Výpis publikací

SLANINÁKOVÁ, Terézia; Adrián ROŠINEC; Jakub ČILLÍK; Aleš KŘENEK; Katarína GREŠOVÁ; Jana PORUBSKÁ; Eva MARŠÁLKOVÁ; Jaroslav OĽHA; David PROCHÁZKA; Lukáš HEJTMÁNEK; Vlastislav DOHNAL; Karel BERKA; Radka SVOBODOVÁ a Matej ANTOL. AlphaFind v2: Similarity Search in AlphaFold DB and TED Domains across Structural Contexts - data. 2026. Dostupné z: https://doi.org/10.58074/mv1w-y227.

SLANINÁKOVÁ, Terézia; Jaroslav OĽHA; David PROCHÁZKA; Matej ANTOL a Vlastislav DOHNAL. On the Costs and Benefits of Learned Indexing for Dynamic High-Dimensional Data. In Carson K. Leung, Anton Dignös, Gabriele Kotsis, A. Min Tjoa, Ismail Khalil. Big Data Analytics and Knowledge Discovery 27th International Conference, DaWaK 2025, Bangkok, Thailand, August 25–27, 2025, Proceedings. 1. vyd. Cham: Springer Cham, 2026, s. 251-258. ISBN 978-3-032-02214-1. Dostupné z: https://doi.org/10.1007/978-3-032-02215-8_20.

OĽHA, Jaroslav; Jana HOZZOVÁ; Matej ANTOL a Jiří FILIPOVIČ. Estimating resource budgets to ensure autotuning efficiency. PARALLEL COMPUTING. NETHERLANDS: ELSEVIER, 2025, roč. 2025, č. 123, s. 1-15. ISSN 0167-8191. Dostupné z: https://doi.org/10.1016/j.parco.2025.103126.

SLANINÁKOVÁ, Terézia; Jaroslav OĽHA; David PROCHÁZKA; Matej ANTOL a Vlastislav DOHNAL. On the Costs and Benefits of Learned Indexing for Dynamic High-Dimensional Data: Extended Version. arXiv, 2025, 16 s. N/A. Dostupné z: https://doi.org/10.48550/arXiv.2507.05865.

SLANINÁKOVÁ, Terézia; Eva MARŠÁLKOVÁ; Katarína GREŠOVÁ; Aleš KŘENEK; Jaroslav OĽHA; Tomáš PAVLÍK; Pavlína ŠPRINGEROVÁ; David SEHNAL a Matej ANTOL. Refining Structure-Based Search in AlphaFold DB: Including confidence metrics into AlphaFind. In CZECH PHD BIOINFORMATICS CONFERENCE. 2025. Dostupné z: https://doi.org/10.5281/zenodo.15103129.

PROCHÁZKA, David; Terézia SLANINÁKOVÁ; Jozef ČERŇANSKÝ; Jaroslav OĽHA; Matej ANTOL a Vlastislav DOHNAL. Scaling Learned Metric Index to 100M Datasets. In Edgar Chávez, Benjamin Kimia, Jakub Lokoč, Marco Patella, Jan Sedmidubsky. SIMILARITY SEARCH AND APPLICATIONS, SISAP 2024. BERLIN: Springer, 2025, s. 266-273. ISBN 978-3-031-75822-5. Dostupné z: https://doi.org/10.1007/978-3-031-75823-2_22.

SLANINÁKOVÁ, Terézia; David PROCHÁZKA; Jaroslav OĽHA; Adrián ROŠINEC; Katarína GREŠOVÁ; Jakub ČILLÍK; Miriama JÁNOŠOVÁ; Jana PORUBSKÁ; Radka SVOBODOVÁ; Vlastislav DOHNAL a Matej ANTOL. AlphaFind — discover structure similarity across the proteome in AlphaFold DB. In Elixir All-Hands 2024. 2024. Dostupné z: https://doi.org/10.7490/f1000research.1119872.1.

GREŠOVÁ, Katarína; Pavlína ŠPRINGEROVÁ; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Jaroslav OĽHA; Adrián ROŠINEC; Miriama JÁNOŠOVÁ; Jakub ČILLÍK; Jana PORUBSKÁ; Radka SVOBODOVÁ; Vlastislav DOHNAL a Matej ANTOL. AlphaFind — discover structure similarity across the proteome in AlphaFold DB. In ECCB2024. 2024.

PROCHÁZKA, David; Terézia SLANINÁKOVÁ; Jaroslav OĽHA; Adrián ROŠINEC; Katarína GREŠOVÁ; Miriama JÁNOŠOVÁ; Jakub ČILLÍK; Jana PORUBSKÁ; Radka SVOBODOVÁ; Vlastislav DOHNAL a Matej ANTOL. AlphaFind: Discover structure similarity across the entire known proteome. Cold Spring Harbor, USA: bioRxiv, 2024, 6 s. N/A. Dostupné z: https://doi.org/10.1101/2024.02.15.580465.

NOVOTNÁ, Lucie; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Lukáš HEJTMÁNEK; Katarína GREŠOVÁ; Jaroslav OĽHA; Vlastislav DOHNAL; Adrián ROŠINEC a Matej ANTOL. AlphaFind: Discover structure similarity across the entire known proteome – data and model. 2024. Dostupné z: https://doi.org/10.48700/datst.d35zf-1ja47.

PROCHÁZKA, David; Terézia SLANINÁKOVÁ; Jaroslav OĽHA; Adrián ROŠINEC; Katarína GREŠOVÁ; Miriama JÁNOŠOVÁ; Jakub ČILLÍK; Jana PORUBSKÁ; Radka SVOBODOVÁ; Vlastislav DOHNAL a Matej ANTOL. AlphaFind: discover structure similarity across the proteome in AlphaFold DB. Nucleic acids research. Oxford: Oxford University Press, 2024, roč. 52, W1, s. "W182"-"W186", 5 s. ISSN 0305-1048. Dostupné z: https://doi.org/10.1093/nar/gkae397.

NOVOTNÁ, Lucie; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Lukáš HEJTMÁNEK; Adrián ROŠINEC; Jaroslav OĽHA; Katarína GREŠOVÁ; Vlastislav DOHNAL a Matej ANTOL. GraSR: Protein structural embeddings of AlphaFold DB. 2024.

NOVOTNÁ, Lucie; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Lukáš HEJTMÁNEK; Adrián ROŠINEC; Jaroslav OĽHA; Katarína GREŠOVÁ; Vlastislav DOHNAL a Matej ANTOL. LMI-10: Protein structural embeddings of AlphaFold DB. 2024.

NOVOTNÁ, Lucie; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Lukáš HEJTMÁNEK; Adrián ROŠINEC; Jaroslav OĽHA; Katarína GREŠOVÁ; Vlastislav DOHNAL a Matej ANTOL. LMI-30: Protein structural embeddings of AlphaFold DB. 2024.

NOVOTNÁ, Lucie; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Lukáš HEJTMÁNEK; Adrián ROŠINEC; Jaroslav OĽHA; Katarína GREŠOVÁ; Vlastislav DOHNAL a Matej ANTOL. 3D-af-Surfer: Protein structural embeddings of AlphaFold DB. 2024. Dostupné z: https://doi.org/10.48700/datst.tbws0-hj147.

NOVOTNÁ, Lucie; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Lukáš HEJTMÁNEK; Adrián ROŠINEC; Jaroslav OĽHA; Katarína GREŠOVÁ; Vlastislav DOHNAL a Matej ANTOL. 3DZD: Protein structural embeddings of AlphaFold DB v4. 2024. Dostupné z: https://doi.org/10.48700/datst.t45hr-bcw17.

NOVOTNÁ, Lucie; Terézia SLANINÁKOVÁ; David PROCHÁZKA; Lukáš HEJTMÁNEK; Adrián ROŠINEC; Jaroslav OĽHA; Katarína GREŠOVÁ; Vlastislav DOHNAL a Matej ANTOL. 3DZD: Protein structural embeddings of ESM Atlas. 2024.

SLANINÁKOVÁ, Terézia; Matej ANTOL; Jaroslav OĽHA; Vlastislav DOHNAL; Susana LADRA a Miguel A. MARTÍNEZ-PRIETO. Reproducible experiments with Learned Metric Index Framework. Information systems. Elsevier, 2023, roč. 118, č. 1, s. 102255-102270. ISSN 0306-4379. Dostupné z: https://doi.org/10.1016/j.is.2023.102255.

SLANINÁKOVÁ, Terézia; David PROCHÁZKA; Matej ANTOL; Jaroslav OĽHA a Vlastislav DOHNAL. SISAP 2023 Indexing Challenge – Learned Metric Index. In Pedreira, O., Estivill-Castro, V. Similarity Search and Applications. SISAP 2023. Lecture Notes in Computer Science, vol 14289. Cham: Springer, 2023, s. 282-290. ISBN 978-3-031-46993-0. Dostupné z: https://doi.org/10.1007/978-3-031-46994-7_24.

STŘELÁK, David; David MYŠKA; Filip PETROVIČ; Jan POLÁK; Jaroslav OĽHA a Jiří FILIPOVIČ. Umpalumpa: a framework for efficient execution of complex image processing workloads on heterogeneous nodes. Computing. Springer, 2023, roč. 105, č. 11, s. 2389-2417. ISSN 0010-485X. Dostupné z: https://doi.org/10.1007/s00607-023-01190-w.

OĽHA, Jaroslav; Terézia SLANINÁKOVÁ; Martin GENDIAR; Matej ANTOL a Vlastislav DOHNAL. Learned Indexing in Proteins: Extended Work on Substituting Complex Distance Calculations with Embedding and Clustering Techniques. arXiv, 2022. Dostupné z: https://doi.org/10.48550/ARXIV.2208.08910.

OĽHA, Jaroslav; Terézia SLANINÁKOVÁ; Martin GENDIAR; Matej ANTOL a Vlastislav DOHNAL. Learned Indexing in Proteins: Substituting Complex Distance Calculations with Embedding and Clustering Techniques. In Tomáš Skopal, Fabrizio Falchi, Jakub Lokoč, Maria Luisa Sapino, Ilaria Bartolini, Marco Patella. Similarity Search and Applications, 15th International Conference, SISAP 2022, Bologna, Italy, October 5–7, 2022, Proceedings. 1. vyd. Cham: Springer Cham, 2022, s. 274-282. ISBN 978-3-031-17848-1. Dostupné z: https://doi.org/10.1007/978-3-031-17849-8_22.

TRAPL, Dalibor; MArtin KRUPIČKA; Vladimír VIŠŇOVSKÝ; Jana HOZZOVÁ; Jaroslav OĽHA; Aleš KŘENEK a Vojtěch SPIWOK. Property Map Collective Variable as a Useful Tool for a Force Field Correction. Journal of Chemical Information and Modeling. American Chemical Society, 2022, roč. 62, č. 3, s. 567-576. ISSN 1549-9596. Dostupné z: https://doi.org/10.1021/acs.jcim.1c00651.

FILIPOVIČ, Jiří; Jana HOZZOVÁ; Amin NEZARAT; Jaroslav OĽHA a Filip PETROVIČ. Using hardware performance counters to speed up autotuning convergence on GPUs. Journal of Parallel and Distributed Computing. Elsevier, 2022, roč. 160, February, s. 16-35. ISSN 0743-7315. Dostupné z: https://doi.org/10.1016/j.jpdc.2021.10.003.

VIŠŇOVSKÝ, Vladimír; Viktória SPIŠAKOVÁ; Jana HOZZOVÁ; Jaroslav OĽHA; Dalibor TRAPL; Vojtěch SPIWOK; Lukáš HEJTMÁNEK a Aleš KŘENEK. Complex simulation workflows in containerized high-performance environment. In Armenia S., Geril P. Proc. ESM 2021. Brusel: EUROSIS, 2021, s. 42-45. ISBN 978-94-92859-18-1.

SLANINÁKOVÁ, Terézia; Matej ANTOL; Jaroslav OĽHA a Vlastislav DOHNAL. Data-driven Learned Metric Index: an Unsupervised Approach. In 14th International Conference on Similarity Search and Applications (SISAP 2021). Cham: Springer, 2021, s. 81-94. ISBN 978-3-030-89656-0. Dostupné z: https://doi.org/10.1007/978-3-030-89657-7_7.

ANTOL, Matej; Jaroslav OĽHA; Terézia SLANINÁKOVÁ a Vlastislav DOHNAL. Learned metric index - proposition of learned indexing for unstructured data. Information Systems. Elsevier, 2021, roč. 100, č. 101774, s. 1-12. ISSN 0306-4379. Dostupné z: https://doi.org/10.1016/j.is.2021.101774.

HOZZOVÁ, Jana; Jiří FILIPOVIČ; Amin NEZARAT; Jaroslav OĽHA a Filip PETROVIČ. Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures. Data in Brief. Elsevier, 2021, roč. 39, December, s. 1-12. ISSN 2352-3409. Dostupné z: https://doi.org/10.1016/j.dib.2021.107631.

PETROVIČ, Filip; David STŘELÁK; Jana HOZZOVÁ; Jaroslav OĽHA; Richard TREMBECKÝ; Siegfried BENKNER a Jiří FILIPOVIČ. A benchmark set of highly-efficient CUDA and OpenCL kernels and its dynamic autotuning with Kernel Tuning Toolkit. Future Generation Computer Systems. Elsevier, 2020, roč. 108, July, s. 161-177. ISSN 0167-739X. Dostupné z: https://doi.org/10.1016/j.future.2020.02.069.

OĽHA, Jaroslav; Jana HOZZOVÁ; Jan FOUSEK a Jiří FILIPOVIČ. Exploiting historical data: Pruning autotuning spaces and estimating the number of tuning steps. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE. HOBOKEN: WILEY, 2020, roč. 32, č. 21, s. 1-15. ISSN 1532-0626. Dostupné z: https://doi.org/10.1002/cpe.5962.

KŘENEK, Aleš; Jana HOZZOVÁ; Jaroslav OĽHA; Dalibor TRAPL a Vojtěch SPIWOK. Exploring Protein Folding Space with Neural Network Guided Simulations. In Alexandre Nketsa. MODELLING AND SIMULATION 2020. Brusel: EUROSIS-ETI, 2020, s. 305-309. ISBN 978-94-92859-12-9.

OĽHA, Jaroslav; Jana HOZZOVÁ; Jan FOUSEK a Jiří FILIPOVIČ. Exploiting historical data: pruning autotuning spaces and estimating the number of tuning steps. In Ulrich Schwardmann, Christian Boehme, Dora B. Heras, Valeria Cardellini, Emmanuel Jeannot, Antonio Salis, Claudio Schifanella, Ravi Reddy Manumachu, Dieter Schwamborn, Laura Ricci, Oh Sangyoon, Thomas Gruber, Laura Antonelli, Stephen L. Scott. Lecture Notes in Computer Science. Cham, Switzerland: Springer, Cham, 2019, s. 295-307. ISBN 978-3-030-48339-5. Dostupné z: https://doi.org/10.1007/978-3-030-48340-1_23.

PAZÚRIKOVÁ, Jana; Jaroslav OĽHA; Aleš KŘENEK a Vojtěch SPIWOK. Acceleration of Mean Square Distance Calculations with Floating Close Structure in Metadynamics Simulations. arXiv, 2018, 22 s. arXiv:1801.02362.