Haris Vikalo

XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer Samples

XVir uses a transformer-based deep learning model to detect viral DNA in cancer samples, achieving high accuracy and efficiency compared to existing methods.

Graph-Based Reconstruction and Analysis of Disease Transmission Networks using Viral Genomic Data

The paper presents a framework using viral genomic data to reconstruct disease transmission networks, detect clusters, and identify significant nodes, outperforming existing methods on synthetic and experimental data.

A Convolutional Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction

This paper introduces a convolutional auto-encoder for haplotype assembly and viral quasispecies reconstruction, showing improved accuracy and efficiency over existing methods.

A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction

This paper introduces a graph auto-encoder for haplotype assembly and viral quasispecies reconstruction, showing improved performance over existing methods on synthetic and experimental data.

Sparse Tensor Decomposition For Haplotype Assembly Of Diploids And Polyploids

The paper introduces AltHap, a method for haplotype assembly in diploids and polyploids using sparse tensor decomposition, showing improved performance over existing techniques for polyploids.

aBayesQR: A Bayesian method for reconstruction of viral populations characterized by low diversity

This paper introduces aBayesQR, a Bayesian method for reconstructing viral quasispecies from sequencing data, showing improved performance on low-diversity viral populations.

Viral Quasispecies Reconstruction via Correlation Clustering

This paper introduces QSdpR, a correlation clustering method for viral quasispecies reconstruction, showing improved accuracy over existing methods on synthetic and real data.