Dimitar Vassilev

发表

Object-Oriented Analysis for Design of Protein Fingerprints

Monica Dimitrova, Dimitar Vassilev, D. Vassilev, 2018, Serdica Journal of Computing.

Machine Learning Techniques for Survival Time Prediction in Breast Cancer

Dimitar Vassilev, Iliyan Mihaylov, Maria Nisheva, 2018, AIMSA.

Using neural networks to filter predicted errors in NGS data

Dimitar Vassilev, Deyan Peychev, Maria Nisheva, 2015 .

An Intelligent System Approach for Integrating Anatomical Ontologies

Peter Petrov, Dimitar Vassilev, Milko Krachunov, 2012 .

An Algorithmic Approach to Inferring Cross-Ontology Links while Mapping Anatomical Ontologies

Peter Petrov, Dimitar Vassilev, Milko Krachounov, 2012 .

An approach to a metagenomic data processing workflow

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

Predicting and Scoring Links in Anatomical Ontology Mapping

Peter Petrov, Dimitar Vassilev, Maria Nisheva, 2012 .

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

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

Fuzzy indication of reliability in metagenomics NGS data analysis

Dimitar Vassilev, Maria Nisheva-Pavlova, Milko Krachunov, 2015, ICCS.

Bioinformatics in Proteomics: A Review on Methods and Algorithms

Dimitar Vassilev, Ivan Popov, Peter Petrov, 2009 .

Application of Machine Learning Models in Error and Variant Detection in High-Variation Genomics Datasets

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

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

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

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

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

A Semi-Automated Structural Class Dependent Method for the Prediction of Protein Secondary Structures

Dimitar Vassilev, Ivan Popov, 2010 .

Manageable Workflows for Processing Parallel Sequencing Data

Dimitar Vassilev, Maria Nisheva, Milko Krachunov, 2014 .

An Approach for Semantic Data Integration in Cancer Studies

Dimitar Vassilev, Maria Nisheva-Pavlova, Iliyan Mihaylov, 2019, ICCS.

Validity of Automated Inferences in Mapping of Anatomical Ontologies

Peter Petrov, Dimitar Vassilev, Maria Nisheva, 2017, ISMIS.

Application of Machine Learning Models for Survival Prognosis in Breast Cancer Studies

Dimitar Vassilev, Iliyan Mihaylov, Maria Nisheva, 2019, Inf..

In silico Prediction of C4-related Genes by Finding Duplications Causing Pattern Deviation and Comparative Analysis of Phylogenetic Trees

Dimitar Vassilev, Milko Krachunov, Irena Avdjieva, 2019 .

Application of bioinformatics in GMO detection

Dimitar Vassilev, A. Nenov, D. Vassilev, 2006 .

Quality of Different Machine Learning Models in Error Discovery for Parallel Genome Sequencing

Dimitar Vassilev, Maria Nisheva, Milko Krachunov, 2018 .

A Semi-Automated Approach for Anatomical Ontology Mapping

Peter Petrov, Dimitar Vassilev, Milko Krachunov, 2013, J. Integr. Bioinform..

Using Machine Learning in Accuracy Assessment of Knowledge-Based Energy and Frequency Base Likelihood in Protein Structures

Dimitar Vassilev, Iliyan Mihaylov, Piotr Zielenkiewicz, 2020, ICCS.

Ontology-Based Decision Support System for Dietary Recommendations for Type 2 Diabetes Mellitus

Dimitar Vassilev, Maria Nisheva-Pavlova, Iliyan Mihaylov, 2021, ICCS.

Fusion Protein Design with Computational Homologybased Structure Prediction

Dimitar Vassilev, Irena Avdjieva, Ivan Terziyski, 2021 .

Comparative Analysis of Data Distribution Patterns in Plant Comet Assay

Dimitar Vassilev, E. Todorovska, D. Vassilev, 2010 .

Experiences with workflows for automating data-intensive bioinformatics

Ola Spjuth, Eija Korpelainen, Samuel Lampa, 2015, Biology Direct.

Estimation of Sequencing Error Rates Present in Genome Databases

Dimitar Vassilev, Ivan Popov, Valeriya Simeonova, 2012 .