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A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair

PloS one, 2022-11, Vol.17 (11), p.e0276562-e0276562

2022

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Editorial: Computational and Experimental Approaches in Multi-target Pharmacology

Frontiers in pharmacology, 2017-06, Vol.8, p.443-443

Anastasio, Thomas J

2017

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Computational identification of potential multi-drug combinations for reduction of microglial inflammation in Alzheimer disease

Frontiers in pharmacology, 2015-06, Vol.6, p.116-116

Anastasio, Thomas J

2015

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Exploring the contribution of estrogen to amyloid-Beta regulation: a novel multifactorial computational modeling approach

Frontiers in pharmacology, 2013-01, Vol.4, p.16

Anastasio, Thomas J

2013

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A Novel Application of Neural Networks to Identify Potentially Effective Combinations of Biologic Factors for Enhancement of Bone Fusion/Repair

Foot & ankle orthopaedics, 2023-12, Vol.8 (4)

2023

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Computational Analysis of Therapeutic Neuroadaptation to Chronic Antidepressant in a Model of the Monoaminergic Neurotransmitter and Stress Hormone Systems

Frontiers in pharmacology, 2019-10, Vol.10, p.1215-1215

2019

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Computational Model of Antidepressant Response Heterogeneity as Multi-pathway Neuroadaptation

Frontiers in pharmacology, 2017-12, Vol.8, p.925-925

2017

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Computational identification of potential multitarget treatments for ameliorating the adverse effects of amyloid-β on synaptic plasticity

Frontiers in pharmacology, 2014-05, Vol.5, p.85

Anastasio, Thomas J

2014

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Computational Analysis of the Hypothalamic Control of Food Intake

Frontiers in computational neuroscience, 2016-04, Vol.10, p.27-27

2016

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Exploring the Correlation between the Cognitive Benefits of Drug Combinations in a Clinical Database and the Efficacies of the Same Drug Combinations Predicted from a Computational Model

Journal of Alzheimer's disease, 2019-01, Vol.70 (1), p.287-302

Anastasio, Thomas J.

2019

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A geometric method for eigenvalue problems with low-rank perturbations

Royal Society open science, 2017-09, Vol.4 (9), p.170390-170390

2017

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Data-driven modeling of Alzheimer Disease pathogenesis

Journal of theoretical biology, 2011-12, Vol.290, p.60-72

Anastasio, Thomas J.

2011

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Computational modeling of the monoaminergic neurotransmitter and male neuroendocrine systems in an analysis of therapeutic neuroadaptation to chronic antidepressant

European neuropsychopharmacology, 2020-02, Vol.31, p.86-99

2020

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Temporal-logic analysis of microglial phenotypic conversion with exposure to amyloid-β

Molecular bioSystems, 2015-02, Vol.11 (2), p.434-453

Anastasio, Thomas J

2015

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Knowledge-driven computational modeling in Alzheimer's disease research: Current state and future trends

Alzheimer's & dementia, 2017-11, Vol.13 (11), p.1292-1302

2017

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Deriving testable hypotheses through an analogy between individual and collective memory

Collective Memory, 2022, Vol.274 (1), p.99-128

Anastasio, Thomas J

2022

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Bifurcation theory explains waveform variability in a congenital eye movement disorder

Journal of computational neuroscience, 2009-04, Vol.26 (2), p.321-329

2009

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Computational and Experimental Approaches in Multi-Target Pharmacology

Thomas J. Anastasio

2017

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Computational search for hypotheses concerning the endocannabinoid contribution to the extinction of fear conditioning

Frontiers in computational neuroscience, 2013-06, Vol.7, p.74-74

Anastasio, Thomas J

2013

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Predictive encoding of moving target trajectory by neurons in the parabigeminal nucleus

Journal of neurophysiology, 2013-04, Vol.109 (8), p.2029-2043

2013

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Input minimization: a model of cerebellar learning without climbing fiber error signals

Neuroreport, 2001-12, Vol.12 (17), p.3825-3831

Anastasio, Thomas J

2001

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Complex systems modeling of Alzheimer etiology

Alzheimer's & dementia, 2010-07, Vol.6 (4), p.S254-S254

Anastasio, Thomas J

2010

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Simulating the shaping of the fastigial deep nuclear saccade command by cerebellar Purkinje cells

Neural networks, 2010-09, Vol.23 (7), p.789-804

2010

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Using Bayes' Rule to Model Multisensory Enhancement in the Superior Colliculus

Neural computation, 2000-05, Vol.12 (5), p.1165-1187

2000

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Predicting the Potency of Anti-Alzheimer’s Drug Combinations Using Machine Learning

Processes, 2021-02, Vol.9 (2), p.264

Anastasio, Thomas J.

2021

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A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair

Editorial: Computational and Experimental Approaches in Multi-target Pharmacology

Computational identification of potential multi-drug combinations for reduction of microglial inflammation in Alzheimer disease

Exploring the contribution of estrogen to amyloid-Beta regulation: a novel multifactorial computational modeling approach

A Novel Application of Neural Networks to Identify Potentially Effective Combinations of Biologic Factors for Enhancement of Bone Fusion/Repair

Computational Analysis of Therapeutic Neuroadaptation to Chronic Antidepressant in a Model of the Monoaminergic Neurotransmitter and Stress Hormone Systems

Computational Model of Antidepressant Response Heterogeneity as Multi-pathway Neuroadaptation

Computational identification of potential multitarget treatments for ameliorating the adverse effects of amyloid-β on synaptic plasticity

Computational Analysis of the Hypothalamic Control of Food Intake

Exploring the Correlation between the Cognitive Benefits of Drug Combinations in a Clinical Database and the Efficacies of the Same Drug Combinations Predicted from a Computational Model

A geometric method for eigenvalue problems with low-rank perturbations

Data-driven modeling of Alzheimer Disease pathogenesis

Computational modeling of the monoaminergic neurotransmitter and male neuroendocrine systems in an analysis of therapeutic neuroadaptation to chronic antidepressant

Temporal-logic analysis of microglial phenotypic conversion with exposure to amyloid-β

Knowledge-driven computational modeling in Alzheimer's disease research: Current state and future trends

Deriving testable hypotheses through an analogy between individual and collective memory

Bifurcation theory explains waveform variability in a congenital eye movement disorder

Computational and Experimental Approaches in Multi-Target Pharmacology

Computational search for hypotheses concerning the endocannabinoid contribution to the extinction of fear conditioning

Predictive encoding of moving target trajectory by neurons in the parabigeminal nucleus

Input minimization: a model of cerebellar learning without climbing fiber error signals

Complex systems modeling of Alzheimer etiology

Simulating the shaping of the fastigial deep nuclear saccade command by cerebellar Purkinje cells

Using Bayes' Rule to Model Multisensory Enhancement in the Superior Colliculus

Predicting the Potency of Anti-Alzheimer’s Drug Combinations Using Machine Learning

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