Dr. Pavel Sulimov
Dr. Pavel Sulimov
ZHAW
School of Engineering
Forschungsschwerpunkt Intelligent Information Systems
Obere Kirchgasse 2 / Steinberggasse 12/14
8400 Winterthur
Membership of networks
Projects
Publications before appointment at the ZHAW
Sulimov P., Voronkova A. V., Kertesz-Farkas A. Annotation of tandem mass spectrometry data using stochastic neural networks in shotgun proteomics // Bioinformatics. 2020. Vol. 36. No. 12. P. 3781-3787. doi.org/10.1093/bioinformatics/btaa206
Sulimov P., Kertesz-Farkas A. Tailor: A Nonparametric and Rapid Score Calibration Method for Database Search-Based Peptide Identification in Shotgun Proteomics // Journal of Proteome Research. 2020. No. 19(4). P. 1481-1490. pubs.acs.org/doi/abs/10.1021/acs.jproteome.9b00736
Sulimov P., Sukmanova E., Chereshnev R., Kertesz-Farkas A. Guided Layer-Wise Learning for Deep Models Using Side Information, in: van der Aalst W. et al. (eds) Analysis of Images, Social Networks and Texts. AIST 2019, Communications in Computer and Information Science, vol 1086. Springer, 2020. link.springer.com/chapter/10.1007/978-3-030-39575-9_6
Sulimov P., Voronkova A., Danilova Y., Kertesz-Farkas A. Bias in False Discovery Rate Estimation in Mass-Spectrometry-Based Peptide Identification // Journal of Proteome Research. 2019. Vol. 18. No. 5. P. 2354-2358. pubs.acs.org/doi/abs/10.1021/acs.jproteome.8b00991
Makarov I., Gerasimova O., Sulimov P., Zhukov L. E. Dual network embedding for representing research interests in the link prediction problem on co-authorship networks // PeerJ Computer Science. 2019. P. 1-20. peerj.com/articles/cs-172/
Makarov I., Gerasimova O., Sulimov P., Zhukov L. E. Recommending Co-authorship via Network Embeddings and Feature Engineering: The case of National Research University Higher School of Economics, in: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries. NY : Association for Computing Machinery (ACM), 2018. P. 365-366. dl.acm.org/doi/abs/10.1145/3197026.3203911
Makarov I., Gerasimova O., Sulimov P., Ksenia Korovina, Zhukov L. E. Joint Node-Edge Network Embedding for Link Prediction, in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science / Ed. by W. van der Aalst,, V. Batagelj, G. Glavaš,, D. I. Ignatov, M. Khachay,, O. Koltsova,, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch,, A. Napoli,, A. Savchenko, A. Panchenko,, P. M. Pardalos, M. Pelillo,. Berlin : Springer, 2018. P. 1-12. link.springer.com/chapter/10.1007%2F978-3-030-11027-7_3
Makarov I., Gerasimova O., Sulimov P., Zhukov L. E. Co-authorship Network Embedding and Recommending Collaborators via Network Embedding, in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science / Ed. by W. van der Aalst,, V. Batagelj, G. Glavaš,, D. I. Ignatov, M. Khachay,, O. Koltsova,, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch,, A. Napoli,, A. Savchenko, A. Panchenko,, P. M. Pardalos, M. Pelillo,. Berlin : Springer, 2018. P. 1-6. link.springer.com/chapter/10.1007%2F978-3-030-11027-7_4