Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Thomas Pierrot"'
Autor:
Javier Mendoza-Revilla, Evan Trop, Liam Gonzalez, Maša Roller, Hugo Dalla-Torre, Bernardo P. de Almeida, Guillaume Richard, Jonathan Caton, Nicolas Lopez Carranza, Marcin Skwark, Alex Laterre, Karim Beguir, Thomas Pierrot, Marie Lopez
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-18 (2024)
Abstract Significant progress has been made in the field of plant genomics, as demonstrated by the increased use of high-throughput methodologies that enable the characterization of multiple genome-wide molecular phenotypes. These findings have provi
Externí odkaz:
https://doaj.org/article/8af619509e904512a946b50928ccabd2
Autor:
Marie Lopez, Hugo Dalla-Torre, Liam Gonzalez, Javier Mendoza-Revilla, Nicolas Lopez Carranza, Adam Grzywaczewski, Francesco Oteri, Christian Dallago, Evan Trop, Hassan Sirelkhatim, Guillaume Richard, Marcin Skwark, Karim Beguir, Thomas Pierrot
Closing the gap between measurable genetic information and observable traits is a longstanding challenge in genomics. Yet, the prediction of molecular phenotypes from DNA sequences alone remains limited and inaccurate, often driven by the scarcity of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53d35eb637b4693c9cea8bfc8dc0ca0e
https://doi.org/10.1101/2023.01.11.523679
https://doi.org/10.1101/2023.01.11.523679
Autor:
Karim Beguir, Marcin J. Skwark, Yunguan Fu, Thomas Pierrot, Nicolas Lopez Carranza, Alexandre Laterre, Ibtissem Kadri, Abir Korched, Anna U. Lowegard, Bonny Gaby Lui, Bianca Sänger, Yunpeng Liu, Asaf Poran, Alexander Muik, Uğur Şahin
Publikováno v:
Computers in Biology and Medicine. 155:106618
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62fc2f0404519f6b1b8b8c1a0a264ae4
https://doi.org/10.1016/j.compbiomed.2023.106618
https://doi.org/10.1016/j.compbiomed.2023.106618
Autor:
Karim Beguir, Marcin J. Skwark, Yunguan Fu, Thomas Pierrot, Nicolas Lopez Carranza, Alexandre Laterre, Ibtissem Kadri, Abir Korched, Anna U. Lowegard, Bonny Gaby Lui, Bianca Sänger, Yunpeng Liu, Asaf Poran, Alexander Muik, Ugur Sahin
The ongoing COVID-19 pandemic is leading to the discovery of hundreds of novel SARS-CoV-2 variants on a daily basis. While most variants do not impact the course of the pandemic, some variants pose a significantly increased risk when the acquired mut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::565e85aa5586cf621c0ea800f4d6e0b2
https://doi.org/10.1101/2021.12.24.474095
https://doi.org/10.1101/2021.12.24.474095
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030863395
ICANN (2)
Artificial Neural Networks and Machine Learning – ICANN 2021
30th International Conference on Artificial Neural Networks-ICANN 2021
30th International Conference on Artificial Neural Networks-ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.197-208, ⟨10.1007/978-3-030-86340-1_16⟩
ICANN (2)
Artificial Neural Networks and Machine Learning – ICANN 2021
30th International Conference on Artificial Neural Networks-ICANN 2021
30th International Conference on Artificial Neural Networks-ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.197-208, ⟨10.1007/978-3-030-86340-1_16⟩
In this paper, we provide an overview of first-order and second-order variants of the gradient descent method that are commonly used in machine learning. We propose a general framework in which 6 of these variants can be interpreted as different inst
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f950621432111056a84c193f120ab23
https://hal.archives-ouvertes.fr/hal-02397757
https://hal.archives-ouvertes.fr/hal-02397757