Results 81 to 90 of about 174,883 (339)

Computational Complexity Analysis of Simple Genetic Programming On Two Problems Modeling Isolated Program Semantics [PDF]

arXiv, 2010
Analyzing the computational complexity of evolutionary algorithms for binary search spaces has significantly increased their theoretical understanding. With this paper, we start the computational complexity analysis of genetic programming. We set up several simplified genetic programming algorithms and analyze them on two separable model problems ...
arxiv  

Circulating tumor cells in metastatic breast cancer patients treated with immune checkpoint inhibitors – a biomarker analysis of the ALICE and ICON trials

Molecular Oncology, EarlyView.
In this explorative biomarker analysis, we assessed serial sampling of circulating tumor cells (CTCs) with CellSearch in two randomized trials testing immune checkpoint inhibitors (ICIs) in metastatic breast cancer. Our data demonstrate a prognostic potential of CTCs, most apparent 4 weeks into ICI therapy.
Nikolai Kragøe Andresen, Andreas Hagen Røssevold, Elin Borgen, Cecilie Bendigtsen Schirmer, Bjørnar Gilje, Øystein Garred, Jon Lømo, Marius Stensland, Oddmund Nordgård, Ragnhild Sørum Falk, Randi R. Mathiesen, Hege G. Russnes, Jon Amund Kyte, Bjørn Naume   +13 more
wiley   +1 more source

A genetic programming ecosystem [PDF]

Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001, 2005
Algorithms are needed in every aspect of parallel computing. Genetic Programming is an evolutionary technique for automating the design of algorithms through iterative steps of mutation and crossover operations on an initial population of randomly generated computer programs.
Martial Michel, O. Nicolas, A. Samson, J E. Devaney, G. Garg, J. Hagedorn   +5 more
openaire   +2 more sources

Circulating tumor cells: advancing personalized therapy in small cell lung cancer patients

Molecular Oncology, EarlyView.
Small cell lung cancer (SCLC) is an aggressive form of lung cancer that spreads rapidly to secondary sites such as the brain and liver. Cancer cells circulating in the blood, “circulating tumor cells” (CTCs), have demonstrated prognostic value in SCLC, and evaluating biomarkers on CTCs could guide treatment decisions such as for PARP inhibitors ...
Prajwol Shrestha, Steven Kao, Veronica K. Cheung, Wendy A. Cooper, Nico van Zandwijk, John E. J. Rasko, Dannel Yeo   +6 more
wiley   +1 more source

Positional Cartesian Genetic Programming [PDF]

arXiv, 2018
Cartesian Genetic Programming (CGP) has many modifications across a variety of implementations, such as recursive connections and node weights. Alternative genetic operators have also been proposed for CGP, but have not been fully studied. In this work, we present a new form of genetic programming based on a floating point representation.
arxiv  

Obtaining Basic Algebra Formulas with Genetic Programming and Functional Rewriting [PDF]

arXiv, 2020
In this paper, we develop a set of genetic programming operators and an initialization population process based on concepts of functional programming rewriting for boosting inductive genetic programming. Such genetic operators are used within a hybrid adaptive evolutionary algorithm that evolves operator rates at the same time it evolves the solution ...
arxiv  

Cell‐free and extracellular vesicle microRNAs with clinical utility for solid tumors

Molecular Oncology, EarlyView.
Cell‐free microRNAs (cfmiRs) are small‐RNA circulating molecules detectable in almost all body biofluids. Innovative technologies have improved the application of cfmiRs to oncology, with a focus on clinical needs for different solid tumors, but with emphasis on diagnosis, prognosis, cancer recurrence, as well as treatment monitoring.
Yoshinori Hayashi, Janelle‐Cheri Millen, Romela Irene Ramos, Jennifer A. Linehan, Timothy G. Wilson, Dave S. B. Hoon, Matias A. Bustos   +6 more
wiley   +1 more source

Towards Advanced Phenotypic Mutations in Cartesian Genetic Programming [PDF]

arXiv, 2018
Cartesian Genetic Programming is often used with a point mutation as the sole genetic operator. In this paper, we propose two phenotypic mutation techniques and take a step towards advanced phenotypic mutations in Cartesian Genetic Programming. The functionality of the proposed mutations is inspired by biological evolution which mutates DNA sequences ...
arxiv  

KRAS and GNAS mutations in cell‐free DNA and in circulating epithelial cells in patients with intraductal papillary mucinous neoplasms—an observational pilot study

Molecular Oncology, EarlyView.
This study demonstrates that KRAS and GNAS mutations are more prevalent in patients with resected intraductal papillary mucinous neoplasms (IPMN) compared to those under clinical surveillance. GNAS mutations significantly differ between the two patient cohorts, indicating that their absence may serve as a potential biomarker to support conservative ...
Christine Nitschke, Marie Tölle, Philipp Walter, Kira Meißner, Mara Goetz, Jolanthe Kropidlowski, Andreas W. Berger, Jakob R. Izbicki, Felix Nickel, Thilo Hackert, Klaus Pantel, Harriet Wikman, Faik G. Uzunoglu   +12 more
wiley   +1 more source

Scaling Genetic Programming for Source Code Modification [PDF]

arXiv, 2012
In Search Based Software Engineering, Genetic Programming has been used for bug fixing, performance improvement and parallelisation of programs through the modification of source code. Where an evolutionary computation algorithm, such as Genetic Programming, is to be applied to similar code manipulation tasks, the complexity and size of source code for
arxiv