Alexandros Armaos

HERCULES predicts RNA-binding regions and mutation effects using a deep-learning framework combining language models and physicochemical descriptors.

PHANES provides a comprehensive, interpretable database of protein features for the human proteome, integrating sequence, structure, and expression data to support biological analysis and machine learning.

scRAPID-web predicts protein-RNA interactions from scRNA-seq data across eight organisms, offering GRN inference and visualization tools.

The paper analyzes hormone pathways in Kappaphycus alvarezii and related algae to understand their role in biostimulant activity, revealing conserved biosynthesis and divergent signaling.

This study uses RNA aptamers to detect pathological FUS in ALS, showing improved specificity and sensitivity compared to antibodies.

This paper introduces catGRANULE 2.0 ROBOT, an algorithm predicting protein LLPS at single amino acid resolution, showing high performance and experimental validation.

This paper identifies low-complexity repeats as key drivers of RNA-RNA interactions and introduces RIME, a deep learning model that outperforms traditional methods in predicting these interactions.

This paper designs aptamers targeting RAD51-BRCA2 interaction to inhibit RAD51 nuclear recruitment, enhancing DNA damage and cytotoxicity in pancreatic cancer cells.

The paper investigates how RNA modifications affect protein-RNA interactions and introduces an algorithm to predict these effects.

This study develops scRAPID, a pipeline that predicts protein-RNA interactions from single-cell transcriptomic data, showing comparable or better performance than transcription factor-target interaction prediction.

This study identifies MOK as a kinase regulating microglial inflammatory responses and type-I IFN through Brd4, showing its involvement in ALS pathogenesis.

The paper identifies and predicts RNA G-quadruplex-binding proteins, showing their roles in transcription and phase separation, and provides a web tool for prediction.

ORC1 binds to cis-transcribed RNAs from genes with replication origins at TSSs, which is required for optimal origin activation.

PRALINE is a database that catalogs proteins and RNAs in biological condensates, their interactions, and the impact of single-nucleotide variants on condensate properties.

This study identifies SAM68 as a regulator of cardiomyocyte differentiation by enhancing Gata4 translation through RNA-binding in mouse embryonic stem cells.

The paper analyzes two deep mutational scanning experiments to show that protein aggregation affects molecular evolution differently in distinct cellular contexts.

The paper analyzes the structural elements of the SARS-CoV-2 genome and predicts human protein interactions, identifying conserved regions and potential host factors involved in viral replication.

The paper investigates how Prion-Like Domains (PrLDs) and RNA-Binding Domains (RBDs) contribute to biomolecular condensation in human and yeast proteomes.

CROSSalive predicts RNA secondary structure in vivo and assesses the impact of m6A methylation using icSHAPE data and a trained model.

The paper introduces CROSSalign, a method for RNA secondary structure prediction and comparison, showing it outperforms covariance models in identifying conserved structures in lncRNAs and viruses.

The paper investigates how RNA structure influences protein interactions, showing that structured RNA competes with protein binding and alters interaction networks.