Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Nina Miolane"'
Publikováno v:
Frontiers in Molecular Biosciences, Vol 11 (2024)
Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image
Externí odkaz:
https://doaj.org/article/19a2396eda624f80a89cae989873551e
Publikováno v:
Frontiers in Bioinformatics, Vol 3 (2023)
Conventional dimensionality reduction methods like Multidimensional Scaling (MDS) are sensitive to the presence of orthogonal outliers, leading to significant defects in the embedding. We introduce a robust MDS method, called DeCOr-MDS (Detection and
Externí odkaz:
https://doaj.org/article/cf0f0aa2441b471a94883a7577c297dd
Autor:
Nina Miolane, Xavier Pennec
Publikováno v:
Entropy, Vol 17, Iss 4, Pp 1850-1881 (2015)
In computational anatomy, organ’s shapes are often modeled as deformations of a reference shape, i.e., as elements of a Lie group. To analyze the variability of the human anatomy in this framework, we need to perform statistics on Lie groups. A Lie
Externí odkaz:
https://doaj.org/article/9ea511ff289042c89936ecf23b5e4100
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783031289927
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4dd88ed0f26790545ddf526c56bc64e2
https://doi.org/10.1007/978-3-031-28993-4_31
https://doi.org/10.1007/978-3-031-28993-4_31
Autor:
Axel Levy, Frédéric Poitevin, Julien Martel, Youssef Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, Gordon Wetzstein
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198021
Comput Vis ECCV
Comput Vis ECCV
Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in structural biology, helping us understand the basic building blocks of life. The algorithmic challenge of cryo-EM is to jointly estimate the unknown 3D poses and the 3D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e87dc567597f5bf11351f2f136d7718
https://doi.org/10.1007/978-3-031-19803-8_32
https://doi.org/10.1007/978-3-031-19803-8_32
Publikováno v:
Journal of Structural Biology. 214:107920
Recent breakthroughs in high-resolution imaging of biomolecules in solution with cryo-electron microscopy (cryo-EM) have unlocked new doors for the reconstruction of molecular volumes, thereby promising further advances in biology, chemistry, and pha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a58d44448f3dc20af8b030b39aa0369
https://doi.org/10.1016/j.jsb.2022.107920
https://doi.org/10.1016/j.jsb.2022.107920
Autor:
Allison M. Gabbert, James A. Mondo, Joseph P. Campanale, Noah P. Mitchell, Adele Myers, Sebastian J. Streichan, Nina Miolane, Denise J. Montell
Septins self-assemble into polymers that bind and deform membranes in vitro and regulate diverse cell behaviors in vivo. How their in vitro properties relate to their in vivo functions is under active investigation. Here we uncover requirements for s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::598bebea9384088913dbe4e1d0874c7c
https://doi.org/10.1101/2021.04.08.439079
https://doi.org/10.1101/2021.04.08.439079
Autor:
Nina Miolane, Nicolas Guigui, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Daniel Brooks, Bernhard Kainz, Claire Donnat, Susan Holmes, Xavier Pennec
Publikováno v:
HAL
Journal of Machine Learning Research
Journal of Machine Learning Research, Microtome Publishing, 2020, 21 (223), pp.1-9
Journal of Machine Learning Research, 2020, 21 (223), pp.1-9
Journal of Machine Learning Research
Journal of Machine Learning Research, Microtome Publishing, 2020, 21 (223), pp.1-9
Journal of Machine Learning Research, 2020, 21 (223), pp.1-9
International audience; We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matrices, Lie groups of transformations, and many m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8cb7f51a3a95696af7654c621e432e3e
http://hdl.handle.net/20.500.12278/113146
http://hdl.handle.net/20.500.12278/113146
As data is a predominant resource in applications, Riemannian geometry is a natural framework to model and unify complex nonlinear sources of data. However, the development of computational tools from the basic theory of Riemannian geometry is labori
Autor:
Nina Miolane, Paul Chauchat, Xavier Pennec, Bernhard Kainz, Daniel Brooks, Susan Holmes, Johan Mathe, Niklas Koep, Stefan Heyder, Benjamin Hou, Alice Le Brigant, Christian Shewmake, Yann Thanwerdas, Yann Cabanes, Thomas Gerald, Olivier Peltre, Nicolas Guigui, Claire Donnat, Hadi Zaatiti, Hatem Hajri
Publikováno v:
SciPy 2020-19th Python in Science Conference
SciPy 2020-19th Python in Science Conference, Jul 2020, Austin, Texas, United States. pp.48-57, ⟨10.25080/Majora-342d178e-007⟩
Proceedings of the 19th Python in Science Conference
SciPy 2020-19th Python in Science Conference, Jul 2020, Austin, Texas, United States. pp.48-57, ⟨10.25080/Majora-342d178e-007⟩
Proceedings of the 19th Python in Science Conference
International audience; There is a growing interest in leveraging differential geometry in the machine learning community. Yet, the adoption of the associated geometric computations has been inhibited by the lack of a reference implementation. Such a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3547d9c37a81d93725731a1eb934095
https://inria.hal.science/hal-02908006/file/geomstats.pdf
https://inria.hal.science/hal-02908006/file/geomstats.pdf