Cited by 34Lipid Membrane Structure and BehaviorScientific Computing and Data ManagementResearch Data Management Practices

Overlay databank unlocks data-driven analyses of biomolecules for all

Open access
Kiirikki, Anne M., Antila, Hanne S., Bort, Lara S., Buslaev, Pavel, Favela-Rosales, Fernando, Ferreira, Tiago Mendes, Fuchs, Patrick F. J., Garcia-Fandino, Rebeca +21 more·2024·Nature Communications

Published version of a preprint

Abstract

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank—a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.

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References 74 · Cited by 34

Authors
Kiirikki, A. M., Antila, H. S., Bort, L. S., Buslaev, P., Favela-Rosales, F., Ferreira, T. M., Fuchs, P. F. J., Garcia-Fandino, R., Gushchin, I., Kav, B., Kučerka, N., Kula, P., Kurki, M., Kuzmin, A., Lalitha, A., Lolicato, F., Madsen, J. J., Miettinen, M. S., Mingham, C., Monticelli, L., Nencini, R., Nesterenko, A. M., Piggot, T. J., Piñeiro, Á., Reuter, N., Samantray, S., Suárez-Lestón, F., Talandashti, R., & Ollila, O. H. S.
Affiliations
  • University of Helsinki (FI)
  • Max Planck Institute of Colloids and Interfaces (DE)
  • University of Potsdam (DE)
  • University of Jyväskylä (FI)
  • Tecnológico Nacional de México (MX)
  • Martin Luther University Halle-Wittenberg (DE)
  • Centre National de la Recherche Scientifique (FR)
  • Forschungszentrum Jülich (DE)
  • Comenius University Bratislava (SK)
  • Czech Academy of Sciences (CZ)
  • University of Eastern Finland (FI)
  • University of South Florida (US)
  • Technische Hochschule Mannheim (DE)
  • University of Bergen (NO)
  • University of Southampton (GB)
  • Universidade de Santiago de Compostela (ES)
Corresponding author
Ollila, O. H. Samuli
Venue
Nature Communications
Published
2024-02-07
Volume
15
Issue
1
Pages
1136-1136
ISSN
2041-1723 (ISSN-L)
OpenAlex
W4391607908
Cited by
34
References
74
Citations by year
2026: 10 · 2025: 13 · 2024: 11
FWCI
4.61
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, cc-by)
  • Jyväskylä University Digital Archive (University of Jyväskylä) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • RWTH Publications (RWTH Aachen)
Funders
  • Tecnológico Nacional de México
  • Ministerio de Ciencia, Innovación y Universidades (RYC-2016-20335, PID2019, RTI2018-098795-A-I00, RTI2018, ED431F 2020/05)
  • Trond Mohn stiftelse (BFS2017TMT01)
  • Deutsche Forschungsgemeinschaft (LO 2821/1-1, 2821/1-1)
  • Institut National de la Santé et de la Recherche Médicale
  • Academy of Finland (315596)
  • Suomen Kulttuurirahasto
  • China Scholarship Council
  • Norges Forskningsråd (Sigma2, 335772, 288008)
  • Universidad Nacional Autónoma de México
  • Vedecká Grantová Agentúra MŠVVaŠ SR a SAV (VEGA 1/0223/20, 1/0223/20)
  • Axencia Galega de Innovación (ED431B)
  • Xunta de Galicia (ED431G/09, ED431F 2020/05, RYC-2016-20335, ED431G, 2022/36, ED431B 2022/36, RTI2018-098795-A-I00, ED431B)
  • Centro Singular de Investigación de Galicia (ED431G, ED431F 2020/05, ED431 G/09, RYC-2016-20335, RTI2018-098795-A-I00)
  • Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (LANCAD-UNAM-DGTIC-057)
  • European Regional Development Fund (RYC-2016-20335, 2016-2019, PID2019-111327GB-I00, RTI2018-098795-A-I00, RTI2018, ED431F 2020/05, PDC2022-133402-I00, ED431G/09)
  • Agencia Estatal de Investigación (ED431F 2020/05, PID2019-111327GB-I00, PDC2022-133402-I00, RYC-2016-20335, RTI2018-098795-A-I00, PID2019)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Lipid Membrane Structure and Behavior
  • Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
Keywords
molecular dynamics simulation data, plasma membrane, lipid composition, open data access, machine learning training data, graphical user interface
MeSH terms
Machine Learning, Artificial Intelligence, Cell Membrane, Membrane Lipids, Molecular Dynamics Simulation

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