| Genome-scale algorithm design: bioinformatics in the era of high-throughput sequencing V Mäkinen, D Belazzougui, F Cunial, AI Tomescu Cambridge University Press, 2023 | 192* | 2023 |
| A novel min-cost flow method for estimating transcript expression with RNA-Seq AI Tomescu, A Kuosmanen, R Rizzi, V Mäkinen BMC bioinformatics 14, 1-10, 2013 | 108 | 2013 |
| Unicyclic and bicyclic graphs having minimum degree distance AI Tomescu Discrete applied mathematics 156 (1), 125-130, 2008 | 97 | 2008 |
| Safe and complete contig assembly through omnitigs AI Tomescu, P Medvedev Journal of computational biology 24 (6), 590-602, 2017 | 62* | 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 | 60* | 2019 |
| On the complexity of string matching for graphs M Equi, R Grossi, V Mäkinen, A Tomescu International Colloquium on Automata, Languages and Programming, 55: 1--55: 15, 2019 | 60 | 2019 |
| rNA: a fast and accurate short reads numerical aligner F Vezzi, C Del Fabbro, AI Tomescu, A Policriti Bioinformatics 28 (1), 123-124, 2012 | 55 | 2012 |
| On the complexity of minimum path cover with subpath constraints for multi-assembly R Rizzi, AI Tomescu, V Mäkinen BMC bioinformatics 15, 1-11, 2014 | 44 | 2014 |
| Graphs cannot be indexed in polynomial time for sub-quadratic time string matching, unless SETH fails M Equi, V Mäkinen, AI Tomescu Theoretical Computer Science 975, 114128, 2023 | 43* | 2023 |
| Sparsifying, shrinking and splicing for minimum path cover in parameterized linear time M Cáceres, M Cairo, B Mumey, R Rizzi, AI Tomescu Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 36 | 2022 |
| Extremely fast construction and querying of compacted and colored de Bruijn graphs with GGCAT A Cracco, AI Tomescu Genome Research 33 (7), 1198-1207, 2023 | 35 | 2023 |
| Gap filling as exact path length problem L Salmela, K Sahlin, V Mäkinen, AI Tomescu Journal of Computational Biology 23 (5), 347-361, 2016 | 30 | 2016 |
| Set graphs. III. Proof Pearl: Claw-free graphs mirrored into transitive hereditarily finite sets EG Omodeo, AI Tomescu Journal of automated reasoning 52, 1-29, 2014 | 29 | 2014 |
| Linear time construction of indexable founder block graphs V Mäkinen, B Cazaux, M Equi, T Norri, AI Tomescu arXiv preprint arXiv:2005.09342, 2020 | 28 | 2020 |
| Set graphs. I. Hereditarily finite sets and extensional acyclic orientations M Milaniè, AI Tomescu Discrete Applied Mathematics 161 (4-5), 677-690, 2013 | 26 | 2013 |
| Flow decomposition with subpath constraints L Williams, AI Tomescu, B Mumey IEEE/ACM Transactions on Computational Biology and Bioinformatics 20 (1 …, 2022 | 24 | 2022 |
| Explaining a weighted DAG with few paths for solving genome-guided multi-assembly AI Tomescu, T Gagie, A Popa, R Rizzi, A Kuosmanen, V Mäkinen IEEE/ACM transactions on computational biology and bioinformatics 12 (6 …, 2015 | 24 | 2015 |
| Counting extensional acyclic digraphs A Policriti, AI Tomescu Information Processing Letters 111 (16), 787-791, 2011 | 24 | 2011 |
| On sets and graphs: Perspectives on logic and combinatorics EG Omodeo, A Policriti, AI Tomescu Springer, 2017 | 23* | 2017 |
| A safe and complete algorithm for metagenomic assembly N Obscura Acosta, V Mäkinen, AI Tomescu Algorithms for Molecular Biology 13, 1-12, 2018 | 22 | 2018 |
Veli MäkinenProfessor of Computer Science, University of HelsinkiVerified email at helsinki.fi
