A. Ferguson

发表

Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design.

Andrew L. Ferguson, Jaclyn K. Mann, B. Walker, 2013, Immunity.

Machine learning-enabled discovery and design of membrane-active peptides.

Andrew L. Ferguson, Andrew L Ferguson, Ernest Y Lee, 2017, Bioorganic & medicinal chemistry.

Thermodynamics, morphology, and kinetics of early-stage self-assembly of π-conjugated oligopeptides

Andrew L. Ferguson, A. Ferguson, J. Tovar, 2016 .

In search of a novel chassis material for synthetic cells: emergence of synthetic peptide compartment.

Andrew L. Ferguson, A. Ferguson, Allen P. Liu, 2020, Soft matter.

Mapping membrane activity in undiscovered peptide sequence space using machine learning

Andrew L. Ferguson, Ernest Y Lee, Benjamin M Fulan, 2016, Proceedings of the National Academy of Sciences.

Systematic determination of order parameters for chain dynamics using diffusion maps

Andrew L. Ferguson, I. Kevrekidis, P. Debenedetti, 2010, Proceedings of the National Academy of Sciences.

Helical antimicrobial polypeptides with radial amphiphilicity

Andrew L. Ferguson, A. Ferguson, Lin-Feng Chen, 2015, Proceedings of the National Academy of Sciences.

Investigating the optimal size of anticancer nanomedicine

Andrew L. Ferguson, A. Ferguson, L. Tang, 2014, Proceedings of the National Academy of Sciences.

Machine learning and data science in soft materials engineering

Andrew L. Ferguson, Andrew L Ferguson, A. Ferguson, 2018, Journal of physics. Condensed matter : an Institute of Physics journal.

Landmark diffusion maps (L-dMaps): Accelerated manifold learning out-of-sample extension

Andrew L. Ferguson, Andrew W. Long, A. Ferguson, 2017, Applied and Computational Harmonic Analysis.

Nonlinear machine learning of patchy colloid self-assembly pathways and mechanisms.

Andrew L. Ferguson, Andrew W. Long, Andrew L Ferguson, 2014, The journal of physical chemistry. B.

Nonlinear dimensionality reduction in molecular simulation: The diffusion map approach

Ioannis G. Kevrekidis, Andrew L. Ferguson, Pablo G. Debenedetti, 2011 .

Machine learning and molecular design of self-assembling -conjugated oligopeptides

Andrew L. Ferguson, A. Ferguson, Bryce A. Thurston, 2018 .

Machine learning antimicrobial peptide sequences: Some surprising variations on the theme of amphiphilic assembly.

Ernest Y Lee, A. Ferguson, G. Wong, 2018, Current opinion in colloid & interface science.

SUPPORTING INFORMATION FOR The Fitness Landscape of HIV-1 Gag

Jaclyn K. Mann, B. Walker, A. Chakraborty, 2014 .

A Study of the Morphology, Dynamics, and Folding Pathways of Ring Polymers with Supramolecular Topological Constraints Using Molecular Simulation and Nonlinear Manifold Learning

Andrew L. Ferguson, A. Ferguson, Jiang Wang, 2017, 1708.00988.

Nonlinear machine learning and design of reconfigurable digital colloids.

Andrew L. Ferguson, Andrew W. Long, A. Ferguson, 2016, Soft matter.

Nonlinear reconstruction of single-molecule free-energy surfaces from univariate time series.

Andrew L. Ferguson, A. Ferguson, Jiang Wang, 2016, Physical review. E.

Free energy calculations of the functional selectivity of 5-HT2B G protein-coupled receptor

Andrew L. Ferguson, Brandon L. Peters, A. Ferguson, 2020, PloS one.

Mesoscale Simulation of Asphaltene Aggregation.

Andrew L. Ferguson, A. Ferguson, Jiang Wang, 2016, The journal of physical chemistry. B.

Variation of formal hydrogen-bonding networks within electronically delocalized π-conjugated oligopeptide nanostructures.

Andrew L. Ferguson, A. Ferguson, J. Tovar, 2014, Langmuir : the ACS journal of surfaces and colloids.

The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry.

Andrew L. Ferguson, Thomas F. Miller, A. Ferguson, 2020, The journal of physical chemistry. A.

Nonlinear and Hierarchical Discovery of Slow Molecular Modes using Sequential Learning with Natural Constraints

Wei Chen, Andrew Ferguson, Hythem Sidky, 2019 .

A computational investigation of the phase behavior and capillary sublimation of water confined between nanoscale hydrophobic plates.

Andrew L. Ferguson, P. Rossky, P. Debenedetti, 2012, The Journal of chemical physics.

Computational design of hepatitis C virus immunogens from host-pathogen dynamics over empirical viral fitness landscapes

Andrew L. Ferguson, Gregory R. Hart, Gregory R Hart, 2018, Physical biology.

Data-driven reaction coordinate discovery in overdamped and non-conservative systems: application to optical matter structural isomerization

Andrew L. Ferguson, John A. Parker, S. Rice, 2020, Nature Communications.

High-Resolution Markov State Models for the Dynamics of Trp-Cage Miniprotein Constructed over Slow Folding Modes Identified by State-Free Reversible VAMPnets.

Wei Chen, Andrew L. Ferguson, Hythem Sidky, 2019, The journal of physical chemistry. B.

Synthesis of polypeptides via bioinspired polymerization of in situ purified N-carboxyanhydrides

Andrew L. Ferguson, A. Ferguson, Yao Lin, 2019, Proceedings of the National Academy of Sciences.

Supramolecular polymorphism: tunable electronic interactions within π-conjugated peptide nanostructures dictated by primary amino acid sequence.

Andrew L. Ferguson, A. Ferguson, J. Tovar, 2014, Langmuir : the ACS journal of surfaces and colloids.

Diffusivities of Gases in Room-Temperature Ionic Liquids: Data and Correlations Obtained Using a Lag-Time Technique

Andrew L. Ferguson, Paul Scovazzo, A. Ferguson, 2005 .

Empirical fitness models for hepatitis C virus immunogen design

Andrew L. Ferguson, Gregory R. Hart, Andrew L Ferguson, 2015, Physical biology.

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Andrew L. Ferguson, Rachael A. Mansbach, Hythem Sidky, 2020, The journal of physical chemistry. B.

Controlling supramolecular chirality in peptide-π-peptide networks by variation of alkyl spacer length.

Andrew L. Ferguson, A. Ferguson, S. Panda, 2019, Langmuir : the ACS journal of surfaces and colloids.

The value of antimicrobial peptides in the age of resistance.

Andrew L. Ferguson, Steven B. Bradfute, A. Ferguson, 2020, The Lancet. Infectious diseases.

Integrating diffusion maps with umbrella sampling: application to alanine dipeptide.

Ioannis G Kevrekidis, Andrew L. Ferguson, Andrew L Ferguson, 2011, The Journal of chemical physics.

Solubility and molecular conformations of n-alkane chains in water.

Andrew L. Ferguson, Andrew L Ferguson, Athanassios Z Panagiotopoulos, 2009, The journal of physical chemistry. B.

PACAP is a pathogen-inducible resident antimicrobial neuropeptide affording rapid and contextual molecular host defense of the brain

Andrew L. Ferguson, Ernest Y Lee, A. Ferguson, 2020, Proceedings of the National Academy of Sciences.

Coarse-Grained Molecular Simulation and Nonlinear Manifold Learning of Archipelago Asphaltene Aggregation and Folding.

Andrew L. Ferguson, A. Ferguson, M. Gayatri, 2018, The journal of physical chemistry. B.

Mesoscale Simulation and Machine Learning of Asphaltene Aggregation Phase Behavior and Molecular Assembly Landscapes.

Andrew L. Ferguson, A. Ferguson, M. Gayatri, 2017, The journal of physical chemistry. B.

Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data

Andrew L. Ferguson, Michael S. Seaman, Arup K. Chakraborty, 2013, PloS one.

Molecular Motor Dnm1 Synergistically Induces Membrane Curvature To Facilitate Mitochondrial Fission

Andrew L. Ferguson, Ernest Y Lee, Nolan W. Kennedy, 2017, ACS central science.

GANs and Closures: Micro-Macro Consistency in Multiscale Modeling

Juan M. Bello-Rivas, I. Kevrekidis, A. Ferguson, 2022, ArXiv.

Tetranucleosome Interactions Drive Chromatin Folding

Andrew L. Ferguson, A. Ferguson, J. D. de Pablo, 2021, ACS central science.

Reconstruction of protein structures from single-molecule time series.

Andrew L. Ferguson, Maximilian Topel, A. Ferguson, 2020, The Journal of chemical physics.

Machine learning force fields and coarse-grained variables in molecular dynamics: application to materials and biological systems.

Fabio Pietrucci, Alexandre Tkatchenko, Andrew L. Ferguson, 2020, Journal of chemical theory and computation.

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Andrew L. Ferguson, Hythem Sidky, Wei Chen, 2020, Molecular Physics.

Recovery of Protein Folding Funnels from Single-Molecule Time Series by Delay Embeddings and Manifold Learning.

Andrew L. Ferguson, A. Ferguson, Jiang Wang, 2018, The journal of physical chemistry. B.

Nonlinear machine learning in simulations of soft and biological materials

Jiang Wang, Andrew L. Ferguson, Andrew Ferguson, 2018 .

Collective variable discovery and enhanced sampling using autoencoders: Innovations in network architecture and error function design.

Wei Chen, Andrew L. Ferguson, Aik Rui Tan, 2018, The Journal of chemical physics.

Molecular enhanced sampling with autoencoders: On‐the‐fly collective variable discovery and accelerated free energy landscape exploration

Wei Chen, Andrew L. Ferguson, A. Ferguson, 2017, J. Comput. Chem..

Global graph matching using diffusion maps

Andrew L. Ferguson, Jingtian Hu, A. Ferguson, 2016, Intell. Data Anal..

An experimental and computational investigation of spontaneous lasso formation in microcin J25.

Andrew L. Ferguson, Andrew L Ferguson, Siyan Zhang, 2010, Biophysical journal.

100th Anniversary of Macromolecular Science Viewpoint: Data-Driven Protein Design.

Rama Ranganathan, Andrew L. Ferguson, R. Ranganathan, 2021, ACS macro letters.

Nonlinear Discovery of Slow Molecular Modes using Hierarchical Dynamics Encoders

Wei Chen, Andrew L. Ferguson, Hythem Sidky, 2019, The Journal of chemical physics.

Promoting transparency and reproducibility in enhanced molecular simulations

Jakub Rydzewski, Toni Giorgino, Massimiliano Bonomi, 2019, Nature Methods.

The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

John P. Barton, Andrew L. Ferguson, Bruce D. Walker, 2014, PLoS Comput. Biol..

Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes.

Arup K Chakraborty, Andrew L. Ferguson, Mehran Kardar, 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

Polymeric "Clickase" Accelerates the Copper Click Reaction of Small Molecules, Proteins, and Cells.

Andrew L. Ferguson, M. Gruebele, A. Ferguson, 2019, Journal of the American Chemical Society.

Enzyme-like Click Catalysis by a Copper-Containing Single-Chain Nanoparticle.

Andrew L. Ferguson, A. Ferguson, S. Zimmerman, 2018, Journal of the American Chemical Society.

Patchy Particle Model of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides.

Andrew L. Ferguson, A. Ferguson, R. Mansbach, 2018, The journal of physical chemistry. B.

BayesWHAM: A Bayesian approach for free energy estimation, reweighting, and uncertainty quantification in the weighted histogram analysis method

Andrew L. Ferguson, A. Ferguson, 2017, J. Comput. Chem..

Machine learning for autonomous crystal structure identification.

Andrew L. Ferguson, Andrew W. Long, Michael P. Howard, 2017, Soft matter.

Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics.

Rachael A Mansbach, Andrew L. Ferguson, Andrew L Ferguson, 2015, The Journal of chemical physics.

Accelerated polymerization of N-carboxyanhydrides catalyzed by crown ether

Andrew L. Ferguson, A. Ferguson, Yao Lin, 2021, Nature Communications.

Revealing the Sequence-Structure-Electronic Property Relation of Self-Assembling π-Conjugated Oligopeptides by Molecular and Quantum Mechanical Modeling.

Andrew L. Ferguson, Ethan P. Shapera, A. Ferguson, 2019, Langmuir : the ACS journal of surfaces and colloids.

Modulation of polypeptide conformation through donor–acceptor transformation of side-chain hydrogen bonding ligands

Andrew L. Ferguson, A. Ferguson, Yao Lin, 2017, Nature Communications.

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction.

Andrew L. Ferguson, A. Ferguson, S. Jenekhe, 2022, Chemical reviews.

What can machine learning do for antimicrobial peptides, and what can antimicrobial peptides do for machine learning?

Andrew L. Ferguson, Andrew L Ferguson, Ernest Y Lee, 2017, Interface Focus.

Thermal Unthreading of the Lasso Peptides Astexin-2 and Astexin-3.

Andrew L. Ferguson, Andrew L Ferguson, A James Link, 2016, ACS chemical biology.

Molecular latent space simulators

Andrew L. Ferguson, Wei Chen, Hythem Sidky, 2020, Chemical science.

Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems pdf

Wei Chen, Andrew L. Ferguson, Hythem Sidky, 2019, The Journal of Chemical Physics.

Inverse design of self-assembling colloidal crystals with omnidirectional photonic bandgaps.

Andrew L. Ferguson, A. Ferguson, Yutao Ma, 2019, Soft matter.

Statistically optimal continuous free energy surfaces from biased simulations and multistate reweighting.

Andrew L. Ferguson, Michael R. Shirts, M. Shirts, 2020, Journal of chemical theory and computation.

Near quantitative synthesis of urea macrocycles enabled by bulky N-substituent

Andrew L. Ferguson, A. Ferguson, Qian Chen, 2021, Nature Communications.

ACS Central Science Virtual Issue on Machine Learning

Andrew L. Ferguson, A. Ferguson, 2018, ACS central science.

Learning the relationship between nanoscale chemical patterning and hydrophobicity

Amish J. Patel, Nicholas B Rego, A. Ferguson, 2022, Proceedings of the National Academy of Sciences of the United States of America.

Rational design of patchy colloids via landscape engineering

Andrew L. Ferguson, Andrew W. Long, A. Ferguson, 2018 .

Control of the hierarchical assembly of π-conjugated optoelectronic peptides by pH and flow.

A. Ferguson, R. Mansbach, 2017, Organic & biomolecular chemistry.

Coarse-Grained Molecular Simulation of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides.

Andrew L. Ferguson, A. Ferguson, R. Mansbach, 2017, The journal of physical chemistry. B.

Computationally Guided Tuning of Amino Acid Configuration Influences the Chiroptical Properties of Supramolecular Peptide-π-Peptide Nanostructures.

Andrew L. Ferguson, A. Ferguson, S. Panda, 2020, Langmuir : the ACS journal of surfaces and colloids.

A MARTINI-Compatible Coarse-Grained Model for the Mesoscale Simulation of Peptoids.

Andrew L. Ferguson, A. Ferguson, J. Pfaendtner, 2020, The journal of physical chemistry. B.

Evidence for Prenucleated Fibrilogenesis of Acid-Mediated Self-Assembling Oligopeptides via Molecular Simulation and Fluorescence Correlation Spectroscopy.

Andrew L. Ferguson, A. Ferguson, W. Wilson, 2018, Langmuir : the ACS journal of surfaces and colloids.

Effect of core oligomer length on the phase behavior and assembly of π-conjugated peptides.

Andrew L. Ferguson, A. Ferguson, J. Tovar, 2020, ACS applied materials & interfaces.

Machine learning assembly landscapes from particle tracking data.

Andrew W. Long, Steve Granick, Jie Zhang, 2015, Soft matter.

GANs and Closures: Micro-Macro Consistency in Multiscale Modeling

Andrew L. Ferguson, Juan M. Bello-Rivas, I. Kevrekidis, 2022, Multiscale Modeling & Simulation.

Modulation of polypeptide conformation through donor–acceptor transformation of side-chain hydrogen bonding ligands

A. Ferguson, Yao Lin, Yun Liu, 2017, Nature Communications.

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Andrew L. Ferguson, A. Ferguson, J. Pablo, 2023, npj Computational Materials.

Nonlinear Discovery of Slow Molecular Modes using Hierarchical Dynamics Encoders pdf

Wei Chen, Andrew L. Ferguson, Hythem Sidky, 2019, ArXiv.

The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry.

Jim Pfaendtner, Andrew L. Ferguson, Thomas F. Miller, 2020, The journal of physical chemistry. B.

Hierarchical Self-Assembly Pathways of Peptoid Helices and Sheets.

Andrew L. Ferguson, A. Ferguson, J. Pfaendtner, 2022, Biomacromolecules.