Zobrazeno 1 - 10
of 137
pro vyhledávání: '"Papoutsoglou P"'
Autor:
Dimitrios Tzovaras, Iordanis Papoutsoglou, Georgios Nikoletos, Alexandros Nizamis, Antonios Lalas, Konstantinos Votis, Georgios Spanos
Publikováno v:
Open Research Europe, Vol 4 (2024)
The e-commerce and digital technologies growth, has led to the emergence of various electronic marketplaces having the ability to connect parties across geographical locations, thus offering convenience and flexibility. The European Union recognizes
Externí odkaz:
https://doaj.org/article/e3887e88acc7472da5fd6f93487e621a
Free and open source software is widely used in the creation of software systems, whereas many organisations choose to provide their systems as open source. Open source software carries licenses that determine the conditions under which the original
Externí odkaz:
http://arxiv.org/abs/2110.00361
Autor:
Caroline Gélabert, Panagiotis Papoutsoglou, Irene Golán, Eric Ahlström, Adam Ameur, Carl-Henrik Heldin, Laia Caja, Aristidis Moustakas
Publikováno v:
Cell Communication and Signaling, Vol 21, Iss 1, Pp 1-26 (2023)
Abstract Background Long non-coding RNAs (lncRNAs) regulate cellular processes by interacting with RNAs or proteins. Transforming growth factor β (TGFβ) signaling via Smad proteins regulates gene networks that control diverse biological processes,
Externí odkaz:
https://doaj.org/article/a582c71957894d6caef289ea2cc1fa2b
Software developers are social creatures: they communicate, collaborate, and promote their work in a variety of channels. Twitter, GitHub, Stack Overflow, and other platforms offer developers opportunities to network and exchange ideas. Researchers a
Externí odkaz:
http://arxiv.org/abs/2103.17054
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-13 (2023)
Abstract Plant phenotyping experiments are conducted under a variety of experimental parameters and settings for diverse purposes. The data they produce is heterogeneous, complicated, often poorly documented and, as a result, difficult to reuse. Meet
Externí odkaz:
https://doaj.org/article/2ddb45fd971e406cb112a09654a4a827
Autor:
Corentin Louis, Tanguy Ferlier, Raffaële Leroux, Raphaël Pineau, Matthis Desoteux, Panagiotis Papoutsoglou, Delphine Leclerc, Gaëlle Angenard, Javier Vaquero, Rocio I.R. Macias, Julien Edeline, Cédric Coulouarn
Publikováno v:
JHEP Reports, Vol 5, Iss 12, Pp 100900- (2023)
Background & Aims: Intrahepatic cholangiocarcinoma (iCCA) is a deadly cancer worldwide with an increasing incidence and limited therapeutic options. Therefore, there is an urgent need to open the field to new concepts for identifying clinically relev
Externí odkaz:
https://doaj.org/article/d65272770452400784fb8235c71e509e
Autor:
Scott Bowler, Georgios Papoutsoglou, Aristides Karanikas, Ioannis Tsamardinos, Michael J. Corley, Lishomwa C. Ndhlovu
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract Since the onset of the COVID-19 pandemic, increasing cases with variable outcomes continue globally because of variants and despite vaccines and therapies. There is a need to identify at-risk individuals early that would benefit from timely
Externí odkaz:
https://doaj.org/article/b5d98b8fb0da490a9f7efec0cabcabc8
Autor:
Georgios Papoutsoglou, Sonia Tarazona, Marta B. Lopes, Thomas Klammsteiner, Eliana Ibrahimi, Julia Eckenberger, Pierfrancesco Novielli, Alberto Tonda, Andrea Simeon, Rajesh Shigdel, Stéphane Béreux, Giacomo Vitali, Sabina Tangaro, Leo Lahti, Andriy Temko, Marcus J. Claesson, Magali Berland
Publikováno v:
Frontiers in Microbiology, Vol 14 (2023)
Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction
Externí odkaz:
https://doaj.org/article/a35769259f1946d3b9af729120cec4fd
Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
Autor:
Domenica D’Elia, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou, Michelangelo Ceci, Aldert Zomer, Marta B. Lopes, Eliana Ibrahimi, Aleksandra Gruca, Alina Nechyporenko, Marcus Frohme, Thomas Klammsteiner, Enrique Carrillo-de Santa Pau, Laura Judith Marcos-Zambrano, Karel Hron, Gianvito Pio, Andrea Simeon, Ramona Suharoschi, Isabel Moreno-Indias, Andriy Temko, Miroslava Nedyalkova, Elena-Simona Apostol, Ciprian-Octavian Truică, Rajesh Shigdel, Jasminka Hasić Telalović, Erik Bongcam-Rudloff, Piotr Przymus, Naida Babić Jordamović, Laurent Falquet, Sonia Tarazona, Alexia Sampri, Gaetano Isola, David Pérez-Serrano, Vladimir Trajkovik, Lubos Klucar, Tatjana Loncar-Turukalo, Aki S. Havulinna, Christian Jansen, Randi J. Bertelsen, Marcus Joakim Claesson
Publikováno v:
Frontiers in Microbiology, Vol 14 (2023)
The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve
Externí odkaz:
https://doaj.org/article/5f8da7afb1744c6687be2586111ac38e
Autor:
Ioannis Tsamardinos, Paulos Charonyktakis, Georgios Papoutsoglou, Giorgos Borboudakis, Kleanthi Lakiotaki, Jean Claude Zenklusen, Hartmut Juhl, Ekaterini Chatzaki, Vincenzo Lagani
Publikováno v:
npj Precision Oncology, Vol 6, Iss 1, Pp 1-17 (2022)
Abstract Fully automated machine learning (AutoML) for predictive modeling is becoming a reality, giving rise to a whole new field. We present the basic ideas and principles of Just Add Data Bio (JADBio), an AutoML platform applicable to the low-samp
Externí odkaz:
https://doaj.org/article/f2dc8bdf872b45419ea0cde209017745