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Vedrana Vidulin Data scientist and bioinformatician

Publications


Publications in Scientific Journals

Zhou N., ÔÇŽ, Vidulin V., ÔÇŽ, Friedberg I. (2019) The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens. Genome Biology, 20, 244.
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Madjarov G. and Vidulin V., Dimitrovski I., Kocev D. (2019) Web genre classification with methods for structured output prediction. Information Sciences, 503, 551-573.
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Vidulin V., ┼ámuc T., D┼żeroski S., Supek F. (2018) The evolutionary signal in metagenome phyletic profiles predicts many gene functions. Microbiome, 6, 129.
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Vidulin V., Šmuc T., Supek F. (2016) Extensive complementarity between gene function prediction methods. Bioinformatics, 32(23), 3645-3653.
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Brbi─ç M., Pi┼íkorec M., Vidulin V., Kri┼íko A., ┼ámuc T., Supek F. (2016) The landscape of microbial phenotypic traits and associated genes. Nucleic Acids Research, 44(21), 10074ÔÇô10090.
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Vidulin V., Bohanec M., Gams M. (2014) Combining human analysis and machine data mining to obtain credible data relations. Information Sciences, 288, 254-278.
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Vidulin V. (2013) Searching for credible relations in machine learning. Informatica: An International Journal of Computing and Informatics, 37(3), 355-356.
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Vidulin V., Gams M. (2011) Impact of high-level knowledge on economic welfare through interactive data mining. Applied Artificial Intelligence, 25(4), 267-291.
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Vidulin V., Luštrek M., Gams M. (2009) Multi-label approaches to web genre identification. Journal for Language Technology and Computational Linguistics, 24(1), 93-110.
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Vidulin V., Luštrek M., Gams M. (2007) Training a genre classifier for automatic classification of web pages. CIT: Journal of Computing and Information Technology, 15(4), 305-311.
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Vidulin V., Gams M. (2006) Analyzing the impact of investment in education and R&D on economic welfare with data mining. Electrotechnical Review: Journal of Electrical Engineering and Computer Science, 73(5), 285-290.
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Publications in Conference Proceedings

Vidulin V., D┼żeroski S. (2020) Hierarchy decomposition pipeline: a toolbox for comparison of model induction algorithms on hierarchical multi-label classification problems. In Discovery Science (pp. 486-501). DS 2020. Lecture Notes in Computer Science, vol 12323. Springer, Cham.
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Levati─ç J., Brbi─ç M., Stepi┼ínik T., Kocev D., Vidulin V., ┼ámuc T., Supek F., D┼żeroski S. (2018) Phenotype prediction with semi-supervised classification trees. In New Frontiers in Mining Complex Patterns (pp. 138ÔÇô150). NFMCP 2017. Lecture Notes in Computer Science, vol 10785. Springer, Cham.
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Brbi─ç M., Pi┼íkorec M., Vidulin V., Kri┼íko A., ┼ámuc T., Supek F. (2017) Phenotype inference from text and genomic data. In Machine Learning and Knowledge Discovery in Databases (pp. 373ÔÇô377). ECML PKDD 2017. Lecture Notes in Computer Science, vol 10536. Springer, Cham.
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Vidulin V. and Brbić M., Supek F., Šmuc T. (2016) Evaluation of fusion approaches in large-scale bio-annotation setting. In 4th Workshop on Machine Learning in Life Science (pp. 37-51). ECML PKDD 2016.
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Madjarov G. and Vidulin V., Dimitrovski I., Kocev D. (2015) Web genre classification via hierarchical multi-label classification. In Intelligent Data Engineering and Automated Learning (pp. 9-17). IDEAL 2015. Lecture Notes in Computer Science, vol 9375. Springer, Cham.
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Vidulin V., Šmuc T., Supek F. (2014) Speed and accuracy benchmarks of large-scale microbial gene function prediction with supervised machine learning. In Discovery Science: Book of Abstracts. DS 2014.
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Kova─Ź S., Vidulin V. (2013) Android design principles and their use in application e-doorman. In 16th International Multiconference Information Society (pp. 63-66). IS 2013.

Pušnik M., Piltaver R., Vidulin V., Gams M. (2013) Inteligentni sistem e-vratar. In 16th International Multiconference Information Society (pp. 94-97). IS 2013.

Vidulin V., Piltaver R., Gams M. (2013) Pregled inteligentnih algoritmov za procesiranje senzorskih podatkov. In 16th International Multiconference Information Society (pp. 126-129). IS 2013.

Vidulin V., Gams M. (2012) Slovenske demografske projekcije in analize. In 15th International Multiconference Information Society (pp. 14-18). IS 2012.

Vidulin V., Gams M. (2012) Varnostna verzija inteligentnega vratarja. In 15th International Multiconference Information Society (pp. 159-162). IS 2012.

Vidulin V., Gams M. (2010) Searching for meaningful models in macroeconomic domain. In 13th International Multiconference Information Society (pp. 94-97). IS 2010.

Vidulin V. (2009) Problem transformation methods for multi-genre web pages classification. In 12th International Multiconference Information Society (pp. 136-139). IS 2009.

Vidulin V., Gams M. (2009) Multi-label classification of web genres. In 18th International Electrotechnical and Computer Science Conference (pp. 179-182). ERK 2009.

Rehm G., Santini M., Mehler A., Branislavski P., Gleim R., Stubbe A., Symonenko S., Tavosanis M., Vidulin V. (2008) Towards a reference corpus of web genres for the evaluation of genre identification systems. In 6th International Conference on Language Resources and Evaluation. LREC 2008.
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Vidulin V., Gams M. (2008) Impacts of education and R&D on economy: analysis by data mining techniques. In International Conference on Advances in the Internet, Processing, Systems, and Interdisciplinary Research. VIPSI 2008.

Vidulin V., Gams M. (2008) Is science important for economic welfare? In 11th International Multiconference Information Society (pp. 41-44). IS 2008.

Vidulin V., Luštrek M., Gams M. (2007) Using genres to improve search engines. In Towards Genre-Enabled Search Engines: The Impact of Natural Language Processing (pp. 45-51). RANLP 2007.
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Vidulin V., Luštrek M., Gams M. (2007) Training the genre classifier for automatic classification of web pages. In 29th International Conference on Information Technology Interfaces (pp. 93-98). ITI 2007.

Vidulin V., Luštrek M., Gams M. (2007) Evaluation of different approaches to training a genre classifier. In International Conference on Artificial Intelligence and Pattern Recognition (pp. 515-520). AIPR 2007.

Vidulin V., Gams M. (2007) The impact of high level knowledge on economic welfare. In 10th International Multiconference Information Society (pp. 107-110). IS 2007.

Vidulin V., Luštrek M., Gams M. (2006) Comparison of the performance of genre classifiers trained by different machine learning algorithms. In 9th International Multiconference Information Society (pp. 140-143). IS 2006.

Vidulin V., Gams M. (2006) Impact of investment in education and R&D on economic growth. In 15th International Electrotechnical and Computer Science Conference (pp. 129-132). ERK 2006.

Vidulin V., Filipi─Ź, B. (2006) Visualization of a simple genetic algorithm for pedagogical purposes. In 15th International Electrotechnical and Computer Science Conference (pp. 99-102). ERK 2006.
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Selected Talks and Posters

Vidulin V., D┼żeroski S. (October, 28th 2019) Gene function prediction using Gene Ontology decomposition. Talk and poster at Discovery Science. Split, Croatia.
poster | abstract

Vidulin V., ┼ámuc T., D┼żeroski S., Supek F. (July, 22nd 2019) The evolutionary signal in metagenome phyletic profiles predicts many gene functions. Talk and poster at ISMB/ECCB. Basel, Switzerland.
talk | abstract | poster | slides

Vidulin V., ┼ámuc T., D┼żeroski S., Supek F. (June, 19th 2017) Automated gene function prediction using metagenome data. Poster at Workshop in Advanced Computational Metagenomics. Bari, Italy.

Madjarov G. and Vidulin V., Dimitrovski I., Kocev D. (October, 16th 2015) Web genre classification via hierarchical multi-label classification. Talk at IDEAL. Wroclaw, Poland.
presentation

Vidulin V., Šmuc T., Supek F. (July, 12th 2015) Predicting microbial gene function on a massive scale reveals extensive complementarity between genome context methods. Poster at ISMB/ECCB. Dublin, Ireland.
poster | abstract | link

Vidulin V., Šmuc T., Supek F. (October, 8th 2014) Speed and accuracy benchmarks of large-scale microbial gene function prediction with supervised machine learning. Poster at Discovery Science. Bled, Slovenia.
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Theses

Vidulin V. (2012) Searching for credible relations in machine learning, PhD Thesis, Jo┼żef Stefan International Postgraduate School, Ljubljana, Slovenia.
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Other Publications

Vidulin V. (2006) Constructivist learning theory as a link between artificial neural networks and intelligent tutoring systems. Organizacija: revija za management, informatiko in kadre, 39(2), 154-156.

Gams M., Vidulin V. (30.8.2006) Vpliv znanja na gospodarsko uspešnost. Finance, št. 166, 18.

Google Scholar

The number of times my papers have been cited can be seen at Google Scholar.

ResearchGate

Selected publications and accompanying materials are available at ResearchGate.

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