References
The initial code for this package was first used in [Wilson2021]. Please cite it if you use this package in published work.
Wilson, K. A.; Wang, L.; Lin, Y. C.; O’Mara, M. L. Investigating the Lipid Fingerprint of SLC6 Neurotransmitter Transporters: A Comparison of DDAT, HDAT, HSERT, and GlyT2. BBA Advances 2021, 1, 100010. doi: 10.1016/j.bbadva.2021.100010
The DEI algorithm with a hard cutoff was first used in [Corradi2018].
Corradi, V., Mendez-Villuendas, E., Ingólfsson, H. I., Gu, R.-X., Siuda, I., Melo, M. N., Moussatova, A., DeGagné, L. J., Sejdiu, B. I., Singh, G., Wassenaar, T. A., Delgado Magnero, K., Marrink, S. J., & Tieleman, D. P. Lipid–Protein Interactions Are Unique Fingerprints for Membrane Proteins. ACS Cent Sci 4, 709–717 (2018). doi:10.1021/acscentsci.8b00143
Lipyds is built on MDAnalysis. Please cite [Michaud-Agrawal2011] and [Gowers2016] if you use this package in published work.
N. Michaud-Agrawal, E. J. Denning, T. B. Woolf, and O. Beckstein. MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations. J. Comput. Chem. 32 (2011), 2319–2327. doi:10.1002/jcc.21787
R. J. Gowers, M. Linke, J. Barnoud, T. J. E. Reddy, M. N. Melo, S. L. Seyler, D. L. Dotson, J. Domanski, S. Buchoux, I. M. Kenney, and O. Beckstein. MDAnalysis: A Python package for the rapid analysis of molecular dynamics simulations. In S. Benthall and S. Rostrup, editors, Proceedings of the 15th Python in Science Conference, pages 98-105, Austin, TX, 2016. SciPy. doi:10.25080/Majora-629e541a-00e