UnityMol-Lite: Cross-platform Collaboration and Interactive Methods for Molecular Modeling in XR

Authors

Antoine Taly (ORCID: https://orcid.org/0000-0001-5109-0091)
Marc Baaden (ORCID: https://orcid.org/0000-0001-6472-0486)
Jérôme Hénin (ORCID: https://orcid.org/0000-0003-2540-4098)
Bastien Vincke (ORCID: https://orcid.org/0000-0002-4770-4238)
Nicolas Férey (ORCID: https://orcid.org/0000-0002-7713-001X)
Hubert Santuz (ORCID: https://orcid.org/0000-0001-6149-9480)
Mariano Spivak

Institutions

Université Paris-Saclay (FR)
Laboratoire de Biochimie Théorique (FR)
Institut de Biologie Physico-Chimique (FR)
Laboratoire des systèmes et applications des technologies de l'information et de l'énergie (FR)
Biologie intégrée du globule rouge et de l'Erythropoïèse (FR)
Laboratoire Interdisciplinaire des Sciences du Numérique (FR)

Publication Details

Journal: SPIRE - Sciences Po Institutional REpository
Published: 2024-11-27
Primary Topic: Machine Learning in Materials Science
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Agence Nationale de la Recherche

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article

UnityMol-Lite: Cross-platform Collaboration and Interactive Methods for Molecular Modeling in XR

Antoine Taly, Marc Baaden, Jérôme Hénin, Bastien Vincke et al.

Nov 27, 2024

SPIRE - Sciences Po Institutional REpository

Machine Learning in Materials Science

article

UnityMol-Lite: Cross-platform Collaboration and Interactive Methods for Molecular Modeling in XR

Antoine Taly, Marc Baaden, Jérôme Hénin, Bastien Vincke, Nicolas Férey, Hubert Santuz, Mariano Spivak

November 27, 2024article en

Abstract

No abstract available for this paper.

SPIRE - Sciences Po Institutional REpository

Université Paris-Saclay (FR), Laboratoire de Biochimie Théorique (FR), Institut de Biologie Physico-Chimique (FR), Laboratoire des systèmes et applications des technologies de l'information et de l'énergie (FR), Biologie intégrée du globule rouge et de l'Erythropoïèse (FR), Laboratoire Interdisciplinaire des Sciences du Numérique (FR)

Agence Nationale de la Recherche

Openalex Percentile: Top 82%

Machine Learning in Materials Science

Open Access PDF OpenAlex

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