Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Jonathan Ronen"'
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-22 (2024)
Abstract The recent advances in high-throughput single-cell sequencing have created an urgent demand for computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models a
Externí odkaz:
https://doaj.org/article/523364de021c45029896cfa9633848d4
Publikováno v:
Genome Biology, Vol 23, Iss 1, Pp 1-23 (2022)
Abstract Tumors are complex tissues of cancerous cells surrounded by a heterogeneous cellular microenvironment with which they interact. Single-cell sequencing enables molecular characterization of single cells within the tumor. However, cell annotat
Externí odkaz:
https://doaj.org/article/718b4b508f2a4431a3f67c0e887f275b
Autor:
Jonathan Ronen, Altuna Akalin
Publikováno v:
F1000Research, Vol 7 (2018)
Single cell RNA-seq (scRNA-seq) experiments suffer from a range of characteristic technical biases, such as dropouts (zero or near zero counts) and high variance. Current analysis methods rely on imputing missing values by various means of local aver
Externí odkaz:
https://doaj.org/article/55e6d7dd3f0c49f3a139ab9dc42ae2a8
Autor:
Jonathan Ronen, Altuna Akalin
Publikováno v:
F1000Research, Vol 7 (2018)
Single cell RNA-seq (scRNA-seq) experiments suffer from a range of characteristic technical biases, such as dropouts (zero or near zero counts) and high variance. Current analysis methods rely on imputing missing values by various means of local aver
Externí odkaz:
https://doaj.org/article/52dc2faca2c348b28fef7234416df413
The recent advances in high-throughput single-cell sequencing has significantly required computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models are required to a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c0aa79097e4ef0f7406eb8435119459
https://doi.org/10.1101/2023.01.18.524506
https://doi.org/10.1101/2023.01.18.524506
Publikováno v:
British Journal of Political Science. 52:107-127
Does social media educate voters, or mislead them? This study measures changes in political knowledge among a panel of voters surveyed during the 2015 UK general election campaign while monitoring the political information to which they were exposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a368ad89391e6017529ce3c5b04f6283
https://doi.org/10.1017/s0007123420000198
https://doi.org/10.1017/s0007123420000198
Cancer is a complex disease with a large financial and healthcare burden on society. One hallmark of the disease is the uncontrolled growth and proliferation of malignant cells. Unlike Mendelian diseases which may be explained by a few genomic loci,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdfa2f6073d304654ff3675152526f0f
https://doi.org/10.1101/2021.09.29.462364
https://doi.org/10.1101/2021.09.29.462364
Publikováno v:
American Journal of Political Science. 63:690-705
Pinning down the role of social ties in the decision to protest has been notoriously elusive, largely due to data limitations. Social media and their global use by protesters offer an unprecedented opportunity to observe real‐time social ties and o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d488940b233bc4a60d887bd9729b62d
https://doi.org/10.1111/ajps.12436
https://doi.org/10.1111/ajps.12436
Autor:
Timm Weber, Anna Jauch, Rebecca Caeser, Jonathan Ronen, Tomoharu Yasuda, Daniel J. Hodson, Kristian Unger, Ulrike Sack, Altuna Akalin, Klaus Rajewsky, Van Trung Chu, Thomas Sommermann, Xun Li, Jingwei Zhang, Tristan Wirtz
Publikováno v:
Proc Natl Acad Sci U S A
Epstein-Barr virus (EBV) is a B cell transforming virus that causes B cell malignancies under conditions of immune suppression. EBV orchestrates B cell transformation through its latent membrane proteins (LMPs) and Epstein-Barr nuclear antigens (EBNA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9eb0fd89ab93abe34ccc672a11d75e0
https://pubmed.ncbi.nlm.nih.gov/32522871
https://pubmed.ncbi.nlm.nih.gov/32522871
Publikováno v:
Cancer Research. 81:196-196
Cancer is a heterogeneous collection of diseases traditionally classified by the tissue of origin. The diversity of the molecular profiles of cancers has a big impact on the way patients are diagnosed and treated, how they respond to their prescribed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6299e18ea4124b319396333af659b940
https://doi.org/10.1158/1538-7445.am2021-196
https://doi.org/10.1158/1538-7445.am2021-196