Andrew L Ferguson
Andrew L Ferguson
Associate Professor of Molecular Engineering, University of Chicago
Verified email at - Homepage
Cited by
Cited by
Investigating the optimal size of anticancer nanomedicine
L Tang, X Yang, Q Yin, K Cai, H Wang, I Chaudhury, C Yao, Q Zhou, ...
Proceedings of the National Academy of Sciences 111 (43), 15344-15349, 2014
Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design
AL Ferguson, JK Mann, S Omarjee, T Ndung’u, BD Walker, ...
Immunity 38 (3), 606-617, 2013
Promoting transparency and reproducibility in enhanced molecular simulations
M Bonomi, G Bussi, C Camilloni, GA Tribello, P Banáš, A Barducci, ...
Nature methods 16 (8), 670-673, 2019
Solubility and Molecular Conformations of n-Alkane Chains in Water
AL Ferguson, PG Debenedetti, AZ Panagiotopoulos
The Journal of Physical Chemistry B 113 (18), 6405-6414, 2009
Systematic determination of order parameters for chain dynamics using diffusion maps
AL Ferguson, AZ Panagiotopoulos, PG Debenedetti, IG Kevrekidis
Proceedings of the National Academy of Sciences 107 (31), 13597-13602, 2010
The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing
JK Mann, JP Barton, AL Ferguson, S Omarjee, BD Walker, A Chakraborty, ...
PLoS Comput Biol 10 (8), e1003776, 2014
Nonlinear dimensionality reduction in molecular simulation: The diffusion map approach
AL Ferguson, AZ Panagiotopoulos, IG Kevrekidis, PG Debenedetti
Chemical Physics Letters 509 (1), 1-11, 2011
Helical antimicrobial polypeptides with radial amphiphilicity
M Xiong, MW Lee, RA Mansbach, Z Song, Y Bao, RM Peek, C Yao, ...
Proceedings of the National Academy of Sciences 112 (43), 13155-13160, 2015
Mapping membrane activity in undiscovered peptide sequence space using machine learning
EY Lee, BM Fulan, GCL Wong, AL Ferguson
Proceedings of the National Academy of Sciences 113 (48), 13588-13593, 2016
Machine learning and data science in soft materials engineering
AL Ferguson
Journal of Physics: Condensed Matter 30 (4), 043002, 2017
Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes
K Shekhar, CF Ruberman, AL Ferguson, JP Barton, M Kardar, ...
Physical review E 88 (6), 062705, 2013
Molecular enhanced sampling with autoencoders: On‐the‐fly collective variable discovery and accelerated free energy landscape exploration
W Chen, AL Ferguson
Journal of computational chemistry 39 (25), 2079-2102, 2018
Integrating diffusion maps with umbrella sampling: Application to alanine dipeptide
AL Ferguson, AZ Panagiotopoulos, PG Debenedetti, IG Kevrekidis
The Journal of chemical physics 134 (13), 04B606, 2011
The value of antimicrobial peptides in the age of resistance
M Magana, M Pushpanathan, AL Santos, L Leanse, M Fernandez, ...
The Lancet Infectious Diseases, 2020
Supramolecular polymorphism: tunable electronic interactions within π-conjugated peptide nanostructures dictated by primary amino acid sequence
BD Wall, AE Zacca, AM Sanders, WL Wilson, AL Ferguson, JD Tovar
Langmuir 30 (20), 5946-5956, 2014
Machine learning for autonomous crystal structure identification
WF Reinhart, AW Long, MP Howard, AL Ferguson, AZ Panagiotopoulos
Soft Matter 13 (27), 4733-4745, 2017
Nonlinear machine learning of patchy colloid self-assembly pathways and mechanisms
AW Long, AL Ferguson
The Journal of Physical Chemistry B 118 (15), 4228-4244, 2014
An experimental and computational investigation of spontaneous lasso formation in microcin J25
AL Ferguson, S Zhang, I Dikiy, AZ Panagiotopoulos, PG Debenedetti, ...
Biophysical journal 99 (9), 3056-3065, 2010
Collective variable discovery and enhanced sampling using autoencoders: Innovations in network architecture and error function design
W Chen, AR Tan, AL Ferguson
The Journal of chemical physics 149 (7), 072312, 2018
What can machine learning do for antimicrobial peptides, and what can antimicrobial peptides do for machine learning?
EY Lee, MW Lee, BM Fulan, AL Ferguson, GCL Wong
Interface focus 7 (6), 20160153, 2017
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