| Genome-scale algorithm design V Mäkinen, D Belazzougui, F Cunial, AI Tomescu Cambridge University Press, 2015 | 110 | 2015 |
| Unicyclic and bicyclic graphs having minimum degree distance AI Tomescu Discrete applied mathematics 156 (1), 125-130, 2008 | 84 | 2008 |
| A novel min-cost flow method for estimating transcript expression with RNA-Seq AI Tomescu, A Kuosmanen, R Rizzi, V Mäkinen BMC bioinformatics 14 (5), 1-10, 2013 | 66 | 2013 |
| rNA: a fast and accurate short reads numerical aligner F Vezzi, C Del Fabbro, AI Tomescu, A Policriti Bioinformatics 28 (1), 123-124, 2012 | 50 | 2012 |
| On the complexity of minimum path cover with subpath constraints for multi-assembly R Rizzi, AI Tomescu, V Mäkinen BMC bioinformatics 15 (9), 1-11, 2014 | 29 | 2014 |
| Gap filling as exact path length problem L Salmela, K Sahlin, V Mäkinen, AI Tomescu Journal of Computational Biology 23 (5), 347-361, 2016 | 24 | 2016 |
| Set graphs. III. Proof Pearl: Claw-free graphs mirrored into transitive hereditarily finite sets EG Omodeo, AI Tomescu Journal of automated reasoning 52 (1), 1-29, 2014 | 24 | 2014 |
| Set graphs. I. Hereditarily finite sets and extensional acyclic orientations M Milanič, AI Tomescu Discrete Applied Mathematics 161 (4-5), 677-690, 2013 | 23 | 2013 |
| Counting extensional acyclic digraphs A Policriti, AI Tomescu Information processing letters 111 (16), 787-791, 2011 | 22 | 2011 |
| A rank-based sequence aligner with applications in phylogenetic analysis LP Dinu, RT Ionescu, AI Tomescu PloS one 9 (8), e104006, 2014 | 19 | 2014 |
| Indexes for jumbled pattern matching in strings, trees and graphs F Cicalese, T Gagie, E Giaquinta, ES Laber, Z Lipták, R Rizzi, AI Tomescu International Symposium on String Processing and Information Retrieval, 56-63, 2013 | 19 | 2013 |
| A randomized numerical aligner (rna) A Policriti, AI Tomescu, F Vezzi Journal of Computer and System Sciences 78 (6), 1868-1882, 2012 | 19 | 2012 |
| Safe and complete contig assembly through omnitigs AI Tomescu, P Medvedev Journal of Computational Biology 24 (6), 590-602, 2017 | 18* | 2017 |
| Sparse dynamic programming on DAGs with small width V Mäkinen, AI Tomescu, A Kuosmanen, T Paavilainen, T Gagie, R Chikhi ACM Transactions on Algorithms (TALG) 15 (2), 1-21, 2019 | 17* | 2019 |
| On the complexity of string matching for graphs M Equi, R Grossi, V Mäkinen, A Tomescu 46th International Colloquium on Automata, Languages, and Programming (ICALP …, 2019 | 17 | 2019 |
| Mapping sets and hypersets into numbers G D’Agostino, EG Omodeo, A Policriti, AI Tomescu Fundamenta Informaticae 140 (3-4), 307-328, 2015 | 16* | 2015 |
| MetaFlow: Metagenomic profiling based on whole-genome coverage analysis with min-cost flows A Sobih, AI Tomescu, V Mäkinen International Conference on Research in Computational Molecular Biology, 111-121, 2016 | 14 | 2016 |
| SNV-PPILP: refined SNV calling for tumor data using perfect phylogenies and ILP KE van Rens, V Mäkinen, AI Tomescu Bioinformatics 31 (7), 1133-1135, 2015 | 14 | 2015 |
| Simulating the bitonic sort using P systems R Ceterchi, MJ Pérez-Jiménez, AI Tomescu International Workshop on Membrane Computing, 172-192, 2007 | 14 | 2007 |
| Complexity and algorithms for finding a perfect phylogeny from mixed tumor samples A Hujdurović, U Kačar, M Milanič, B Ries, AI Tomescu IEEE/ACM transactions on computational biology and bioinformatics 15 (1), 96-108, 2016 | 13* | 2016 |
Veli MäkinenProfessor of Computer Science, University of HelsinkiVerified email at helsinki.fi
