G. Mirceva

发表

Protein Binding Sites Prediction Using Ensembles

A. Kulakov, G. Mirceva, 2013 .

MODELLING THE RELATIONSHIP BETWEEN SATURATED OXYGEN AND DISTOMS‘ ABUNDANCE USING WEIGTHED PATTERN TREES WITH ALGEBRAIC OPERATORS

G. Mirceva, A. Naumoski, K. Mitreski, 2018 .

Improvement of protein binding sites prediction by selecting amino acid residues' features.

Georgina Mirceva, Andrea Kulakov, A. Kulakov, 2015, Journal of structural biology.

Protein Classification Based on 3D Structures and Fractal Features

Slobodan Kalajdziski, Georgina Mirceva, Danco Davcev, 2009, ICT Innovations.

TREES FOR PROTEIN BINDING SITES PREDICTION USING WEIGHTED AVERAGING FUZZY AGGREGATION OPERATORS

A. Kulakov, G. Mirceva, 2014 .

Classification of Protein Structures Using Deep Learning Models

A. Kulakov, G. Mirceva, A. Naumoski, 2022, 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO).

Hierarchical Protein Classification based on Gene Ontology and Decision Trees

K. Trivodaliev, I. Ivanoska, S. Kalajdziski, 2010 .

Spatial Relationship between Schools Population and Book Related Services in Skopje

G. Mirceva, A. Naumoski, N. Netkovska, 2022, 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO).

Implication of Hamacher T-norm on Two Fuzzy- Rough Rule Induction Algorithms

G. Mirceva, A. Naumoski, K. Mitreski, 2022, 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO).

Influence of the Yu T-norm on Vaguely Quantified Rough Set Measure Algorithm Accuracy

G. Mirceva, A. Naumoski, K. Mitreski, 2022, 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).

SVM based approaches for classifying protein tertiary structures

Georgina Mirceva, Danco Davcev, D. Davcev, 2011, 2011 International Conference on Data and Knowledge Engineering (ICDKE).

A Protein Classifier Based on SVM by Using the Voxel Based Descriptor

Georgina Mirceva, Danco Davcev, Andreja Naumoski, 2010, RSCTC.

Network Embedding: An Overview pdf

Nino Arsov, Georgina Mirceva, Nino Arsov, 2019, ArXiv.

HMM Approach for Classifying Protein Structures

Georgina Mirceva, Danco Davcev, D. Davcev, 2009, FGIT.

HMM based approach for classifying protein structures

Georgina Mirceva, Danco Davcev, D. Davcev, 2009 .

Evaluation of diatoms biodiversity models by applying different discretization on the class attribute

G. Mirceva, A. Naumoski, K. Mitreski, 2020, 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO).

Classifying Protein Structures by Using Protein Ray Based Descriptor, KNN and FuzzyKNN Classification Methods

G. Mirceva, A. Naumoski, A. Kulakov, 2020, 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO).

Efficient Approaches for Retrieving Protein Tertiary Structures

Georgina Mirceva, Danco Davcev, Zoran Dimov, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Top-Down Approach for Protein Binding Sites Prediction Based on Fuzzy Pattern Trees

Georgina Mirceva, Andrea Kulakov, A. Kulakov, 2012, ICT Innovations.

Method for Protein Active Sites Detection Based on Fuzzy Decision Trees

Georgina Mirceva, Danco Davcev, Andreja Naumoski, 2011, FGIT-DTA/BSBT.

A Novel Fuzzy Decision Tree Based Method for Detecting Protein Active Sites

Georgina Mirceva, Danco Davcev, Andreja Naumoski, 2011, ICT Innovations.

A novel fuzzy based approach simple sequentially rejective multiple for inducing diatom habitat models and discovering diatom indicating properties

Georgina Mirceva, Andreja Naumoski, Kosta Mitreski, 2012, Ecol. Informatics.

Learning diatom ecological models with fuzzy order data mining algorithm

Georgina Mirceva, Kire Trivodaliev, Andreja Naumoski, 2018, 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

Fuzzy models with GIS for water quality diatom-indicator classification

Georgina Mirceva, Andreja Naumoski, Kosta Mitreski, 2011, 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD).

Examination of Different Representations of Proteins Using Protein Ray-based Descriptor and Deep Learning Models

A. Kulakov, G. Mirceva, A. Naumoski, 2023, 2023 46th MIPRO ICT and Electronics Convention (MIPRO).

Classification of Protein Structures by Making Fuzzy-Rough Feature Selection

Georgina Mirceva, Andrea Kulakov, Andreja Naumoski, 2020, 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).

Protein classification by using four approaches for extraction of the protein ray-based descriptor

Georgina Mirceva, Andrea Kulakov, A. Kulakov, 2020 .

Feature Selection for Improved Classification of Protein Structures

G. Mirceva, A. Naumoski, A. Kulakov, 2019, 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

A Novel Approach For Classifying Protein Structures Based On Fuzzy Decision Tree

Georgina Mirceva, Andrea Kulakov, Andreja Naumoski, 2018, 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).

A Complete Air Pollution Monitoring and Prediction Framework

S. Gievska, Jovan Kalajdjieski, K. Trivodaliev, 2023, IEEE Access.

Content Engineering for State-of-the-art SEO Digital Strategies by Using NLP and ML

G. Mirceva, Emilija Gjorgjevska, 2021, 2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA).

Diatom Ecological Modelling with Weighted Pattern Tree Algorithm by Using Polygonal and Gaussian Membership Functions

Georgina Mirceva, Andreja Naumoski, Kosta Mitreski, 2019, ICT Innovations.

Incorporating the depth and protrusion index in the protein ray based descriptor

Georgina Mirceva, Danco Davcev, D. Davcev, 2011, 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD).

Improvement of protein binding sites prediction by selecting amino acid residues' features.

A. Kulakov, G. Mirceva, 2015, Journal of structural biology.