Attila Kertész-Farkas’ CV
Curriculum Vitae
Kertész-Farkas, Attila, Ph.D.
Post-Doctoral fellow
Protein Structure and Bioinformatics Group,
International Centre of Genetic Engineering and Biotechnology,
Trieste, Italy,
Personal Data
Born: November 26, 1979 in Kiskunmajsa (Hungary)
Hungarian nationality, Male, Single,
Address:
ICGEB, Padriciano 99, Trieste, Italy, 34149
e-mail:
kfattila@icgeb.org
phone:
+39 346 0396947
Former Affiliations (postdocs)
2008-2009
Division of Imaging and Applied Mathematics, Center for Devices and Radiological
Health, U.S. Food and Drug Administration, USA, Maryland, USA.
2008-2009
Department of Biology, University of Maryland Baltimore County (UMBC)
Education
2004-2008
PhD studies at the University of Szeged, Szeged (Hungary).
1999-2004
University of Szeged, MSc in Computer Science and Mathematics (specialising in
Fundamentals of Computer Science) with Summa cum laude. Title of thesis work:
Compact representation of finite languages with nondeterministic automata (in
Hungarian)
1994-1998
High school, Kiskunhalas (Hungary), special informatics class.
Scholarship
2006-2007
Erasmus, one winter semester, Technische Universitaet Dresden, Germany
Awards
2004. Apr.
1st prize at a Scientific Conference of Students for the article entitled Kernel-based
learning with feature weighting. (In Hungarian, TDK)
2002. Nov.
1st prize at a Scientific Conference of Students for the article entitled Compact
representation of finite languages with nondeterministic automata. (In Hungarian,
TDK)
Attila Kertész-Farkas’ CV
Experience and research topics
Research activity:
2009-
I am working on two projects. The first project relates to tandem mass spectrometry. I am
developping a de novo algorithm for identification of post-trasnlationally modifications in
peptide mass spectra. The second project is the analysis of the integration of biological and
medical databases.
2008 -2009 During my Postdoctoral fellowship in USA I had been involved mutation extraction from
scientific literature using natural Language processing techniques and I also had been working
on classification of disease mutations using machine learning techniques.
2004-2008
During my PhD studies at the Research Group on Artificial Intelligence my primary research
areas were statistical machine learning and bioinformatics including structural and functional
protein classification; protein ranking; design of similarity function for protein sequences,
learning of similarity and spectral decomposition of similarity; kernel functions for strings
and discrete structures; operations research; DNA micro-array processing; constructing
protein databases and benchmark collections for classification. The developed methods were
evaluated mostly with Matlab but several other technologies were used such as JAVA, C and
MySQL under Linux and Windows systems. I collaborated with several research groups from
Europe and the results were presented via perhaps the best regarded publication channels. For
details see my publication list and affiliations.
2000-2004
During my undergraduate studies at the Research Group on Artificial Intelligence my tasks
were developing and implementing in various environment the following linguistics software
projects to aid the speech recognition system for the Hungarian language.
 A neural network editor to carry out artificial neural network structures
 A context-free grammar editor to design a language model for speech recognition
 A phonetic transcriptor for the Hungarian language
 A nondeterministic automata reduction algorithm to reduce the size of the language model
 Morphological parser for the Hungarian language
Talks:

Protein databases and similarity measures for protein classification, Bioinformatics seminar at
Renyi Mathematical Institute, Budapest on 3.10.2007. (Hungary)

Equivalence Learning in Protein Classification, Young Researcher Symposium on Intelligent
Systems at the John von Neumann Computer Society in Budapest on 23.11.2007. (Hungary)
Participation in projects:

2001-2002 Code SZT-IS-10
Open Source Segmentation and Annotation Software for Hungarian Speech Databases

2000-2002 Code IKTA-3/049/2000
Establishing a Hungarian Telephone Speech Database
Attila Kertész-Farkas’ CV
Teaching experiences:

Operational Research (tutorial)

Introduction to Pascal and C programming (tutorial)

Introduction to Java programming (tutorial)

Algorithms and data structures (tutorial)
Technical Program Committee:

International Conference on BioComputation, Bioinformatics, and Biomedical Technologies
BIOTECHNO 2008
Memberships:

The John von Neumann Computer Society

Eötvös Collegium
Computer skills:

Matlab (using toolboxes such as Bioinformatics, Mosek, LSSVMLab, NeuralNet, Spider,
Statistics, Optimization toolbox)

Weka, C/C++, Visual C++ with MFC

Java, J2ME, JBuilder and JBuilder Mobil Set, Nokia MobileToolset (MIDP, CLDC)

Pascal, Prolog, OpenGL, Python, Internet programming, Perl

Relational databases, SQL, ODBC, JDBC

Windows, Linux, MS Office, Latex
Languages:

Hungarian: native

English: fluent

German: basic level
January 24, 2011
Attila Kertesz-Farkas
Attila Kertész-Farkas’ CV
Publications
Number of independent references is 40 (at least).
Book chapter
1. Attila Kertész-Farkas1, András Kocsor3 and Sándor Pongor4,5, The application of Data
Compression-based Distance to Biological Sequences, In: Frank Emmert-Streib. (Ed.) Information
Theory and Statistical Learning, (2008), p. 73-88
Refereed journal papers
2. E. Doughty11, A. Kertesz-Farkas10,11, O. Bodenreider12, G. Thompson11, A. Adadey11, T. Peterson11,
and M. G. Kann11 Toward an automatic method for extracting cancer- and other disease-related
point mutations from the biomedical literature, Bioinformatics (2010), in press
Shared first authorship.
3. Dhir S.4, Pacurar M.4, Franklin D.4, Gáspári Z.7, Kertész-Farkas A.4, Kocsor, A.3, Eisenhaber F.,
Pongor S.4,5(2010) Detecting atypical examples of known domain types by sequence similarity
searching: The SBASE domain library approach, Current Protein Peptide Science, 2010, in press
4. József Dombi8 and Attila Kertész-Farkas1, Applying Fuzzy Technologies to Equivalence Learning
in Protein Classification, Journal of Computational Biology, 16(4), 2009, p. 611-623
5. Róbert Busa-Fekete1, Attila Kertész-Farkas1, András Kocsor3 and Sándor Pongor4,5, Balanced ROC
analysis (BAROC) protocol for the evaluation of protein similarities, Journal of Biochemical and
Biophysical Methods, 70(6), 2008, p. 1210-1214
6. Attila Kertész-Farkas1,2, András Kocsor1,3 and Sándor Pongor4,5, Equivalence Learning in Protein
Classification, In: P. Perner (Ed.) Machine Learning and Data Mining in Pattern Recognition, LNAI
(4571), Springer Verlag, Heidelberg, 2007, p. 824-837
7. Attila Kertész-Farkas1, Somdutta Dhir4, Paolo Sonego4, Mircea Pacurar4, Sergiu Netoteia5, Harm
Nijveen6, Arnold Kuzniar6, Jack A.M. Leunissen6, András Kocsor1 and Sándor Pongor4,5
Benchmarking protein classification algorithms via supervised cross-validation, Journal of
Biochemical and Biophysical Methods, 70(6), 2008, pp. 1215-1223
8. Paolo Sonego4, Mircea Pacurar4, Somdutta Dhir4, Attila Kertész-Farkas1, András Kocsor1, Zoltán
Gáspári7, Jack A.M. Leunissen6 and Sándor Pongor4,5, A Protein Classification Benchmark
collection for Machine Learning, Nucleic Acids Research (35), 2006, D232-6
9. János Z. Kelemen8, Attila Kertész-Farkas1, András Kocsor1 and László G. Puskás8, Kalman
Filtering for Disease-State Estimation from Microarray Data, Bioinformatics (22), 2006, pp 30473053
10. László Kaján4, Attila Kertész-Farkas1, Dino Franklin4, Nelly Ivanova4, András Kocsor1 and Sándor
Pongor4,5, Application of a simple log likelihood ratio approximant to protein sequence
classification, Bioinformatics (22), 2006, pp 2865-2869
Attila Kertész-Farkas’ CV
11. András Kocsor1, Attila Kertész-Farkas1, László Kaján4 and Sándor Pongor4,5, Application of
compression-based distance measures to protein sequence-classification: a methodological study,
Bioinformatics (22), 2006, pp 407-412
Other journal papers
12. Attila Kertész-Farkas1 and András Kocsor1, Kernel-based Classification of Tissues using Feature
Weightings, Applied Ecology and Environmental Research 4(2), 2006, pp. 63-71
13. Attila Kertész-Farkas1, Zoltán Fülöp9 and András Kocsor1, Compact Representation of Hungarian
Corpora (in Hungarian), Hungarian Journal of Applied Linguistics (1-2), 2005, pp. 63-70
Conferences
14. Attila Kertész-Farkas1,2, András Kocsor1,3 and Sándor Pongor4,5, Equivalence Learning in Protein
Classification, International Conference on Machine Learning and Data Mining in Pattern Recognition
MLDM 2007, 18-20 July 2007, Leipzig (Germany)
15. Attila Kertész-Farkas1 and András Kocsor1, Classification of Tissues using Feature Weightings (in
Hungarian), VII. Hungarian Conference on Biometrics and Biomathematics, 5th-6th July 2005,
Budapest (Hungary).
16. Attila Kertész-Farkas1, Zoltán Fülöp9 and András Kocsor1, Compact Representation of Hungarian
Vocabulary with Nondeterministic Finite Automata I. Conference on Hungarian Computational
Linguistic (in Hungarian, I. Magyar Számítógépes Nyelvészet Konferencia) 10th-11th December 2003,
Szeged pp. 231-237, (Hungary)
17. Attila Kertész-Farkas, Kernel-based learning with dimension weighting (in Hungarian), Scientific
Conference of Students, spring 2004, Supervisor: András Kocsor1
18. Attila Kertész-Farkas, Compact representation of finite languages with nondeterministic
automata (in Hungarian), Scientific Conference of Students, autumn 2002, Supervisors: Zoltán Fülöp9
and András Kocsor1
Poster
19. Attila Kertesz-Farkas10,11, Olivier Bodenreider12, Trevor C. Suznick11, Gary Thompson11, Yanan
Sun11 and Maricel G. Kann11, EMU: A tool for the Extraction of MUtations with disease
associations from literature Growth Factor and Signal Transduction Conferences: System Biology,
Integrative, Comaparitve and Multi-scale Modeling, 11–14 June, Iowa, USA
Attila Kertész-Farkas’ CV
Co-author’s Affiliations:
1
Research Group on Artificial Intelligence, Szeged (Hungary),
2
Erasmus Program, Technische Univeritaet Dresden (Germany),
3Applied
Intelligence Laboratory, Szeged, (Hungary),
4
Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Trieste (Italy)
5
Bioinformatics Group, Biological Research Centre, Szeged, (Hungary)
6
Laboratory of Bioinformatics, Wageningen University and Research Centre, Wageningen, (The
Netherlands)
7Institute
8
of Chemistry, Eötvös Loránd University, Budapest (Hungary)
Laboratory of Functional Genomics at Biological Research Centre, Szeged (Hungary)
9
Department of Foundations of Computer Science, University of Szeged, Szeged (Hungary)
10Division
of Imaging and Applied Mathematics, Centre for Devices and Radiological Health, U.S. Food
and Drug Administration, Silver Spring, MD, 20993, USA
11University
12National
of Maryland, Baltimore County, Baltimore, MD 21250, USA,
Library of Medicine, Bethesda, MD 20894, USA
January 24, 2011
Attila Kertész-Farkas