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Statistical inference in mechanistic models: time warping for improved gradient matching
2017
Computational statistics (Zeitschrift)
Preserved Fulltext
Inference in mechanistic models of non-linear differential equations is a challenging problem in current computational statistics. ...
The present article adapts an idea from manifold learning and demonstrates that a time warping approach aiming to homogenize intrinsic length scales can lead to a significant improvement in parameter estimation ...
distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in ...
doi:10.1007/s00180-017-0753-z
pmid:31258254
pmcid:PMC6560940
fatcat:tfqtsuwv4bdg5pasdt2apx2f7u
Parameter Inference in Differential Equation Models of Biopathways Using Time Warped Gradient Matching
[chapter]
2017
Lecture Notes in Computer Science
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However, gradient matching critically hinges on the smoothing scheme for function interpolation, with spurious wiggles in the interpolant having a dramatic effect on the subsequent inference. ...
The present article demonstrates that a time warping approach aiming to homogenize intrinsic functional length scales can lead to a significant improvement in parameter estimation accuracy. ...
Our work proposes a first proof of concept that time warping is useful to improve parameter inference in ODE models. ...
doi:10.1007/978-3-319-67834-4_12
fatcat:wkdpjel63zfjdclkp2ofhv5lrm
Linear-Nonlinear-Time-Warp-Poisson models of neural activity
[article]
2018
bioRxiv
pre-print
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Here we combine the standard Linear-Nonlinear-Poisson (LNP) model with Dynamic Time Warping (DTW) to account for shared temporal variability. ...
For example, we can plan a movement at one point in time and execute it at some arbitrary later time. ...
After correcting for time-warp variability, however, model predictions better matched the measured activity. ...
doi:10.1101/194498
fatcat:u7an5ednrbb6nhizfkmyamzq64
Multimodal image fusion via deep generative models
[article]
2021
bioRxiv
pre-print
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In turn, this may be of aid in predicting disease evolution as well as drug response, hence supporting mechanistic disease understanding and also empowering clinical trials. ...
However, they are usually heavily collapsed a priori through procedures which are not learned as part of model training, and consequently not optimized for the downstream prediction task. ...
We expect that our model will be able to aid in the current quest for solid avenues towards personalized medicine, i.e. the goal of creating an individual patient profile which is matched exactly as possible ...
doi:10.1101/2021.03.08.434427
fatcat:jf5o2ux6izh6zckkosglspb7dq
A Framework for Machine Learning of Model Error in Dynamical Systems
[article]
2022
arXiv
pre-print
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The development of data-informed predictive models for dynamical systems is of widespread interest in many disciplines. ...
, and in the training of such models. ...
However, the improvements in validity time for trajectory-based forecasting deteriorate for ε = 2 −1 . ...
arXiv:2107.06658v2
fatcat:w4l47hcnibe55i7rj4b6xw7wwm
Systematic Literature Review on Data-Driven Models for Predictive Maintenance of Railway Track: Implications in Geotechnical Engineering
2020
Geosciences
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This study presents a systematic literature review of data-driven models applied in the predictive maintenance of railway track. ...
Since just before the beginning of the 21st century, data-driven models have been used in the predictive maintenance of railway track. ...
Dynamic time warping [101] is an algorithm for measuring the similarity between two sequences by using the optimal match. The sequences are warped in a nonlinear fashion to match each other. ...
doi:10.3390/geosciences10110425
fatcat:r73zrv554vcsnjbi2aaeswvbsq
Protein-based identification of quantitative trait loci associated with malignant transformation in two HER2+ cellular models of breast cancer
2012
Proteome Science
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Identifying these subtle differences in signaling circuitry will help understand the mechanistic basis for cancer. ...
The warping was done by choosing a reference image and spot matching was facilitated by placing approximately 10 manual vectors in each quadrant of the gel to align cognate spots at corresponding locations ...
Authors' contributions YK was responsible for the 2-DE, MALDI-TOF MS, PMF, IPA analysis, and immunoblotting. ...
doi:10.1186/1477-5956-10-11
pmid:22357162
pmcid:PMC3305585
fatcat:snwo6kokwzadjp3kqhr4hvpwb4
Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling
2021
Hydrology and Earth System Sciences
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MIKA-SHA-induced optimal models outperform the lumped models used in this study in terms of efficiency values while benefitting hydrologists with more meaningful hydrological inferences about the runoff ...
Both optimal models achieve high-efficiency values in hydrograph predictions (both at catchment and subcatchment outlets) and good visual matches with the observed runoff response of the catchment. ...
We greatly appreciate the support given by Vojtech Havlicek, for the R programming. Furthermore, we acknowledge Fabrizio Fenicia, for his assistance with the SUPERFLEX framework. Review statement. ...
doi:10.5194/hess-25-4373-2021
fatcat:u3hw36csw5ab3hxky5dj7pv4yu
A mathematical model of embodied consciousness
2017
Journal of Theoretical Biology
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projective geometry and under the control of a process of active inference. ...
The FoC in the PCM combines multisensory evidence with prior beliefs in memory, for the choices of projective points of view, that respond to a combination of spatial and affective priors. ...
Acknowledgments We thank for their help at various stages of the elaboration and writing of this work: Guillaume ...
doi:10.1016/j.jtbi.2017.05.032
pmid:28554611
fatcat:j73ialdt2fbxto6cekvvuutqeq
Precision medicine in human heart modeling : Perspectives, challenges, and opportunities
2021
Biomechanics and Modeling in Mechanobiology
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However, the exact role in precision medicine for human heart modeling has not yet been fully explored. ...
We illustrate recent human heart modeling in electrophysiology, cardiac mechanics, and fluid dynamics and highlight clinically relevant applications of these models for drug development, pacing lead failure ...
The mention of commercial products, their sources, or their use in connection with material reported herein is not to be constructed as either an actual or implied endorsement of such products by the Department ...
doi:10.1007/s10237-021-01421-z
pmid:33580313
pmcid:PMC8154814
fatcat:yt4jb7s445fdri6l4r65o47tba
Modelling the dynamic pattern of surface area in basketball and its effects on team performance
2018
Journal of Quantitative Analysis in Sports (JQAS)
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We propose a three-step procedure integrating different statistical modelling approaches. ...
Specifically, we first employ a Markov Switching Model (MSM) to detect structural changes in the surface area. ...
a match importance factor and a time depreciation factor giving less weight to matches that are played a long time ago. ...
doi:10.1515/jqas-2018-0041
fatcat:b3qwsi7tqjg2vdo7gbjtiorv6m
The Anterior Cingulate Cortex Predicts Future States to Mediate Model-Based Action Selection
2020
Neuron
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Accordingly, ACC is necessary only for updating model-based strategies, not for basic reward-driven action reinforcement. ...
These results reveal that ACC is a critical node in model-based control, with a specific role in predicting future states given chosen actions. ...
Activity was aligned across trials by warping the time period between the choice and second-step port entry to match the median trial timings, activity prior to choice and after second-step port entry ...
doi:10.1016/j.neuron.2020.10.013
pmid:33152266
pmcid:PMC7837117
fatcat:gq3vdtuvgralzcwwynjjy5wqsu
Integrating multi-omics with neuroimaging and behavior: A preliminary model of dysfunction in football athletes
2021
Neuroimage: Reports
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This imaging-omics framework using permutation-based mediation/moderation analysis has general applicability for human-animal translational studies. ...
A B S T R A C T Contact sports affect measures at multiple scales such as transcriptomics, metabolomics, brain function, and behavior, but studies have not yet studied the statistical structure of how ...
We further thank John Csernansky, MD for his helpful editing comments. We would like to thank Dr. Zoran Martinovich and Dr. Jaroslaw Harezlak for providing guidance for the statistical analysis. ...
doi:10.1016/j.ynirp.2021.100032
fatcat:umnd23sl5rg2vdv6mzus3nz3yq
MS1 ion current‐based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts
2019
Mass spectrometry reviews (Print)
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To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, ...
Prominent technical developments in these aspects are discussed. ...
lavage
COW
correlation-optimized warping
CPM
continuous profile model
CLL
chronic lymphocytic leukemia
DTW
dynamic time warping
DTT
dithiothreitol
DIA
data-independent acquisition
DDA
data-dependent ...
doi:10.1002/mas.21595
pmid:30920002
pmcid:PMC6849792
fatcat:k2wdwq5de5c7je6neybjjz7e6u
A beacon of new physics: The Pioneer anomaly modelled as a path based speed loss driven by the externalisation of aggregate non-inertial QM energy
[article]
2012
arXiv
pre-print
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'Solutions' of the new model may extend to: the Earth flyby anomaly, solar system related large-scale anomalies in the CMB radiation data, the nature of dark energy, and how a theory of everything unification ...
Working backwards from the observational evidence, and rethinking: time, mass, quantum entanglement and non-locality, we hypothesise a mechanism involving a quantum mechanical energy source and a new type ...
A different role for geometric phase in a 'mechanistic' system Within atoms/molecules, i.e. ...
arXiv:1205.3312v3
fatcat:pd7cy2kizzftvmubomkqiqmegm
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