Results 51 to 60 of about 150,984 (329)

Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression

Energies, 2022
In this study, the crude oil spot price is forecast using Bayesian symbolic regression (BSR). In particular, the initial parameters specification of BSR is analysed.
Krzysztof Drachal
doaj   +1 more source

Revisiting the Sequential Symbolic Regression Genetic Programming [PDF]

, 2016
Sequential Symbolic Regression (SSR) is a technique that recursively induces functions over the error of the current solution, concatenating them in an attempt to reduce the error of the resulting model.
Miranda, Luis F., Oliveira, Luiz Otavio V.B., Otero, Fernando E.B., Pappa, Gisele L.   +3 more
core   +1 more source

Basroparib inhibits YAP‐driven cancers by stabilizing angiomotin

Molecular Oncology, EarlyView.
Basroparib, a selective tankyrase inhibitor, suppresses Wnt signaling and attenuates YAP‐driven oncogenic programs by stabilizing angiomotin. It promotes AMOT–YAP complex formation, enforces cytoplasmic YAP sequestration, inhibits YAP/TEAD transcription, and sensitizes YAP‐active cancers, including KRAS‐mutant colorectal cancer, to MEK inhibition.
Young‐Ju Kwon, Dong Young Kim, Yuna Kim, Uk‐Il Kim, Jae‐Sung Kim   +4 more
wiley   +1 more source

Symbolic Regression on FPGAs for Fast Machine Learning Inference [PDF]

EPJ Web of Conferences
The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to enhance physics sensitivity while still meeting data processing time constraints.
Tsoi Ho Fung, Pol Adrian Alan, Loncar Vladimir, Govorkova Ekaterina, Cranmer Miles, Dasu Sridhara, Elmer Peter, Harris Philip, Ojalvo Isobel, Pierini Maurizio   +9 more
doaj   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

Molecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns, Jaclyn S. Long, Sergio Lilla, Kelly Hodge, Marcus J. G. W. Ladds, Colin Nixon, Paula Fernández‐Palanca, Sara Zanivan, Pilar Acedo, Stephen P. Pereira, Kevin M. Ryan   +10 more
wiley   +1 more source

Prediction of Dynamical Systems by Symbolic Regression

, 2016
We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified ...
Abel, Markus, Niven, Robert K., Noack, Bernd R., Quade, Markus, Shafi, Kamran   +4 more
core   +3 more sources

Shadow symbolic execution for better testing of evolving software [PDF]

, 2014
In this idea paper, we propose a novel way for improving the testing of program changes via symbolic execution. At a high-level, our technique runs two different program versions in the same symbolic execution instance, with the old version effectively ...
Cadar, C, Palikareva, H
core   +2 more sources

Taylor genetic programming for symbolic regression

Proceedings of the Genetic and Evolutionary Computation Conference, 2022
Genetic programming (GP) is a commonly used approach to solve symbolic regression (SR) problems. Compared with the machine learning or deep learning methods that depend on the pre-defined model and the training dataset for solving SR problems, GP is more focused on finding the solution in a search space.
He, Baihe, Lu, Qiang, Yang, Qingyun, Luo, Jake, Wang, Zhiguang   +4 more
openaire   +2 more sources

The cooperative regulation of miR‐221 by APE1 and AUF1 impacts p27Kip1 defining a miR signature relevant for cervical cancer

FEBS Open Bio, EarlyView.
A regulatory axis involving APE1, AUF1, and miR‐221 is proposed. Pri‐miR‐221 is processed by DROSHA and DICER to generate mature miR‐221, which targets p27Kip1 mRNA. APE1 and AUF1 compete for pre‐miR‐221 binding. Reduced APE1/AUF1 levels impair miR‐221 biogenesis, decrease p27Kip1 mRNA degradation, and promote cell cycle progression, chemoresistance ...
Matilde Clarissa Malfatti, Nicolò Gualandi, Gianluca Tell, Giulia Antoniali   +3 more
wiley   +1 more source

Reinforcement Learning-Based Symbolic Regression for Load Modeling

IEEE Open Access Journal of Power and Energy
With the growing demand variability and evolving grid control strategies, accurate and efficient load modeling has become a critical yet challenging task.
Ding Lin, Han GUO, Jianhui Wang, Meng Yue, Tianqiao Zhao   +4 more
doaj   +1 more source