomics data and drug repurposing tools.

PathWalks: Identifying pathway communities using a disease-related map of integrated information

PathWalks identifies pathway communities using a disease-related map of integrated information, revealing key pathways and potential viral involvement in Alzheimer's and idiopathic pulmonary fibrosis.