Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Alicja Płuciennik"'
Autor:
Alicja Płuciennik, Aleksander Płaczek, Agata Wilk, Sebastian Student, Małgorzata Oczko-Wojciechowska, Krzysztof Fujarewicz
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 19, p 11880 (2022)
The data from independent gene expression sources may be integrated for the purpose of molecular diagnostics of cancer. So far, multiple approaches were described. Here, we investigated the impacts of different data fusion strategies on classificatio
Externí odkaz:
https://doaj.org/article/ba91eaa919f242c1b80f29a67b2d32dc
Autor:
Alicja Płuciennik, Michał Stolarczyk, Maria Bzówka, Agata Raczyńska, Tomasz Magdziarz, Artur Góra
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-8 (2018)
Abstract Background Here, we present an R package for entropy/variability analysis that facilitates prompt and convenient data extraction, manipulation and visualization of protein features from multiple sequence alignments. BALCONY can work with res
Externí odkaz:
https://doaj.org/article/33e5741c08d2433d829c8f4ac44da301
Autor:
Krzysztof Fujarewicz, Sebastian Student, Wojciech Bensz, Alicja Płuciennik, Krzysztof Łakomiec, Agata Wilk
Publikováno v:
Computational Science and Its Applications – ICCSA 2019 ISBN: 9783030243074
ICCSA (5)
ICCSA (5)
Despite the increasing amount of available gene expression data, integrative analysis is still hindered by its high susceptibility to microenvironment fluctuations, resulting in inter-experiment variability known as batch effects. Therefore the devel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7183f9028c88665e7675999b2a91ab4
https://doi.org/10.1007/978-3-030-24308-1_48
https://doi.org/10.1007/978-3-030-24308-1_48
Autor:
Alicja Płuciennik, Krzysztof Fujarewicz, Wojciech Bensz, Sebastian Student, Krzysztof Łakomiec
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030237615
ITIB
ITIB
Currently, development in high-throughput technologies generate large amount of molecular biology data at awesome rate. How to merge the mass amount of data coming from different sources to obtain significant and complementary high-level knowledge is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f9e4259c231ce9d1781f88bfa3789ca
https://doi.org/10.1007/978-3-030-23762-2_52
https://doi.org/10.1007/978-3-030-23762-2_52
Autor:
Maria Bzówka, Artur Góra, Michał Stolarczyk, Alicja Płuciennik, Tomasz Magdziarz, Agata Raczyńska
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-8 (2018)
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-8 (2018)
Background Here, we present an R package for entropy/variability analysis that facilitates prompt and convenient data extraction, manipulation and visualization of protein features from multiple sequence alignments. BALCONY can work with residues dis
Publikováno v:
Artificial Intelligence: Methodology, Systems, and Applications ISBN: 9783319993430
AIMSA
AIMSA
This paper describes a classification system which uses feature selection method based on logistic regression algorithm. As a feature elimination criterion the variance inflation factor of the statistical logistic regression model is used. The experi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2ff4c0d0787d54d5a9f485710678f90
https://doi.org/10.1007/978-3-319-99344-7_29
https://doi.org/10.1007/978-3-319-99344-7_29
Autor:
Michał Stolarczyk, Magdalena Lugowska, Artur Góra, Tomasz Magdziarz, Sandra Goldowska, Karolina Mitusińska, Alicja Płuciennik
Publikováno v:
Bioinformatics (Oxford, England). 33(13)
Motivation The identification and tracking of molecules which enter active site cavity requires screening the positions of thousands of single molecules along several thousand molecular dynamic steps. To fill the existing gap between tools searching
Autor:
Aleksander Placzek, Alicja Pluciennik, Agnieszka Kotecka-Blicharz, Michal Jarzab, Dariusz Mrozek
Publikováno v:
IEEE Access, Vol 8, Pp 175125-175139 (2020)
The use of machine learning has increased over the years, especially in the world of molecular data. Generally, the inference of relationships between features is determined by statistical models. The phenotype (observable clinical characteristics) c
Externí odkaz:
https://doaj.org/article/0ee3867318e24c79a90b0750465408a3