Panagiotis Chrysinas

SCREAM: Single-cell Clustering using Representation Autoencoder of Multiomics

SCREAM is a deep learning framework for integrating and clustering multi-omics single-cell data, showing superior performance in benchmarking with high ARI and NMI scores.

Cell and tissue-specific glycosylation pathways informed by single-cell transcriptomics

The paper analyzes single-cell glycogene expression in human tissues to identify cell- and tissue-specific glycosylation pathways and transcription factor regulation.

CrossTx: Cross-cell line Transcriptomic Signature Predictions

CrossTx predicts drug transcriptomic signatures for unseen cell lines using reference data and correction methods, achieving accurate and efficient results.

DeltaNeTS+: Elucidating the mechanism of drugs and diseases using gene expression and transcriptional regulatory networks

DeltaNeTS+ infers direct gene targets of drugs and diseases from gene expression data, showing effectiveness in complex organisms and time-course profiles.