D.D. Boehr, R. Nussinov & P.E. Wright (2009):
The role of dynamic conformational ensembles in biomolecular recognition.
Nat. Chem. Biol. 5(11),
pp. 789–796,
doi:10.1038/nchembio.232.
A. Cangelosi, Nolfi S. & Parisi D. (2003):
Artificial Life Models of Neural Development.
In: On Growth, form and Computers.
Elsevier Academic Press,
pp. 339–52,
doi:10.1016/B978-012428765-5/50051-7.
D. Fraccalvieri, A. Pandini, F. Stella & L. Bonati (2011):
Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps..
BMC Bioinformatics 12,
pp. 158,
doi:10.1186/1471-2105-12-158.
D. Fraccalvieri, M. Tiberti, A. Pandini, L. Bonati & E. Papaleo (2012):
Functional annotation of the mesophilic-like character of mutants in a cold-adapted enzyme by self-organising map analysis of their molecular dynamics.
Mol. Biosyst. 8,
pp. 2680–91,
doi:10.1039/C2MB25192B.
S. Horvath (2011):
Weighted Network Analysis: Applications in Genomics and Systems Biology.
Springer,
doi:10.1007/978-1-4419-8819-5.
T.K. Kohonen (2013):
Essentials of the Self-Organizing Map.
Neural Networks 37,
pp. 52–65,
doi:10.1016/j.neunet.2012.09.018.
R. Mojena (1977):
Hierarchical Grouping Methods and Stopping Rules: An Evaluation..
Comput. J. 20(4),
pp. 359–63,
doi:10.1093/comjnl/20.4.359.
M.E.J. Newman (2010):
Networks: An Introduction.
Oxford University Press,
New York.
A. Pandini, D. Fraccalvieri & L. Bonati (2013):
Artificial Neural Networks for Efficient Clustering of Conformational Ensembles and their Potential for Medicinal Chemistry.
Curr. Top. Med. Chem. 13(5),
pp. 642–51,
doi:10.2174/1568026611313050007.
J. Shao, S.W. Tanner, N. Thompson & T.E. Cheatham (2007):
Clustering molecular dynamics trajectories: 1. Characterizing the performance of different clustering algorithms.
J. Chem. Theory Comput. 3(6),
pp. 2312–34,
doi:10.1021/ct700119m.