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Related papers: Optimization Aspects of Carcinogenesis

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A tumor often consists of multiple cell subpopulations (clones). Current chemo-treatments often target one clone of a tumor. Although the drug kills that clone, other clones overtake it and the tumor reoccurs. Genome sequencing and…

Molecular Networks · Quantitative Biology 2014-09-09 Edwin Wang , Jinfeng Zou , Naif Zaman , Lenore K. Beitel , Mark Trifiro , Miltiadis Paliouras

Traditionally evolution is seen as a process where from a pool of possible variations of a population (e.g. biological species or industrial goods) a few variations get selected which survive and proliferate, whereas the others vanish.…

Populations and Evolution · Quantitative Biology 2008-09-25 Rudolf Hanel , Stefan Thurner

Death has long been overlooked in evolutionary algorithms. Recent research has shown that death (when applied properly) can benefit the overall fitness of a population and can outperform sub-sections of a population that are "immortal" when…

Neural and Evolutionary Computing · Computer Science 2021-09-29 Micah Burkhardt , Roman V. Yampolskiy

Chemotherapy is one of the primary modalities of cancer treatment. Chemotherapy drug administration is a complex problem that often requires expensive clinical trials to evaluate potential regimens. One way to alleviate this burden and…

Optimization and Control · Mathematics 2021-11-04 Temitayo Ajayi , Seyedmohammadhossein Hosseinian , Andrew J. Schaefer , Clifton D. Fuller

One of many important features of the tumour microenvironment is that it is a place of active Darwinian selection where different tumour clones become adapted to the variety of ecological niches that make up the microenvironment. These…

Biological Physics · Physics 2019-06-07 Thierry Fredrich , Heiko Rieger , Roberto Chignola , Edoardo Milotti

Biological information processing manifests a huge variety in its complexity and capability among different organisms, which presumably stems from the evolutionary optimization under limited computational resources. Starting from the…

Biological Physics · Physics 2025-10-21 Takehiro Tottori , Tetsuya J. Kobayashi

Bayesian optimization is a methodology to optimize black-box functions. Traditionally, it focuses on the setting where you can arbitrarily query the search space. However, many real-life problems do not offer this flexibility; in…

We present a powerful general framework for designing data-dependent optimization algorithms, building upon and unifying recent techniques in adaptive regularization, optimistic gradient predictions, and problem-dependent randomization. We…

Machine Learning · Statistics 2015-10-14 Mehryar Mohri , Scott Yang

Evolutionary algorithms have been successfully applied to a variety of optimisation problems in stationary environments. However, many real world optimisation problems are set in dynamic environments where the success criteria shifts…

Neural and Evolutionary Computing · Computer Science 2016-10-11 Matthew Hughes

Cancer has been characterized as a constellation of hundreds of diseases differing in underlying mutations and depending on cellular environments. Carcinogenesis as a stochastic physical process has been studied for over sixty years, but…

Tissues and Organs · Quantitative Biology 2015-06-02 Carson C. Chow , Yanjun Li , Vipul Periwal

Theoretical reasoning suggests that human cancer may result from knocking down the genetic constraints evolved for maintenance of the metazoan multicellularity, which, however, requires a critical test. Using xenograft-based experimental…

Genomics · Quantitative Biology 2016-02-17 Han Chen , Fangqin Lin , Xionglei He

Many real-world optimization problems occur in environments that change dynamically or involve stochastic components. Evolutionary algorithms and other bio-inspired algorithms have been widely applied to dynamic and stochastic problems.…

Neural and Evolutionary Computing · Computer Science 2020-01-30 Vahid Roostapour , Mojgan Pourhassan , Frank Neumann

Translation of proteins is a fundamental part of gene expression that is mediated by ribosomes. As ribosomes significantly contribute to both cellular mass and energy consumption, achieving efficient management of the ribosome population is…

Subcellular Processes · Quantitative Biology 2024-04-18 Clément Soubrier , Eric Foxall , Luca Ciandrini , Khanh Dao Duc

Nonlinear constrained optimization problems are encountered in many scientific fields. To utilize the huge calculation power of current computers, many mathematic models are also rebuilt as optimization problems. Most of them have…

Optimization and Control · Mathematics 2011-10-03 Wei Zhang , Xudong Shi , Liwen Wang

We propose and analyse a variant of the recently introduced kinetic based optimization method that incorporates ideas like survival-of-the-fittest and mutation strategies well-known from genetic algorithms. Thus, we provide a first attempt…

Optimization and Control · Mathematics 2024-07-18 Giacomo Albi , Federica Ferrarese , Claudia Totzeck

Population-based evolutionary algorithms have great potential to handle multiobjective optimisation problems. However, these algorithms depends largely on problem characteristics, and there is a need to improve their performance for a wider…

Neural and Evolutionary Computing · Computer Science 2019-10-17 Shouyong Jiang , Hongru Li , Jinglei Guo , Mingjun Zhong , Shengxiang Yang , Marcus Kaiser , Natalio Krasnogor

A punctuated equilibrium model of biological evolution with relative fitness between different species being the fundamental driving force of evolution is introduced. Mutation is modeled as a fitness updating cellular automaton process…

Condensed Matter · Physics 2015-06-25 H. F. Chau , L. Mak , P. K. Kwok

Development of resistance limits transferability of most anticancer therapies into curative treatment and understanding mechanisms beyond it remains a big challenge. Many high resolution experimental observations show enormous intratumor…

Populations and Evolution · Quantitative Biology 2013-07-03 B. Brutovsky , D. Horvath

Cancer is most commonly viewed as resulting from somatic mutations enhancing proliferation and invasion. Some hypotheses further propose that these new capacities reveal a breakdown of multicellularity allowing cancer cells to escape…

Populations and Evolution · Quantitative Biology 2024-11-27 Bertrand Daignan-Fornier , Thomas Pradeu

This manuscript portrays optimization as a process. In many practical applications the environment is so complex that it is infeasible to lay out a comprehensive theoretical model and use classical algorithmic theory and mathematical…

Machine Learning · Computer Science 2023-08-08 Elad Hazan
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