A5064609702- Data Mining Algorithms and Applications
- Machine Learning and Data Classification
- Text and Document Classification Technologies
- Rough Sets and Fuzzy Logic
- Semantic Web and Ontologies
- Neural Networks and Applications
- Data Stream Mining Techniques
- Machine Learning in Bioinformatics
- Gene expression and cancer classification
- Logic, Reasoning, and Knowledge
- Bioinformatics and Genomic Networks
- Image Retrieval and Classification Techniques
- AI-based Problem Solving and Planning
- Biomedical Text Mining and Ontologies
- Face and Expression Recognition
- Imbalanced Data Classification Techniques
- Hydrological Forecasting Using AI
- Advanced Database Systems and Queries
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Machine Learning and Algorithms
- Time Series Analysis and Forecasting
- Data Management and Algorithms
- Natural Language Processing Techniques
- Gene Regulatory Network Analysis
Jožef Stefan Institute
2016-2025
Jožef Stefan International Postgraduate School
2015-2024
European Space Research Institute
2020-2024
University of Ljubljana
2018-2023
Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins
2012-2020
John Snow (United States)
2003
Hong Kong Association of Registered Tour Co-ordinators
2001
Deutsche Nationalbibliothek
2001
FORTH Institute of Electronic Structure and Laser
1997
FORTH Institute of Computer Science
1997
Automated annotation of protein function is challenging. As the number sequenced genomes rapidly grows, overwhelming majority products can only be annotated computationally. If computational predictions are to relied upon, it crucial that accuracy these methods high. Here we report results from first large-scale community-based critical assessment (CAFA) experiment. Fifty-four representing state art for prediction were evaluated on a target set 866 proteins 11 organisms. Two findings stand...
Abstract Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation protein function. Results Here, we report on results third CAFA challenge, CAFA3, that featured expanded analysis over previous rounds, both in terms volume data analyzed types performed. In a novel major new development, predictions assessment goals drove some experimental assays, resulting functional annotations for...
Multi-label classification (MLC) has recently attracted increasing interest in the machine learning community. Several studies provide surveys of methods and datasets for MLC, a few empirical comparisons MLC methods. However, they are limited number considered. This paper provides comprehensive investigation wide range on wealth from different domains. More specifically, our study evaluates 26 42 benchmark using 20 evaluation measures. The methodology used meets highest literature standards...
Data mining algorithms look for patterns in data. While most existing data approaches a single table, multi-relational (MRDM) that involve multiple tables (relations) from relational database. In recent years, the common types of and considered have been extended to case MRDM now encompasses (MR) association rule discovery, MR decision trees distance-based methods, among others. successfully applied number problems variety areas, notably area bioinformatics. This article provides brief...
S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions ORFs these automatically. Different machine learning have been proposed this end, but it remains unclear which method be preferred terms predictive performance, efficiency usability. We study use decision tree based models for predicting multiple ORFs. First, we...
Earth observation (EO) is a prime instrument for monitoring land and ocean processes, studying the dynamics at work, taking pulse of our planet. This article gives bird's eye view essential scientific tools approaches informing supporting transition from raw EO data to usable EO-based information. The promises, as well current challenges these developments, are highlighted under dedicated sections. Specifically, we cover impact (i) Computer vision; (ii) Machine learning; (iii) Advanced...
We address the problem of estimating time-to-employment a jobseeker using survival analysis and oblique predictive clustering tree. Unlike standard analysis, tree can handle categorical continuous data is capable modelling non-linear dependences. Treating censored as missing opens possibility to perform by structured output prediction in semi-supervised multi-target regression setting. The effectiveness this approach shown on real dataset from Public Employment Services Slovenia, comprising...