Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Aneta Polewko-Klim"'
Autor:
Aneta Polewko-Klim, Wojciech Lesiński, Agnieszka Kitlas Golińska, Krzysztof Mnich, Maria Siwek, Witold R. Rudnicki
Publikováno v:
Poultry Science, Vol 99, Iss 12, Pp 6341-6354 (2020)
Two categories of immune responses—innate and adaptive immunity—have both polygenic backgrounds and a significant environmental component. The goal of the reported study was to define candidate genes and mutations for the immune traits of interes
Externí odkaz:
https://doaj.org/article/65933f16a8064f159430f76f1e1f1ff8
Autor:
Aneta Polewko-Klim, Sibo Zhu, Weicheng Wu, Yijing Xie, Ning Cai, Kexun Zhang, Zhen Zhu, Tao Qing, Ziyu Yuan, Kelin Xu, Tiejun Zhang, Ming Lu, Weimin Ye, Xingdong Chen, Chen Suo, Witold R. Rudnicki
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly cons
Externí odkaz:
https://doaj.org/article/7b5c3be94f154e3789759c2e9699f0ea
Autor:
Aneta Polewko-Klim, Wojciech Lesiński, Krzysztof Mnich, Radosław Piliszek, Witold R. Rudnicki
Publikováno v:
Biology Direct, Vol 13, Iss 1, Pp 1-22 (2018)
Abstract Background Modern experimental techniques deliver data sets containing profiles of tens of thousands of potential molecular and genetic markers that can be used to improve medical diagnostics. Previous studies performed with three different
Externí odkaz:
https://doaj.org/article/a07d01ef6a6942088cef423f635d9715
Autor:
Witold R. Rudnicki, Krzysztof Mnich, Wojciech Lesinski, Maria Siwek, Aneta Polewko-Klim, Agnieszka Kitlas Golińska
Publikováno v:
Poultry Science, Vol 99, Iss 12, Pp 6341-6354 (2020)
Poultry Science
Poultry Science
Two categories of immune responses—innate and adaptive immunity—have both polygenic backgrounds and a significant environmental component. The goal of the reported study was to define candidate genes and mutations for the immune traits of interes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9919b6aa163a88248560216890e5c2a3
http://www.sciencedirect.com/science/article/pii/S0032579120306064
http://www.sciencedirect.com/science/article/pii/S0032579120306064
Publikováno v:
Journal of Medical Systems
We present a protocol for integrating two types of biological data – clinical and molecular – for more effective classification of patients with cancer. The proposed approach is a hybrid between early and late data integration strategy. In this h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b23bf94566d1a576d212d1a6801eae35
http://europepmc.org/articles/PMC7902598
http://europepmc.org/articles/PMC7902598
Autor:
Witold R. Rudnicki, Krzysztof Mnich, Agnieszka Kitlas Golinska, Aneta Polewko-Klim, Wojciech Lesinski
Publikováno v:
ICDM (Workshops)
Super learner algorithm was created to combine results of multiple base learners with the use of cross validation. However, in many cases it does not outperform significantly a simple average of the base results. We propose to apply multiple repeats
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d20d100db31b4ea32a446caef343dde
https://doi.org/10.1109/icdmw51313.2020.00089
https://doi.org/10.1109/icdmw51313.2020.00089
Autor:
Witold R. Rudnicki, Aneta Polewko-Klim
Publikováno v:
Trends and Innovations in Information Systems and Technologies ISBN: 9783030456900
WorldCIST (2)
WorldCIST (2)
This paper presents the protocol for integration of data coming from two most common types of biological data (clinical and molecular) for more effective classification patients with cancer disease. In this protocol, the identification of the most in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b3e3f64bc395a02c4bc25fdc4c6e226
https://doi.org/10.1007/978-3-030-45691-7_56
https://doi.org/10.1007/978-3-030-45691-7_56
Publikováno v:
Trends and Innovations in Information Systems and Technologies ISBN: 9783030456900
WorldCIST (2)
WorldCIST (2)
Prostate cancer is the most common cancer among men in high-income countries. This study examines which clinical variables are useful for prediction of clinical end-point for patients with metastatic castration-resistant prostate cancer. First inform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50fae382e2c32fb5ecc39080eb1be77f
https://doi.org/10.1007/978-3-030-45691-7_57
https://doi.org/10.1007/978-3-030-45691-7_57
Autor:
Witold R. Rudnicki, Aneta Polewko-Klim
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030504199
ICCS (3)
ICCS (3)
Discovery of diagnostic and prognostic molecular markers is important and actively pursued the research field in cancer research. For complex diseases, this process is often performed using Machine Learning. The current study compares two approaches
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::306d61fed14c0e1d4a39bba63baa3a44
https://doi.org/10.1007/978-3-030-50420-5_39
https://doi.org/10.1007/978-3-030-50420-5_39
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030504199
ICCS (3)
ICCS (3)
Super learner algorithm can be applied to combine results of multiple base learners to improve quality of predictions. The default method for verification of super learner results is by nested cross validation; however, this technique is very expensi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dc70599b21e26baa880a2d419a90a18
https://doi.org/10.1007/978-3-030-50420-5_41
https://doi.org/10.1007/978-3-030-50420-5_41