Nestoras Karathanasis
Nestoras Karathanasis
Computational Medicine Center, Thomas Jefferson University
Email verificata su jefferson.edu
Titolo
Citata da
Citata da
Anno
GluA2 mRNA distribution and regulation by miR-124 in hippocampal neurons
VM Ho, LO Dallalzadeh, N Karathanasis, MF Keles, S Vangala, T Grogan, ...
Molecular and Cellular Neuroscience 61, 1-12, 2014
402014
Prediction of miRNA targets
A Oulas, N Karathanasis, A Louloupi, GA Pavlopoulos, P Poirazi, ...
RNA Bioinformatics, 207-229, 2015
312015
MiRduplexSVM: a high-performing miRNA-duplex prediction and evaluation methodology
N Karathanasis, I Tsamardinos, P Poirazi
PloS one 10 (5), e0126151, 2015
182015
A new microRNA target prediction tool identifies a novel interaction of a putative miRNA with CCND2
A Oulas, N Karathanasis, A Louloupi, I Iliopoulos, K Kalantidis, P Poirazi
RNA biology 9 (9), 1196-1207, 2012
182012
Combining evidence from four immune cell types identifies DNA methylation patterns that implicate functionally distinct pathways during Multiple Sclerosis progression
E Ewing, L Kular, SJ Fernandes, N Karathanasis, V Lagani, S Ruhrmann, ...
EBioMedicine 43, 411-423, 2019
102019
Finding cancer-associated miRNAs: methods and tools
A Oulas, N Karathanasis, A Louloupi, P Poirazi
Molecular biotechnology 49 (1), 97-107, 2011
102011
Computational identification of miRNAs involved in cancer
A Oulas, N Karathanasis, P Poirazi
MicroRNA and Cancer, 23-41, 2011
82011
omicsNPC: applying the non-parametric combination methodology to the integrative analysis of heterogeneous omics data
N Karathanasis, I Tsamardinos, V Lagani
PloS one 11 (11), e0165545, 2016
72016
Don't use a cannon to kill the… miRNA mosquito
N Karathanasis, I Tsamardinos, P Poirazi
Bioinformatics 30 (7), 1047-1048, 2014
62014
Non-parametric combination analysis of multiple data types enables detection of novel regulatory mechanisms in T cells of multiple sclerosis patients
SJ Fernandes, H Morikawa, E Ewing, S Ruhrmann, RN Joshi, V Lagani, ...
Scientific reports 9 (1), 1-12, 2019
12019
Machine Learning Approaches Identify Genes Containing Spatial Information from Single-Cell Transcriptomics Data.
P Loher, N Karathanasis
bioRxiv, 818393, 2019
12019
Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data
J Tanevski, T Nguyen, B Truong, N Karaiskos, ME Ahsen, X Zhang, C Shu, ...
BioRxiv, 796029, 2019
12019
Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data
J Tanevski, T Nguyen, B Truong, N Karaiskos, ME Ahsen, X Zhang, C Shu, ...
Life science alliance 3 (11), 2020
2020
STATegra: Multi-omics data integration-A conceptual scheme with a bioinformatics pipeline
N Planell, V Lagani, P Sebastian-Leon, F van der Kloet, E Ewing, ...
bioRxiv, 2020
2020
A bioinformatics approach for investigating the determinants of Drosha processing
N Karathanasis, I Tsamardinos, P Poirazi
13th IEEE International Conference on BioInformatics and BioEngineering, 1-4, 2013
2013
Study of miRNA–mRNA interactions related with cancer
N Karathanasis
Πανεπιστήμιο Κρήτης. Σχολή Θετικών και Τεχνολογικών Επιστημών. Τμήμα Βιολογίας, 2013
2013
Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics
J Tanevski, T Nguyen, B Truong, N Karaiskos, M Eren, X Zhang, C Shu, ...
Life Science Alliance, 0
Single Cell Transcriptomics Challenge-DeepCMC Submission
N Karathanasis, P Loher, I Rigoutsos
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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