Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Marcin Możejko"'
Autor:
Paulina Szymczak, Marcin Możejko, Tomasz Grzegorzek, Radosław Jurczak, Marta Bauer, Damian Neubauer, Karol Sikora, Michał Michalski, Jacek Sroka, Piotr Setny, Wojciech Kamysz, Ewa Szczurek
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-23 (2023)
Abstract Antimicrobial peptides emerge as compounds that can alleviate the global health hazard of antimicrobial resistance, prompting a need for novel computational approaches to peptide generation. Here, we propose HydrAMP, a conditional variationa
Externí odkaz:
https://doaj.org/article/5c436eeedaa54f1aaf4e657e6e0f9a55
Autor:
Paulina Szymczak, Marcin Możejko, Tomasz Grzegorzek, Radosław Jurczak, Marta Bauer, Damian Neubauer, Karol Sikora, Michał Michalski, Jacek Sroka, Piotr Setny, Wojciech Kamysz, Ewa Szczurek
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-1 (2023)
Externí odkaz:
https://doaj.org/article/faf5b7ebf8a8454baf15c95845495ccb
Publikováno v:
Studies in Computational Intelligence ISBN: 9783031266508
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c098471fae5bfb1aa9efcd7740a8589
https://doi.org/10.1007/978-3-031-26651-5_9
https://doi.org/10.1007/978-3-031-26651-5_9
Autor:
Paulina Szymczak, Marcin Możejko, Tomasz Grzegorzek, Radosław Jurczak, Marta Bauer, Damian Neubauer, Karol Sikora, Michał Michalski, Jacek Sroka, Piotr Setny, Wojciech Kamysz, Ewa Szczurek
Antimicrobial peptides emerge as compounds that can alleviate the global health hazard of antimicrobial resistance, prompting a need for novel computational approaches to peptide generation. Here, we propose HydrAMP, a conditional variational autoenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55773418c6f45988b3f731415227b717
https://doi.org/10.1101/2022.01.27.478054
https://doi.org/10.1101/2022.01.27.478054
Publikováno v:
Schedae Informaticae. 27:19-30
We investigate performance of a gradient descent optimization (GR) applied to the traffic signal setting problem and compare it to genetic algorithms. We used neural networks as metamodels evaluating quality of signal settings and discovered that bot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6ce785cfdf91ffd5be5be238e86f614
https://doi.org/10.4467/20838476si.18.002.10407
https://doi.org/10.4467/20838476si.18.002.10407
Publikováno v:
Scientific Reports
Scientific Reports, Vol 9, Iss 1, Pp 1-12 (2019)
Scientific Reports, Vol 9, Iss 1, Pp 1-12 (2019)
Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59dbbcb41c7dff4cb7e374ffe30a20c8
https://pubmed.ncbi.nlm.nih.gov/31586139
https://pubmed.ncbi.nlm.nih.gov/31586139
Autor:
Paweł Gora, Przemyslaw Przybyszewski, Arkadiusz Klemenko, Hubert Dryja, Marcin Możejko, Dawid Kopczyk, Magdalena Kukawska, Adrian Kochanski, Maciej Brzeski, Katarzyna Karnas
Publikováno v:
MT-ITS
We present a method for optimizing traffic signal settings which can be used for offline planning and realtime adaptive traffic management. The method is based on metaheuristics efficiently exploring space of possible settings and evaluating candidat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60b79be0775ea9f3be3eb6bef90b2d65
https://ruj.uj.edu.pl/xmlui/handle/item/148615
https://ruj.uj.edu.pl/xmlui/handle/item/148615