Zobrazeno 1 - 10
of 147
pro vyhledávání: '"P Chouvardas"'
Autor:
Fani Roumelioti, Christos Tzaferis, Dimitris Konstantopoulos, Dimitra Papadopoulou, Alejandro Prados, Maria Sakkou, Anastasios Liakos, Panagiotis Chouvardas, Theodore Meletakos, Yiannis Pandis, Niki Karagianni, Maria C Denis, Maria Fousteri, Maria Armaka, George Kollias
Publikováno v:
eLife, Vol 13 (2024)
miRNAs constitute fine-tuners of gene expression and are implicated in a variety of diseases spanning from inflammation to cancer. miRNA expression is deregulated in rheumatoid arthritis (RA); however, their specific role in key arthritogenic cells s
Externí odkaz:
https://doaj.org/article/e5d50d4d00c3408c8809b26c70ef81cd
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Long non-coding RNAs (lncRNAs) represent an emerging class of genes which play significant and diverse roles in human cancers. Nevertheless, the functional repertoires of lncRNAs in cancer cell subtypes remains unknown since most studies are
Externí odkaz:
https://doaj.org/article/971c6d8989064529a4f1b107d36448db
Autor:
Katja Ovchinnikova, Jannis Born, Panagiotis Chouvardas, Marianna Rapsomaniki, Marianna Kruithof-de Julio
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-7 (2024)
Abstract Machine learning (ML) models of drug sensitivity prediction are becoming increasingly popular in precision oncology. Here, we identify a fundamental limitation in standard measures of drug sensitivity that hinders the development of personal
Externí odkaz:
https://doaj.org/article/0b70ce5cd8e84908af41f9aac145c56b
Autor:
Daniel Hanhart, Federico Gossi, Maria Anna Rapsomaniki, Marianna Kruithof-de Julio, Panagiotis Chouvardas
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-7 (2024)
Abstract Single-cell multi-omics have transformed biomedical research and present exciting machine learning opportunities. We present scLinear, a linear regression-based approach that predicts single-cell protein abundance based on RNA expression. Sc
Externí odkaz:
https://doaj.org/article/339131cd997d4828bfb77af969194e71
Akademický článek
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Autor:
Martina Minoli, Thomas Cantore, Daniel Hanhart, Mirjam Kiener, Tarcisio Fedrizzi, Federico La Manna, Sofia Karkampouna, Panagiotis Chouvardas, Vera Genitsch, Antonio Rodriguez-Calero, Eva Compérat, Irena Klima, Paola Gasperini, Bernhard Kiss, Roland Seiler, Francesca Demichelis, George N. Thalmann, Marianna Kruithof-de Julio
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-16 (2023)
Abstract Bladder Cancer (BLCa) inter-patient heterogeneity is the primary cause of treatment failure, suggesting that patients could benefit from a more personalized treatment approach. Patient-derived organoids (PDOs) have been successfully used as
Externí odkaz:
https://doaj.org/article/506bcb5c022948ab961b87996aa3927e
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Zebrafish have the capacity to fully regenerate the heart after an injury, which lies in sharp contrast to the irreversible loss of cardiomyocytes after a myocardial infarction in humans. Transcriptomics analysis has contributed to dissect u
Externí odkaz:
https://doaj.org/article/19fdd2d72b1d4c4d9d465fe902bf9a4d
Autor:
G. Thalmann, M.M. Minoli, T.C. Cantore, F.L. La Manna, M.K. Kiener, S.K. Karkampouna, P.C. Chouvardas, A.R. Rodriquez-Calero, B.K. Kiss, F.D. Demichelis, M.K.D. Kruithof-de Julio
Publikováno v:
European Urology Open Science, Vol 60, Iss , Pp S13- (2023)
Externí odkaz:
https://doaj.org/article/db1346e38d934cb1ab62f0452a2eded4
Autor:
Dimitra Papadopoulou, Fani Roumelioti, Christos Tzaferis, Panagiotis Chouvardas, Anna-Kathrine Pedersen, Filippos Charalampous, Eleni Christodoulou-Vafeiadou, Lydia Ntari, Niki Karagianni, Maria C. Denis, Jesper V. Olsen, Alexios N. Matralis, George Kollias
Publikováno v:
JCI Insight, Vol 8, Iss 9 (2023)
Synovial fibroblasts (SFs) are key pathogenic drivers in rheumatoid arthritis (RA). Their in vivo activation by TNF is sufficient to orchestrate full arthritic pathogenesis in animal models, and TNF blockade proved efficacious for a high percentage o
Externí odkaz:
https://doaj.org/article/1d4158356be44267b7a2df77d6bc97a8
We present a novel diffusion scheme for online kernel-based learning over networks. So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS), is the need for updating a growing number of parame
Externí odkaz:
http://arxiv.org/abs/1703.08131
