Results 61 to 70 of about 150,984 (329)
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
Universal Approach to Solution of Optimization Problems by Symbolic Regression
Optimization problems and their solution by symbolic regression methods are considered. The search is performed on non-Euclidean space. In such spaces it is impossible to determine a distance between two potential solutions and, therefore, algorithms ...
Elena Sofronova, Askhat Diveev
doaj +1 more source
Traditional Linear Genetic Programming (LGP) algorithms are based only on the selection mechanism to guide the search. Genetic operators combine or mutate random portions of the individuals, without knowing if the result will lead to a fitter individual.
Bosman P. A. N. +5 more
core +1 more source
Symbolic Maximum Likelihood Estimation with Mathematica [PDF]
Mathematica is a symbolic programming language that empowers the user to undertake complicated algebraic tasks. One such task is the derivation of maximum likelihood estimators, demonstrably an important topic in statistics at both the research and ...
Rose, Colin, Smith, Murray D.
core +2 more sources
Discovery and Targeted Proteomic Studies Reveal Striatal Markers Validated for Huntington's Disease
ABSTRACT Objective Clinical trials for Huntington's disease (HD) enrolling persons before clinical motor diagnosis (CMD) lack validated biomarkers. This study aimed to conduct an unbiased discovery analysis and a targeted examination of proteomic biomarkers scrutinized by clinical validation. Methods Cerebrospinal fluid was obtained from PREDICT‐HD and
Daniel Chelsky +8 more
wiley +1 more source
SymFormer: End-to-End Symbolic Regression Using Transformer-Based Architecture
Many real-world systems can be naturally described by mathematical formulas. The task of automatically constructing formulas to fit observed data is called symbolic regression.
Martin Vastl +4 more
doaj +1 more source
Modeling of Tunneling Total Loads Based on Symbolic Regression Algorithm
The tunneling total load is one of the core control parameters for safe and efficient construction using tunneling machines. However, because the tunneling process involves complex coupling relationships between the equipment and the local geology ...
Liting Zhang +3 more
doaj +1 more source
Accurate and efficient explicit approximations of the Colebrook flow friction equation based on the Wright omega-function [PDF]
The Colebrook equation is a popular model for estimating friction loss coefficients in water and gas pipes. The model is implicit in the unknown flow friction factor, f. To date, the captured flow friction factor, f, can be extracted from the logarithmic
Brkić, Dejan, Praks, Pavel
core +8 more sources
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
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
Symbolic Regression Approaches for the Direct Calculation of Pipe Diameter
This study provides novel and accurate symbolic regression-based solutions for the calculation of pipe diameter when flow rate and pressure drop (head loss) are known, together with the length of the pipe, absolute inner roughness of the pipe, and ...
Dejan Brkić +3 more
doaj +1 more source

