Results 31 to 40 of about 13,019 (261)

The ubiquitin ligase RNF115 is required for the clearance of damaged lysosomes

open access: yesFEBS Letters, EarlyView.
Upon lysosomal rupture, an E3 ubiquitin ligase RNF115 translocates from the cytosol to the damaged lysosomal membrane. Moreover, RNF115 depletion impairs the clearance of damaged lysosomes, identifying it as a key regulator of lysosomal quality control.
Sae Nakanaga   +3 more
wiley   +1 more source

Patient therapy outcome modeling in cancer organoids is improved by cancer‐associated fibroblasts and organoid assembly convolution

open access: yesMolecular Oncology, EarlyView.
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski   +12 more
wiley   +1 more source

The Application of Symbolic Regression on Identifying Implied Volatility Surface

open access: yesMathematics, 2023
One important parameter in the Black–Scholes option pricing model is the implied volatility. Implied volatility surface (IVS) is an important concept in finance that describes the variation of implied volatility across option strike price and time to ...
Jiayi Luo, Cindy Long Yu
doaj   +1 more source

Pharmacological inhibition of the PERK pathway modulates hepatocellular carcinoma growth and immune signaling

open access: yesFEBS Open Bio, EarlyView.
Pharmacological inhibition of PERK in a DEN‐induced mouse model of liver cancer does not reduce tumor burden but alters cellular stress signaling. Despite blocking PERK activity, downstream stress responses, including CHOP expression, remain active, suggesting compensatory mechanisms within the unfolded protein response that may influence tumor ...
Ada Lerma‐Clavero   +5 more
wiley   +1 more source

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

open access: yesEPJ 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   +9 more
doaj   +1 more source

Hyperosmotic stress‐induced redistribution of pre‐mRNA cleavage factor I subunits is associated with shifts in alternative polyadenylation

open access: yesFEBS Open Bio, EarlyView.
Hyperosmotic stress triggers the relocation of the CFIm complex from the nucleus to the cytoplasm. This shift creates a nuclear ‘stoichiometric bottleneck’, limiting CFIm availability for mRNA processing. Consequently, specific mRNAs like NUDT21 and DICER1 undergo targeted 3′UTR shortening, demonstrating how spatial protein dynamics drive rapid ...
Hitomi Soumiya   +2 more
wiley   +1 more source

Selecting Informative Data Samples for Model Learning Through Symbolic Regression

open access: yesIEEE Access, 2021
Continual model learning for nonlinear dynamic systems, such as autonomous robots, presents several challenges. First, it tends to be computationally expensive as the amount of data collected by the robot quickly grows in time. Second, the model accuracy
Erik Derner   +2 more
doaj   +1 more source

Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito   +14 more
wiley   +1 more source

Reinforcement Learning-Based Symbolic Regression for Load Modeling

open access: yesIEEE 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   +4 more
doaj   +1 more source

Taylor genetic programming for symbolic regression

open access: yesProceedings 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.
Baihe He   +4 more
openaire   +2 more sources

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