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End-to-End Differentiable Molecular Mechanics Force Field Construction [article]

Yuanqing Wang, Josh Fass, Benjamin Kaminow, John E. Herr, Dominic Rufa, Ivy Zhang, Iván Pulido, Mike Henry, John D. Chodera
2022 arXiv   pre-print
accuracy vis-\'a-vis experiments in computing relative alchemical free energy calculations for a popular benchmark set.  ...  Leveraging accuracy and speed, these functional forms find use in a wide variety of applications in biomolecular modeling and drug discovery, from rapid virtual screening to detailed free energy calculations  ...  Top: Tyrosine kinase 2 system parametrized by Espaloma and miminized and equilibrated with TIP3P water model [69] and counterions.  ... 
arXiv:2010.01196v3 fatcat:273366ilxzepdkb2nngx5ktna4

Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives

N. M. deSouza, J. M. Winfield, J. C. Waterton, A. Weller, M.-V. Papoutsaki, S. J. Doran, D. J. Collins, L. Fournier, D. Sullivan, T. Chenevert, A. Jackson, M. Boss (+2 others)
2017 European Radiology  
A standardised ADC measurement in longitudinal studies could be utilized as a prognostic biomarker in oncology and for stratifying patients for therapeutic interventions.  ...  For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up.  ...  1.5-T [11] , emphasising that suitability for inclusion in a multicentre trial requires assessment of individual scanner performance.  ... 
doi:10.1007/s00330-017-4972-z pmid:28956113 pmcid:PMC5811587 fatcat:ysc7qrvhp5gvbizyrdsxx5pvvu

Setting the Phosphorus Boundaries for Greek Natural Shallow and Deep Lakes for Water Framework Directive Compliance

Ifigenia Kagalou, Chrysoula Ntislidou, Dionissis Latinopoulos, Dimitra Kemitzoglou, Vasiliki Tsiaoussi, Dimitra C. Bobori
2021 Water  
Eutrophication caused by nutrient enrichment is a predominant stressor leading to lake degradation and, thus, the set-up of boundaries that support good ecological status, the Water Framework Directive's  ...  A wide range of different statistical approaches has been proposed in the Best Practice Guide for determining appropriate nutrient thresholds.  ...  The network is supervised by the General Directorate for Waters of the Ministry of Environment and Energy. EKBY's personnel conducted samplings and contributed to sample analysis.  ... 
doi:10.3390/w13050739 fatcat:c4dnaxqnujddda3iqkl322oxvi

BigDataStack - D2.6 Conceptual model and Reference architecture - III

Dimosthenis Kyriazis, Mauricio Fadel Argerich, Orlando Avila-García, Ainhoa Azqueta, Bin Cheng, Ismael Cuadrado-Cordero, Christos Doulkeridis, Kostas Giannakopoulos, Gal Hammer, Ricardo Jimenez, Michele Iorio, Konstantinos Kalaboukas (+19 others)
2020 Zenodo  
This deliverable is a refinement of the key functionalities of the overall architecture, the interactions between the main building blocks and their components, as they were described in the previous version  ...  of the architecture (Deliverable D2.5 - Conceptual model and Reference architecture II).  ...  The component list is as follows: • Modeling toolkit: This component provides the interface for business analysts to design their processes in a non-expert way, the interface for developers to provide  ... 
doi:10.5281/zenodo.4004585 fatcat:tiocxddpunerdkdh67qc5hhvzq

A machine learning metasystem for robust probabilistic nonlinear regression-based forecasting of seasonal water availability in the US West

Sean W. Fleming, Angus G. Goodbody
2019 IEEE Access  
We built a probabilistic nonlinear regression water supply forecast (WSF) technique for the US Department of Agriculture, which runs the largest stand-alone WSF system in the US West.  ...  but radically updating the principal components regression framework widely used for WSF.  ...  These tasks are performed here using a combination of an unsupervised learning algorithm for feature extraction, an evolutionary algorithm for feature selection, and a suite of regression models embedded  ... 
doi:10.1109/access.2019.2936989 fatcat:qwwyufndvjeablhncoo4stozzi

Discrete Object Generation with Reversible Inductive Construction [article]

Ari Seff, Wenda Zhou, Farhan Damani, Abigail Doyle, Ryan P. Adams
2019 arXiv   pre-print
The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs.  ...  Here, we present a generative model for discrete objects employing a Markov chain where transitions are restricted to a set of local operations that preserve validity.  ...  Acknowledgements We would like to thank Wengong Jin, Michael Galvin, Dieterich Lawson, and members of the Princeton Laboratory for Intelligent Probabilistic Systems for valuable discussion and feedback  ... 
arXiv:1907.08268v2 fatcat:r4kzsjc745brbjgmferpy62xai

Physical and digital phantoms for validating tractography and assessing artifacts

Ivana Drobnjak, Peter Neher, Cyril Poupon, Tabinda Sarwar
2021 NeuroImage  
As a substitute for in vivo data with a real ground truth that could be used for validation, a widely and successfully employed approach is the use of synthetic phantoms.  ...  As it is the case for all scientific methods, proper validation is a key prerequisite for the successful application of fiber tractography, be it in the area of basic neuroscience or in a clinical setting  ...  Assessing artifacts, quality control and AI One of the very important aspects of artifact assessment in Diffusion MRI is quality control (QC).  ... 
doi:10.1016/j.neuroimage.2021.118704 pmid:34748954 fatcat:zygzq576lnhqxekoixpnc4y3pq

Framing QA as Building and Ranking Intersentence Answer Justifications

Peter Jansen, Rebecca Sharp, Mihai Surdeanu, Peter Clark
2017 Computational Linguistics  
We include a detailed characterization of the justification quality for both our method and a strong baseline, and show that information aggregation is key to addressing the information need in complex  ...  We then jointly rank answers and their justifications using a reranking perceptron that treats justification quality as a latent variable.  ...  Mihai Surdeanu discloses a financial interest in Lum.ai.  ... 
doi:10.1162/coli_a_00287 fatcat:kqssixxjpbavdc6nimqknvtn74

Probabilistic risk assessment – the keystone for the future of toxicology

Alexandra Maertens
2022 ALTEX: Alternatives to Animal Experimentation  
In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm - probably!  ...  This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based  ...  Acknowledgements Thomas Hartung would like to thank Dr Joanna Jaworska for pioneering the field of ProbRA and introducing him to the topic.  ... 
doi:10.14573/altex.2201081 pmid:35034131 pmcid:PMC8906258 fatcat:punp7mcufbay3lcj3f4gqn7oae

Traditional machine learning and big data analytics in virtual screening: a comparative study

Sahar K. Hussin, Yasser M. Omar, Salah M. Abdelmageid, Mahmoud I. Marie
2020 International Journal of Advanced Computer Research  
In many public libraries, label and non-label data are accessible to model such molecules at a highperformance scale.  ...  For example, to distinguish drugs from non-drug [34] or between compounds that have or do not have specific activity [35, 36] , in artificial accessibility [37] , or water solutions [38] , SVMs are  ... 
doi:10.19101/ijacr.2019.940150 fatcat:zzdudmniuvaytcqwhvicn4kg64

A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution [article]

Daniele Ramazzotti
2016 arXiv   pre-print
The framework presented in this work along with algorithms derived from it, represents a novel approach for inferring cancer progression, whose accuracy and convergence rates surpass the existing techniques  ...  Recently, there has been a resurgence of interest in rigorous algorithms for the inference of cancer progression from genomic data.  ...  See Figure 5 Bootstrapping data Finally, we perform non-parametric bootstrap as a further estimation of the confidence in the inferred results.  ... 
arXiv:1602.07614v1 fatcat:3mdqck6ztnav7eea2xz4hl5xue

Machine Learning for Anomaly Detection: A Systematic Review

Ali Bou Nassif, Manar Abu Talib, Qassim Nasir, Fatima Mohamad Dakalbab
2021 IEEE Access  
In the fourth stage, rules are identified for quality assessment to be used to filter the collected study papers.  ...  Moreover, the same concept applies to quality assessment since we applied a strict QAR. V.  ... 
doi:10.1109/access.2021.3083060 fatcat:vv7qthbvqjdz7ksm3yosulk22q

Feasibility study Open MCRA

Johannes W. Kruisselbrink, Marco S. van Lenthe, Hilko van der Voet, Waldo J. de Boer, Jacob D. van Klaveren
2021 EFSA Supporting Publications  
This report presents the results of a feasibility study for improving transparency and accessibility of the models implemented in the Monte Carlo Risk Assessment (MCRA) web platform for assessing the risk  ...  The report ends with a suggested approach and next steps, including a discussion on the need for a governance structure for sustainable development of Open MCRA. © Wageningen Research and RIVM, 2021  ...  and José Cortiñas Abrahantes (EFSA) for their helpful comments on drafts of this publication.  ... 
doi:10.2903/sp.efsa.2021.en-6515 fatcat:mmntclu6pbb5zpjpeuctuu6vhy

The metaRbolomics Toolbox in Bioconductor and beyond

Jan Stanstrup, Corey D. Broeckling, Rick Helmus, Nils Hoffmann, Ewy Mathé, Thomas Naake, Luca Nicolotti, Kristian Peters, Johannes Rainer, Reza M. Salek, Tobias Schulze, Emma L. Schymanski (+7 others)
2019 Metabolites  
This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation  ...  Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system.  ...  Five different machine learning algorithms are available to build models. Plotting available to explore chemical space and model quality assessment.  ... 
doi:10.3390/metabo9100200 pmid:31548506 pmcid:PMC6835268 fatcat:3b2gnq6qdrcfbcq6hewgoobdce

Meeting abstracts from the 4th International Clinical Trials Methodology Conference (ICTMC) and the 38th Annual Meeting of the Society for Clinical Trials

2017 Trials  
Acknowledgements Funded by the MRC North West Hub in Trials Methodological Research (MR/K025635/1) and the NIHR Health Technology Assessment programme (08/14/39).  ...  These include non-parametric bootstrapping, and frequentist approaches such as Ordinary Least Square regression (OLS).  ...  Individual patient level survival and health related quality of life (HRQOL) data were analysed using a flexible parametric model and a mixed effects model for repeated measures, respectively.  ... 
doi:10.1186/s13063-017-1902-y fatcat:yt477zyq4vbi7cm6f3sozyl42u
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