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Jaana M Hartikainen

Showing results (1-10 of 88) with videos related to

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Anticancer Research|January 25, 2008
A BRCA2 mutation, 4088insA, in a Finnish breast and ovarian cancer family associated with favourable clinical courseJaana M Hartikainen, Arto Mannermaa, Seppo Heinonen, et al.
Scientific Reports|July 8, 2020
Predicting breast cancer risk using interacting genetic and demographic factors and machine learningHamid Behravan, Jaana M Hartikainen, Maria Tengström, et al.
Scientific Reports|December 30, 2022
Expression profiles of small non-coding RNAs in breast cancer tumors characterize clinicopathological features and show prognostic and predictive potentialEmmi Kärkkäinen, Sami Heikkinen, Maria Tengström, et al.
Cancer Medicine|July 1, 2020
High mutation burden of circulating cell-free DNA in early-stage breast cancer patients is associated with a poor relapse-free survivalJouni Kujala, Jaana M Hartikainen, Maria Tengström, et al.
Cancer Medicine|May 7, 2021
The debatable presence of PIWI-interacting RNAs in invasive breast cancerEmmi Kärkkäinen, Sami Heikkinen, Maria Tengström, et al.
Cell Stress & Chaperones|March 8, 2024
Comprehensive analysis of human tissues reveals unique expression and localization patterns of HSF1 and HSF2Jenny Joutsen, Jenny C Pessa, Otto Jokelainen, et al.
Cancer Research|September 12, 2012
Genetic polymorphisms and protein expression of NRF2 and Sulfiredoxin predict survival outcomes in breast cancerJaana M Hartikainen, Maria Tengström, Veli-Matti Kosma, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|March 15, 2006
Refinement of the 22q12-q13 breast cancer--associated region: evidence of TMPRSS6 as a candidate gene in an eastern Finnish populationJaana M Hartikainen, Hanna Tuhkanen, Vesa Kataja, et al.
Cells|November 27, 2024
Circulating Micro-RNAs Predict the Risk of Recurrence in Triple-Negative Breast CancerJouni Kujala, Maria Tengström, Sami Heikkinen, et al.
Scientific Reports|September 5, 2018
Machine learning identifies interacting genetic variants contributing to breast cancer risk: A case study in Finnish cases and controlsHamid Behravan, Jaana M Hartikainen, Maria Tengström, et al.
Pageof 9

Showing results (1-10 of 88) with videos related to

Sort By:
Pageof 9
Anticancer Research|January 25, 2008
A BRCA2 mutation, 4088insA, in a Finnish breast and ovarian cancer family associated with favourable clinical courseJaana M Hartikainen, Arto Mannermaa, Seppo Heinonen, et al.
Scientific Reports|July 8, 2020
Predicting breast cancer risk using interacting genetic and demographic factors and machine learningHamid Behravan, Jaana M Hartikainen, Maria Tengström, et al.
Scientific Reports|December 30, 2022
Expression profiles of small non-coding RNAs in breast cancer tumors characterize clinicopathological features and show prognostic and predictive potentialEmmi Kärkkäinen, Sami Heikkinen, Maria Tengström, et al.
Cancer Medicine|July 1, 2020
High mutation burden of circulating cell-free DNA in early-stage breast cancer patients is associated with a poor relapse-free survivalJouni Kujala, Jaana M Hartikainen, Maria Tengström, et al.
Cancer Medicine|May 7, 2021
The debatable presence of PIWI-interacting RNAs in invasive breast cancerEmmi Kärkkäinen, Sami Heikkinen, Maria Tengström, et al.
Cell Stress & Chaperones|March 8, 2024
Comprehensive analysis of human tissues reveals unique expression and localization patterns of HSF1 and HSF2Jenny Joutsen, Jenny C Pessa, Otto Jokelainen, et al.
Cancer Research|September 12, 2012
Genetic polymorphisms and protein expression of NRF2 and Sulfiredoxin predict survival outcomes in breast cancerJaana M Hartikainen, Maria Tengström, Veli-Matti Kosma, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|March 15, 2006
Refinement of the 22q12-q13 breast cancer--associated region: evidence of TMPRSS6 as a candidate gene in an eastern Finnish populationJaana M Hartikainen, Hanna Tuhkanen, Vesa Kataja, et al.
Cells|November 27, 2024
Circulating Micro-RNAs Predict the Risk of Recurrence in Triple-Negative Breast CancerJouni Kujala, Maria Tengström, Sami Heikkinen, et al.
Scientific Reports|September 5, 2018
Machine learning identifies interacting genetic variants contributing to breast cancer risk: A case study in Finnish cases and controlsHamid Behravan, Jaana M Hartikainen, Maria Tengström, et al.
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