@CONFERENCE{MTMT:34577105,
	title = {Exploring the gut-brain connection: How does microbiome composition relate to cognitive behavior in Wisket model rats?},
	url = {https://m2.mtmt.hu/api/publication/34577105},
	author = {Plesz, Szonja Bianka and Adlan, Leatitia Gabriella and Büki, Alexandra and Horváth, Gyöngyi and Ligeti, Balázs and Zádori, Zoltán Sándor and Kékesi, Gabriella},
	booktitle = {7th Hungarian Neuroscience Doctoral Conference for Undergraduate Students, Graduate Students and Junior Post-Docs (HUNDOC) Booklet},
	unique-id = {34577105},
	year = {2024},
	pages = {86},
	orcid-numbers = {Büki, Alexandra/0000-0003-2078-5231; Horváth, Gyöngyi/0000-0002-6025-4577; Zádori, Zoltán Sándor/0000-0001-7312-618X; Kékesi, Gabriella/0000-0002-0185-2155}
}

@CONFERENCE{MTMT:34576951,
	title = {Is gut dysbiosis associated with the motivational deficit observed in Wisket animals?},
	url = {https://m2.mtmt.hu/api/publication/34576951},
	author = {Plesz, Szonja Bianka and Adlan, Leatitia Gabriella and Büki, Alexandra and Ligeti, Balázs and Zádori, Zoltán Sándor and Kékesi, Gabriella},
	booktitle = {International Neuroscience Conference, Pécs 2024},
	unique-id = {34576951},
	year = {2024},
	pages = {73},
	orcid-numbers = {Büki, Alexandra/0000-0003-2078-5231; Zádori, Zoltán Sándor/0000-0001-7312-618X; Kékesi, Gabriella/0000-0002-0185-2155}
}

@CONFERENCE{MTMT:34577063,
	title = {A Lactobacillaceae baktériumok előfordulása a szkizofrénia Wisket állatmodelljének mikrobiomjában},
	url = {https://m2.mtmt.hu/api/publication/34577063},
	author = {Plesz, Szonja Bianka and Adlan, Leatitia Gabriella and Büki, Alexandra and Ligeti, Balázs and Zádori, Zoltán Sándor and Horváth, Gyöngyi and Kékesi, Gabriella},
	booktitle = {A XI. Eötvözet Konferencián elhangzó előadások rövid összefoglalója},
	unique-id = {34577063},
	year = {2023},
	pages = {24-24},
	orcid-numbers = {Büki, Alexandra/0000-0003-2078-5231; Zádori, Zoltán Sándor/0000-0001-7312-618X; Horváth, Gyöngyi/0000-0002-6025-4577; Kékesi, Gabriella/0000-0002-0185-2155}
}

@article{MTMT:32905157,
	title = {State Reconstruction with Generative Models in POMDPs},
	url = {https://m2.mtmt.hu/api/publication/32905157},
	author = {Sulyok, András Attila},
	journal-iso = {PHD PROC PPKE IT},
	journal = {PHD PROCEEDINGS ANNUAL ISSUES OF THE DOCTORAL SCHOOL FACULTY OF INFORMATION TECHNOLOGY AND BIONICS},
	volume = {16},
	unique-id = {32905157},
	issn = {2064-7271},
	year = {2021},
	pages = {n.p.}
}

@article{MTMT:32460741,
	title = {DIPEND: An Open-Source Pipeline to Generate Ensembles of Disordered Segments Using Neighbor-Dependent Backbone Preferences},
	url = {https://m2.mtmt.hu/api/publication/32460741},
	author = {Harmat, Zita and Dudola, Dániel and Gáspári, Zoltán},
	doi = {10.3390/biom11101505},
	journal-iso = {BIOMOLECULES},
	journal = {BIOMOLECULES},
	volume = {11},
	unique-id = {32460741},
	issn = {2218-273X},
	abstract = {Ensemble-based structural modeling of flexible protein segments such as intrinsically disordered regions is a complex task often solved by selection of conformers from an initial pool based on their conformity to experimental data. However, the properties of the conformational pool are crucial, as the sampling of the conformational space should be sufficient and, in the optimal case, relatively uniform. In other words, the ideal sampling is both efficient and exhaustive. To achieve this, specialized tools are usually necessary, which might not be maintained in the long term, available on all platforms or flexible enough to be tweaked to individual needs. Here, we present an open-source and extendable pipeline to generate initial protein structure pools for use with selection-based tools to obtain ensemble models of flexible protein segments. Our method is implemented in Python and uses ChimeraX, Scwrl4, Gromacs and neighbor-dependent backbone distributions compiled and published previously by the Dunbrack lab. All these tools and data are publicly available and maintained. Our basic premise is that by using residue-specific, neighbor-dependent Ramachandran distributions, we can enhance the efficient exploration of the relevant region of the conformational space. We have also provided a straightforward way to bias the sampling towards specific conformations for selected residues by combining different conformational distributions. This allows the consideration of a priori known conformational preferences such as in the case of preformed structural elements. The open-source and modular nature of the pipeline allows easy adaptation for specific problems. We tested the pipeline on an intrinsically disordered segment of the protein Cd3ϵ and also a single-alpha helical (SAH) region by generating conformational pools and selecting ensembles matching experimental data using the CoNSEnsX+ server.},
	year = {2021},
	eissn = {2218-273X},
	orcid-numbers = {Harmat, Zita/0000-0002-5553-5753; Gáspári, Zoltán/0000-0002-8692-740X}
}

@inproceedings{MTMT:32015087,
	title = {A GAN-based Blind Inpainting Method for Masonry Wall Images},
	url = {https://m2.mtmt.hu/api/publication/32015087},
	author = {Ibrahim, Yahya and Nagy, Balázs and Benedek, Csaba},
	booktitle = {25th International Conference on Pattern Recognition (ICPR)},
	doi = {10.1109/ICPR48806.2021.9413009},
	unique-id = {32015087},
	year = {2021},
	pages = {3178-3185},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741}
}

@misc{MTMT:31829590,
	title = {Generation of carrier signal using analog phase-locked loops},
	url = {https://m2.mtmt.hu/api/publication/31829590},
	author = {Mórocz, Ákos},
	unique-id = {31829590},
	year = {2020}
}

@misc{MTMT:31829577,
	title = {Egy új, az APLL akvizíciós tulajdonságait alapvetően meghatározó jelenség felfedezése},
	url = {https://m2.mtmt.hu/api/publication/31829577},
	author = {Mórocz, Ákos},
	unique-id = {31829577},
	year = {2020}
}

@article{MTMT:31776006,
	title = {Thrust library based high-performance agent-based model for modeling the spread of COVID-19},
	url = {https://m2.mtmt.hu/api/publication/31776006},
	author = {Keömley-Horváth, Bence and Reguly, István Zoltán},
	journal-iso = {JEDLIK LABOR REP},
	journal = {JEDLIK LABORATORIES REPORTS},
	volume = {9},
	unique-id = {31776006},
	issn = {2064-3942},
	year = {2020},
	pages = {45},
	orcid-numbers = {Reguly, István Zoltán/0000-0002-4385-4204}
}

@article{MTMT:31676230,
	title = {Deep Learning-Based Masonry Wall Image Analysis},
	url = {https://m2.mtmt.hu/api/publication/31676230},
	author = {Ibrahim, Yahya and Nagy, Balázs and Benedek, Csaba},
	doi = {10.3390/rs12233918},
	journal-iso = {REMOTE SENS-BASEL},
	journal = {REMOTE SENSING},
	volume = {12},
	unique-id = {31676230},
	year = {2020},
	eissn = {2072-4292},
	orcid-numbers = {Benedek, Csaba/0000-0003-3203-0741}
}