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Statistical inference in mechanistic models: time warping for improved gradient matching

Mu Niu, Benn Macdonald, Simon Rogers, Maurizio Filippone, Dirk Husmeier
2017 Computational statistics (Zeitschrift)  
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]

Mu Niu, Simon Rogers, Maurizio Filippone, Dirk Husmeier
2017 Lecture Notes in Computer Science  
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]

Patrick N Lawlor, Matthew G Perich, Lee E Miller, Konrad P Kording
2018 bioRxiv   pre-print
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]

Giovanna Maria Dimitri, Simeon Spasov, Andrea Duggento, Luca Passamonti, Pietro Lio', Nicola Toschi
2021 bioRxiv   pre-print
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]

Matthew E. Levine, Andrew M. Stuart
2022 arXiv   pre-print
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

Jiawei Xie, Jinsong Huang, Cheng Zeng, Shui-Hua Jiang, Nathan Podlich
2020 Geosciences  
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

Yogesh M Kulkarni, David J Klinke
2012 Proteome Science  
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

Herath Mudiyanselage Viraj Vidura Herath, Jayashree Chadalawada, Vladan Babovic
2021 Hydrology and Earth System Sciences  
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

David Rudrauf, Daniel Bennequin, Isabela Granic, Gregory Landini, Karl Friston, Kenneth Williford
2017 Journal of Theoretical Biology  
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

M Peirlinck, F Sahli Costabal, J Yao, J M Guccione, S Tripathy, Y Wang, D Ozturk, P Segars, T M Morrison, S Levine, E Kuhl
2021 Biomechanics and Modeling in Mechanobiology  
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

Rodolfo Metulini, Marica Manisera, Paola Zuccolotto
2018 Journal of Quantitative Analysis in Sports (JQAS)  
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

Thomas Akam, Ines Rodrigues-Vaz, Ivo Marcelo, Xiangyu Zhang, Michael Pereira, Rodrigo Freire Oliveira, Peter Dayan, Rui M. Costa
2020 Neuron  
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

Sumra Bari, Nicole L. Vike, Khrystyna Stetsiv, Alexa Walter, Sharlene Newman, Keisuke Kawata, Jeffrey J. Bazarian, Linda Papa, Eric A. Nauman, Thomas M. Talavage, Semyon Slobounov, Hans C. Breiter
2021 Neuroimage: Reports  
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

Xue Wang, Shichen Shen, Sailee Suryakant Rasam, Jun Qu
2019 Mass spectrometry reviews (Print)  
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]

Paul G. ten Boom
2012 arXiv   pre-print
'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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