M. Krachunov

发表

A novel framework for horizontal and vertical data integration in cancer studies with application to survival time prediction models

Maciej M Kańduła, Iliyan Mihaylov, D. Vassilev, 2019, Biology Direct.

A Semi-Automated Approach for Anatomical Ontology Mapping

D. Vassilev, M. Krachunov, P. Petrov, 2013, Journal of integrative bioinformatics.

Machine Learning Models for Error Detection in Metagenomics and Polyploid Sequencing Data

Dimitar Vassilev, Maria Nisheva, Milko Krachunov, 2019, Inf..

Machine Learning-Driven Noise Separation in High Variation Genomics Sequencing Datasets

Dimitar Vassilev, Maria Nisheva, Milko Krachunov, 2018, AIMSA.

Experiences with workflows for automating data-intensive bioinformatics

David P. Kreil, Paweł P. Łabaj, L. Pireddu, 2015, Biology Direct.

A novel framework for horizontal and vertical data integration in cancer studies with application to survival time prediction models

Maciej M Kańduła, Iliyan Mihaylov, D. Vassilev, 2019, Biology Direct.

Machine learning models in error and variant detection in high-variation high-throughput sequencing datasets

Dimitar Vassilev, Maria Nisheva, Milko Krachunov, 2017, ICCS.

Algorithm for error detection in metagonomics NGS data

P. Siedlecki, Paweł Szczęsny, D. Vassilev, 2012 .

An approach to a metagenomic data processing workflow

Dimitar Vassilev, Milko Krachunov, D. Vassilev, 2014, J. Comput. Sci..