Results 81 to 90 of about 1,503,716 (266)
Molecular Oncology, EarlyView.HDAC4 is degraded by the E3 ligase FBXW7. In colorectal cancer, FBXW7 mutations prevent HDAC4 degradation, leading to oxaliplatin resistance. Forced degradation of HDAC4 using a PROTAC compound restores drug sensitivity by resetting the super‐enhancer landscape, reprogramming the epigenetic state of FBXW7‐mutated cells to resemble oxaliplatin ...
Vanessa Tolotto +13 more
wiley +1 more source
A Hierarchical Sorting Swarm Optimizer for Large-Scale Optimization
IEEE Access, 2019 Large-scale optimization is a challenging problem because it involves a large number of decision variables. In this paper, a simple but effective method, called hierarchical sorting swarm optimizer (HSSO), is proposed for large-scale optimization.
Rushi Lan +4 more
doaj +1 more source
Large‐scale elasto‐plastic topology optimization
International Journal for Numerical Methods in EngineeringAbstractThis work presents large‐scale elasto‐plastic topology optimization for design of structures with maximized energy absorption and tailored mechanical response. The implementation uses parallel computations to address multi million element three‐dimensional problems.
Gunnar Granlund, Mathias Wallin
openaire +1 more source
Molecular Oncology, EarlyView.Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source
Large-scale wireless coverage optimization: A quantum approach
ICT ExpressWireless network coverage optimization is critical for improving service quality. However, optimizing large-scale networks remains challenging for both classical algorithms and quantum methods in the NISQ era.
Chengkang Pan +7 more
doaj +1 more source
A New Chaotic-Based Approach for Multi-Objective Optimization
Algorithms, 2020 Multi-objective optimization problems (MOPs) have been widely studied during the last decades. In this paper, we present a new approach based on Chaotic search to solve MOPs. Various Tchebychev scalarization strategies have been investigated. Moreover, a
Nassime Aslimani +2 more
doaj +1 more source
Molecular Oncology, EarlyView.Generation of two normal and tumour (cancerous) paired human cell lines using an established tissue culture technique and their characterisation is described. Cell lines were characterised at cellular, protein, chromosome and gene expression levels and for HPV status.
Simon Broad +12 more
wiley +1 more source
The cheetah optimizer: a nature-inspired metaheuristic algorithm for large-scale optimization problems. [PDF]
Sci Rep, 2022 Akbari MA +4 more
europepmc +1 more source
An optimal subgradient algorithm for large-scale convex optimization in simple domains [PDF]
, 2015 This paper shows that the optimal subgradient algorithm, OSGA, proposed in \cite{NeuO} can be used for solving structured large-scale convex constrained optimization problems.
Ahookhosh, Masoud, Neumaier, Arnold
core +1 more source
Next‐generation proteomics improves lung cancer risk prediction
Molecular Oncology, EarlyView.This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj +4 more
wiley +1 more source