Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Noël Malod-Dognin"'
Autor:
Katarina Mihajlović, Gaia Ceddia, Noël Malod-Dognin, Gabriela Novak, Dimitrios Kyriakis, Alexander Skupin, Nataša Pržulj
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Parkinson’s disease (PD) is a complex neurodegenerative disorder without a cure. The onset of PD symptoms corresponds to 50% loss of midbrain dopaminergic (mDA) neurons, limiting early-stage understanding of PD. To shed light on early PD d
Externí odkaz:
https://doaj.org/article/531af1861e4c4f0fa772b4af187f52dd
Autor:
Noël Malod-Dognin, Gaia Ceddia, Maja Gvozdenov, Branko Tomić, Sofija Dunjić Manevski, Valentina Djordjević, Nataša Pržulj
Publikováno v:
PLoS ONE, Vol 18, Iss 4 (2023)
Antithrombin resistance is a rare subtype of hereditary thrombophilia caused by prothrombin gene variants, leading to thrombotic disorders. Recently, the Prothrombin Belgrade variant has been reported as a specific variant that leads to antithrombin
Externí odkaz:
https://doaj.org/article/52bc55a561a7478d9ae8acfd1f932492
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
Abstract The COVID-19 pandemic is raging. It revealed the importance of rapid scientific advancement towards understanding and treating new diseases. To address this challenge, we adapt an explainable artificial intelligence algorithm for data fusion
Externí odkaz:
https://doaj.org/article/245d217219a24046be298a5c3a9c30f9
Publikováno v:
PLoS ONE, Vol 17, Iss 1, p e0261676 (2022)
MotivationGraphlet adjacency extends regular node adjacency in a network by considering a pair of nodes being adjacent if they participate in a given graphlet (small, connected, induced subgraph). Graphlet adjacencies captured by different graphlets
Externí odkaz:
https://doaj.org/article/b0f6ed053afa42809dec1ab83c8624d3
Publikováno v:
International Journal of Molecular Sciences, Vol 24, Iss 2, p 1431 (2023)
The COVID-19 pandemic is an acute and rapidly evolving global health crisis. To better understand this disease’s molecular basis and design therapeutic strategies, we built upon the recently proposed concept of an integrated cell, iCell, fusing thr
Externí odkaz:
https://doaj.org/article/ea23992fe9824eda8269e3bfe11af15b
Autor:
Noël Malod-Dognin, Julia Petschnigg, Sam F. L. Windels, Janez Povh, Harry Hemingway, Robin Ketteler, Nataša Pržulj
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-13 (2019)
Integration of omics data remains a challenge. Here, the authors introduce iCell, a framework to integrate tissue-specific protein–protein interaction, co-expression and genetic interaction data, enabling identification of the most rewired genes in
Externí odkaz:
https://doaj.org/article/f16ba5ea82984765ad79c0f292ce025e
Autor:
Thomas Gaudelet, Noël Malod-Dognin, Jon Sánchez-Valle, Vera Pancaldi, Alfonso Valencia, Nataša Pržulj
Publikováno v:
PLoS ONE, Vol 15, Iss 4, p e0231059 (2020)
Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these prof
Externí odkaz:
https://doaj.org/article/72157891471241f38a3c74ca1fe4eda6
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
Abstract Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfe
Externí odkaz:
https://doaj.org/article/8f438089094d4a76bad0b44343da244b
Autor:
Noël Malod-Dognin, Julia Petschnigg, Sam F. L. Windels, Janez Povh, Harry Hemingway, Robin Ketteler, Nataša Pržulj
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-1 (2019)
The original version of this Article contained an error in the spelling of the author Harry Hemingway, which was incorrectly given as Harry Hemmingway. This has been corrected in both the PDF and HTML versions of the Article.
Externí odkaz:
https://doaj.org/article/1d11223e7e4d4cb9a840512fa18fee90
Publikováno v:
Bioinformatics. 39
Motivation Advances in omics technologies have revolutionized cancer research by producing massive datasets. Common approaches to deciphering these complex data are by embedding algorithms of molecular interaction networks. These algorithms find a lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be6a547b58c7059a806aed2700b23f31
https://doi.org/10.1093/bioinformatics/btad281
https://doi.org/10.1093/bioinformatics/btad281