Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Rebecka Jörnsten"'
Autor:
Ida Larsson, Erika Dalmo, Ramy Elgendy, Mia Niklasson, Milena Doroszko, Anna Segerman, Rebecka Jörnsten, Bengt Westermark, Sven Nelander
Publikováno v:
Molecular Systems Biology, Vol 17, Iss 9, Pp 1-19 (2021)
Abstract Tumor cell heterogeneity is a crucial characteristic of malignant brain tumors and underpins phenomena such as therapy resistance and tumor recurrence. Advances in single‐cell analysis have enabled the delineation of distinct cellular stat
Externí odkaz:
https://doaj.org/article/65c2adc5f7ff4fcfb10d205bdc3d16b7
Publikováno v:
Cancer Medicine, Vol 9, Iss 10, Pp 3551-3562 (2020)
Abstract Background Characterizing breast cancer progression and aggressiveness relies on categorical descriptions of tumor stage and grade. Interpreting these categorical descriptions is challenging because stage convolutes the size and spread of th
Externí odkaz:
https://doaj.org/article/323a08f7fd2e466da1d92eb04fa0550f
Autor:
Elin Almstedt, Ramy Elgendy, Neda Hekmati, Emil Rosén, Caroline Wärn, Thale Kristin Olsen, Cecilia Dyberg, Milena Doroszko, Ida Larsson, Anders Sundström, Marie Arsenian Henriksson, Sven Påhlman, Daniel Bexell, Michael Vanlandewijck, Per Kogner, Rebecka Jörnsten, Cecilia Krona, Sven Nelander
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
We lack effective treatment for half of children with high-risk neuroblastoma. Here, the authors introduce an algorithm that can predict the effect of interventions on gene expression signatures associated with high disease processes and risk, and id
Externí odkaz:
https://doaj.org/article/9eefbf3ff5bb4e6b9e9c8aacbd9a935c
Autor:
Bergthor Björnsson, Carl Borrebaeck, Nils Elander, Thomas Gasslander, Danuta R. Gawel, Mika Gustafsson, Rebecka Jörnsten, Eun Jung Lee, Xinxiu Li, Sandra Lilja, David Martínez-Enguita, Andreas Matussek, Per Sandström, Samuel Schäfer, Margaretha Stenmarker, X. F. Sun, Oleg Sysoev, Huan Zhang, Mikael Benson, on behalf of the Swedish Digital Twin Consortium
Publikováno v:
Genome Medicine, Vol 12, Iss 1, Pp 1-4 (2019)
Abstract Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins. These are high-resolution models of individual patients that ar
Externí odkaz:
https://doaj.org/article/813cc408ddb94ef6ad9e11849ee4ab05
Autor:
Eleftheria Alevronta, Viktor Skokic, Gail Dunberger, Cecilia Bull, Karin Bergmark, Rebecka Jörnsten, Gunnar Steineck
Publikováno v:
PLoS ONE, Vol 16, Iss 4, p e0250004 (2021)
BackgroundThe study aims to determine possible dose-volume response relationships between the rectum, sigmoid colon and small intestine and the 'excessive mucus discharge' syndrome after pelvic radiotherapy for gynaecological cancer.Methods and mater
Externí odkaz:
https://doaj.org/article/fe668ca28ae54636ba6aed7cde1d0be7
Autor:
Johan Gustafsson, Felix Held, Jonathan L Robinson, Elias Björnson, Rebecka Jörnsten, Jens Nielsen
Publikováno v:
PLoS ONE, Vol 15, Iss 9, p e0239495 (2020)
Cell-type specific gene expression profiles are needed for many computational methods operating on bulk RNA-Seq samples, such as deconvolution of cell-type fractions and digital cytometry. However, the gene expression profile of a cell type can vary
Externí odkaz:
https://doaj.org/article/2a59eb2ff267438495cba19c49e154ee
Autor:
Johan Gustafsson, Jonathan Robinson, Juan S Inda-Díaz, Elias Björnson, Rebecka Jörnsten, Jens Nielsen
Publikováno v:
PLoS ONE, Vol 15, Iss 12, p e0243360 (2020)
Single-cell RNA sequencing has become a valuable tool for investigating cell types in complex tissues, where clustering of cells enables the identification and comparison of cell populations. Although many studies have sought to develop and compare d
Externí odkaz:
https://doaj.org/article/19f756ebe70142529c4f10a2ab4efa37
Nervous system cancers contain a large spectrum of transcriptional cell states, reflecting processes active during normal development, injury response and growth. However, we lack a good understanding of these states’ regulation and pharmacological
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f7c5a03859665d60c78b769c21a18ad
https://doi.org/10.1101/2023.03.10.532041
https://doi.org/10.1101/2023.03.10.532041
Data analysis in systems medicine often employs knowledge-driven approaches, which leverage prior biological insights to guide and inform the study of large omic sets. However, the current state of knowledge in biology is still partial and biased. Fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e954768296bc32aaade0b9acd407bb70
https://doi.org/10.1101/2023.03.07.531501
https://doi.org/10.1101/2023.03.07.531501
Autor:
Teresia Kling, Roberto Ferrarese, Darren Ó hAilín, Patrik Johansson, Dieter Henrik Heiland, Fangping Dai, Ioannis Vasilikos, Astrid Weyerbrock, Rebecka Jörnsten, Maria Stella Carro, Sven Nelander
Publikováno v:
EBioMedicine, Vol 12, Iss C, Pp 72-85 (2016)
Glioblastomas are characterized by transcriptionally distinct subtypes, but despite possible clinical relevance, their regulation remains poorly understood. The commonly used molecular classification systems for GBM all identify a subtype with high e
Externí odkaz:
https://doaj.org/article/89100b0f366d436e9ce9dffd3f55033f