Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Anni S. Halkola"'
Autor:
Mike Mason, Óscar Lapuente-Santana, Anni S. Halkola, Wenyu Wang, Raghvendra Mall, Xu Xiao, Jacob Kaufman, Jingxin Fu, Jacob Pfeil, Jineta Banerjee, Verena Chung, Han Chang, Scott D. Chasalow, Hung Ying Lin, Rongrong Chai, Thomas Yu, Francesca Finotello, Tuomas Mirtti, Mikko I. Mäyränpää, Jie Bao, Emmy W. Verschuren, Eiman I. Ahmed, Michele Ceccarelli, Lance D. Miller, Gianni Monaco, Wouter R. L. Hendrickx, Shimaa Sherif, Lin Yang, Ming Tang, Shengqing Stan Gu, Wubing Zhang, Yi Zhang, Zexian Zeng, Avinash Das Sahu, Yang Liu, Wenxian Yang, Davide Bedognetti, Jing Tang, Federica Eduati, Teemu D. Laajala, William J. Geese, Justin Guinney, Joseph D. Szustakowski, Benjamin G. Vincent, David P. Carbone
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-16 (2024)
Abstract Background Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti–PD-1 Response Prediction DREAM Challenge, a crowdsourc
Externí odkaz:
https://doaj.org/article/c3635bd5bd234a2da3cffc46f246670f
Autor:
Teemu D. Laajala, Varsha Sreekanth, Alex C. Soupir, Jordan H. Creed, Anni S. Halkola, Federico C. F. Calboli, Kalaimathy Singaravelu, Michael V. Orman, Christelle Colin-Leitzinger, Travis Gerke, Brooke L. Fridley, Svitlana Tyekucheva, James C. Costello
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-13 (2023)
Abstract Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses acr
Externí odkaz:
https://doaj.org/article/74d7b11469474de8bb6ff94431c8476f
Autor:
Onni Niemelä, Anni S. Halkola, Aini Bloigu, Risto Bloigu, Ulla Nivukoski, Heidi Pohjasniemi, Johanna Kultti
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 21, p 12738 (2022)
Aberrations in blood cells are common among heavy alcohol drinkers. In order to shed further light on such responses, we compared blood cell status with markers of hemolysis, mediators of inflammation and immune responses to ethanol metabolites in al
Externí odkaz:
https://doaj.org/article/c191bf88ce444533a43b013065a83d5e
Publikováno v:
Nutrients, Vol 14, Iss 21, p 4529 (2022)
Although excessive alcohol consumption is a highly prevalent public health problem the data on the associations between alcohol consumption and health outcomes in individuals preferring different types of alcoholic beverages has remained unclear. We
Externí odkaz:
https://doaj.org/article/02eede2131884984bb2b746ca86a2c5a
Autor:
Anni S. Halkola, Kaisa Joki, Tuomas Mirtti, Marko M. Mäkelä, Tero Aittokallio, Teemu D. Laajala
In many real-world applications, such as those based on patient electronic health records, prognostic prediction of patient survival is based on heterogeneous sets of clinical laboratory measurements. To address the trade-off between the predictive a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4833735b60fd808138e1d6cda2fe4a4
http://hdl.handle.net/10138/356766
http://hdl.handle.net/10138/356766
Autor:
Mike Mason, Óscar Lapuente-Santana, Anni S. Halkola, Wenyu Wang, Raghvendra Mall, Xu Xiao, Jacob Kaufman, Jingxin Fu, Jacob Pfeil, Jineta Banerjee, Verena Chung, Han Chang, Scott D. Chasalow, Hung Ying Lin, Rongrong Chai, Thomas Yu, Francesca Finotello, Tuomas Mirtti, Mikko I. Mäyränpää, Jie Bao, Emmy W. Verschuren, Eiman I. Ahmed, Michele Ceccarelli, Lance D. Miller, Gianni Monaco, Wouter R.L. Hendrickx, Shimaa Sherif, Lin Yang, Ming Tang, Shengqing Stan Gu, Wubing Zhang, Yi Zhang, Zexian Zeng, Avinash Das Sahu, Yang Liu, Wenxian Yang, Davide Bedognetti, Jing Tang, Federica Eduati, Teemu D. Laajala, William J. Geese, Justin Guinney, Joseph D. Szustakowski, David P. Carbone, Benjamin G. Vincent
PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti–PD-1 Response Prediction DREAM Challenge, a crowdsourced initiati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e51513261c639c675bde6b1f8b1659ef
https://doi.org/10.1101/2022.12.05.518667
https://doi.org/10.1101/2022.12.05.518667
Publikováno v:
Journal of Theoretical Biology. 545:111147
Tumors consist of heterogeneous cell subpopulations that may develop differing phenotypes, such as increased cell growth, metastatic potential and treatment sensitivity or resistance. To study the dynamics of cancer development at a single-cell level
Publikováno v:
Journal of theoretical biology. 488
Each patient's cancer has a unique molecular makeup, often comprised of distinct cancer cell subpopulations. Improved understanding of dynamic processes between cancer cell populations is therefore critical for making treatment more effective and per
Autor:
Mika, Murtojärvi, Anni S, Halkola, Antti, Airola, Teemu D, Laajala, Tuomas, Mirtti, Tero, Aittokallio, Tapio, Pahikkala
Publikováno v:
International journal of medical informatics. 133
Predictive survival modeling offers systematic tools for clinical decision-making and individualized tailoring of treatment strategies to improve patient outcomes while reducing overall healthcare costs. In 2015, a number of machine learning and stat
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 3, p e1010333 (2023)
In many real-world applications, such as those based on electronic health records, prognostic prediction of patient survival is based on heterogeneous sets of clinical laboratory measurements. To address the trade-off between the predictive accuracy
Externí odkaz:
https://doaj.org/article/95601469c59a46ffae4d1cb8885b145e