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Genetic Algorithm Against Cancer [chapter]

F. Pappalardo, E. Mastriani, P. -L. Lollini, S. Motta
2006 Lecture Notes in Computer Science  
Our genetic algorithm found complete immunoprevention with a much lighter vaccination schedule. The number of injections required is roughly one third of those used in Chronic schedule.  ...  Our study is based on our previous model that simulates the Cancer -Immune System competition activated by a tumor vaccine.  ...  Cancer cells controlled by genetic algorithm proposed vaccination schedules. Red ticks above x axis represent the timing of vaccine administration.  ... 
doi:10.1007/11676935_27 fatcat:5pr3vpkhbvfnbhp4jfp7s3nojq

Validation of Version 3.0 of the Breast Cancer Genetics Referral Screening Tool (B-RST™)

Cecelia Bellcross, April Hermstad, Christine Tallo, Christine Stanislaw
2018 Genetics in Medicine  
Results: Algorithmic changes made to B-RST™ 2.0 increased the sensitivity against BRCA1/2 mutation analysis from 71.1 to 94.0% (P < 0.0001).  ...  The Breast Cancer Genetics Referral Screening Tool (B-RST™) was created and validated to easily identify individuals at increased risk for hereditary breast and ovarian cancer for referral to cancer genetics  ...  ACKNOWLEDGEMENTS This work was funded in part by a grant from the Brenda Nease Breast Cancer Research Fund, Glenn Family Breast Center, Winship Cancer Institute of Emory University.  ... 
doi:10.1038/s41436-018-0020-x pmid:29740170 fatcat:ikql2ggdz5b2penlvvcpv2rfiy

Discovery of cancer vaccination protocols with a genetic algorithm driving an agent based simulator

Pier-Luigi Lollini, Santo Motta, Francesco Pappalardo
2006 BMC Bioinformatics  
A possible solution to the former open question using a minimal search strategy based on a genetic algorithm is presented.  ...  We are currently setting up experiments in mice to test whether the actual effectiveness of the vaccination protocol agrees with the genetic algorithm.  ...  Acknowledgements PLL acknowledges financial support from the University of Bologna, the Department of Experimental Pathology ("Pallotti" fund), MIUR and the Italian Association for Cancer Research (AIRC  ... 
doi:10.1186/1471-2105-7-352 pmid:16857043 pmcid:PMC1557867 fatcat:a3yddzbfojdjxgdzgwm6vvc6by

Machine learning tools can now help with improving Taxol production in plant cell cultures

Ranjana Sarma, Biotechnology Kiosk
2021 Biotechnology Kiosk  
breast cancer, lung cancer, Kaposi sarcoma, cervical cancer, and pancreatic cancer).  ...  Due to its ability to inhibit microtubule formation in cells, PTX is effective at all stages of the cancer and is FDA approved for treatment of many types of cancer (ovarian cancer, esophageal cancer,  ...  Problems requiring optimization, can be solved using searchbased algorithms, like genetic algorithms (GAs) [5] .  ... 
doi:10.37756/bk.21.3.3.2 fatcat:2p26hakjlrdg5nrtduonyq3epq

PERSONALIZED CALCULATOR FOR PREDICTION OF OPIOID-ASSOCIATED PHARMACORESISTANCE IN PATIENTS WITH PANCREASE CANCER

Olga Bobrova, Sergey Zyryanov, Natalia Shnayder, Marina Petrova
2020 Archiv Euromedica  
We studied the complex effect of genetic and non-genetic factors on the formation of opioid-associated resistance using machine learning methods in patients with chronic pain syndrome against the background  ...  of pancreatic cancer.  ...  Fig. 2 . 2 Clinical and genetic risk meter for the implementation of fentanylassociated opioid resistance in patients with pancreatic cancer  ... 
doi:10.35630/2199-885x/2020/10/4.3 fatcat:qo3ilnvt5jdwtgfms6c55ws7hu

Evolutionary sequential genetic search technique-based cancer classification using fuzzy rough nearest neighbour classifier

Loganathan Meenachi, Srinivasan Ramakrishnan
2018 Healthcare technology letters  
Hence, the FRNN is applied for performance analysis of existing feature selection algorithms against the proposed GSFR feature selection algorithm.  ...  In this Letter, the authors propose a genetic search fuzzy rough (GSFR) feature selection algorithm, which is hybridised using the evolutionary sequential genetic search technique and fuzzy rough set to  ...  Evolutionary sequential genetic search algorithm: A genetic algorithm is a random evolutionary search technique used to find out vector x (string).  ... 
doi:10.1049/htl.2018.5041 pmid:30155265 pmcid:PMC6103784 fatcat:suq64cg6izdxzaeaqxg33luwbq

39PClinical interpretation of lung cancer molecular profiles using rule-based artificial intelligence

D Tihanyi, C Hegedüs, E Várkondi, R Schwab, I Vályi-Nagy, I Peták, L Urbán
2018 Annals of Oncology  
Conclusions: Molecular treatment calculator algorithm is an efficient tool to classify tumor genetic variants and link them to molecular targets and drugs based on the curated, continuously expanding evidence  ...  Here, we present the analysis of 704 lung cancer profiles using our proprietary algorithm and the personalized treatment protocols established by the rule-based artificial intelligence software, the RealTime  ...  Conclusions: Malignant but not benign thyroid neoplasms may trigger specific autoantibody response against cyclin D1.  ... 
doi:10.1093/annonc/mdy318.020 pmid:32177589 fatcat:3od4itra2beudftflta4hsozw4

A Simple Genetic Algorithm for Biomarker Mining [chapter]

Dusan Popovic, Alejandro Sifrim, Georgios A. Pavlopoulos, Yves Moreau, Bart De Moor
2012 Lecture Notes in Computer Science  
We present a method for prognostics biomarker mining based on a genetic algorithm with a novel fitness function and a bagging-like model averaging scheme.  ...  The obtained results correspond to the top published performances of gene signatures developed specially for the colon cancer case.  ...  They also compared it against a simple wrapper method based on genetic algorithm. However, both described approaches assume a fixed number of features.  ... 
doi:10.1007/978-3-642-34123-6_20 fatcat:7x7x7aniljbh7oab76sw5k5ziu

Classification of Cancer Model for Clinically Actionable Genetic Mutations Using Machine Learning

2020 Medico-Legal Update  
Classification of Cancer Model Clinically Actionable Genetic Mutations Using Machine Learning Algorithms. Its task is to classify genes based on text evidence from clinical issues with good results.  ...  Clinical pathologist has the data's of cancer attacked before and he will collect the gene sample and the person blood sample and predict which type of virus of cancer will attack to the person.  ...  Component extraction against classified Data: It is constructed for extracting the numerous classification algorithms already mentioned above.  ... 
doi:10.37506/mlu.v20i4.1763 fatcat:remc6vj5jng2nhjmp4b6x34f5i

QSAR study of antiproliferative drug against A549 by GA-MLR and SW-MLR methods

Somayeh Alimohammadi, Aliasghar Hamidi, Parinaz Pargolghasemi, Nasim Nourani, Mir Saleh Hoseininezhad-Namin
2019 Chemical review and letters  
For this purpose, we used the multiple linear regressions (MLR) for the construction of a model to predict drug activity and Stepwise (SW) and genetic algorithm (GA) methods used to build the model.  ...  The results obtained in this study can be used to design drugs with higher performance and pharmacological activity to treat lung cancer.  ...  Genetic algorithm-multiple linear regression method In this step for choose the best descriptors with highest associated to pIC50 used genetic algorithm as a subset based on MLR method.  ... 
doi:10.22034/crl.2020.220465.1037 doaj:07c7868dd3614aebba72ec94a54b3d26 fatcat:cjsvibteive5zoibz4zfjjlq5a

Neuroevolution based multi-objective algorithm for gene selection and microarray classification

Daniel García-Núñez, Katya Rodriguez-Vázquez, Carlos Hernández
2022 Proceedings of the Genetic and Evolutionary Computation Conference Companion  
The algorithm is based on the evolutionary multi-objective algorithm SMS-EMOA along with the genetic encoding and the crossover and mutation operators from the neuroevolution algorithms NEAT/N3O.  ...  The algorithm performance was measured by the geometric mean, the number of selected features, and the population hypervolume, and it was compared against N3O on microarray binary classification problems  ...  CONCLUSIONS SMS-MONEAT demonstrated competitive performance against N3O for gene selection and binary classification of cancer microarray datasets.  ... 
doi:10.1145/3520304.3529058 fatcat:asvafy6lobcfhmlw7v7txlkzlm

P1-64 Novel genetic risk variants for breast cancer: from discovery to disease prevention

W. Zheng
2011 Journal of Epidemiology and Community Health  
expert clinical judgement, followed by validation against case note review (n¼1058). Results The algorithm developed had sensitivity 74% (95% CI 69% to 78%) and estimated specificity was 94%.  ...  Applied to all Scottish hospital activity data for 2005 (n¼883 K), the algorithm gave an estimate of annual incidence of severe sepsis (2.7%) and case mortality (34%).  ...  In 2008 we established the Asia Breast Cancer Consortium to search for genetic risk variants for breast cancer.  ... 
doi:10.1136/jech.2011.142976c.57 fatcat:pbzgun5pijfrbfxbcr77t7wuka

P1-63 Estimating fraction cured from cancer: which statistical package to use?

X. Q. Yu, M. Clements, D. O'Connell
2011 Journal of Epidemiology and Community Health  
expert clinical judgement, followed by validation against case note review (n¼1058). Results The algorithm developed had sensitivity 74% (95% CI 69% to 78%) and estimated specificity was 94%.  ...  Applied to all Scottish hospital activity data for 2005 (n¼883 K), the algorithm gave an estimate of annual incidence of severe sepsis (2.7%) and case mortality (34%).  ...  In 2008 we established the Asia Breast Cancer Consortium to search for genetic risk variants for breast cancer.  ... 
doi:10.1136/jech.2011.142976c.56 fatcat:5e6b27ffnjb3vgdab2drpltfki

Predicting cancer risk based on family history

Michelle F Jacobs
2021 eLife  
A new software package provides more accurate cancer risk prediction profiles and has the ability to integrate more genes and cancer types in the future.  ...  This complicates risk assessments and argues against making decisions about genetic testing solely based on risk prediction models.  ...  In rarer cases (about 5-10%), they start due to inherited genetic mutations that produce a predisposition to cancer.  ... 
doi:10.7554/elife.73380 pmid:34586069 fatcat:gxi2bwzyovh2lfwgv4zbkac2ge

P1-62 The virtual committee: a practical process for maintaining high quality content of online learning resources for public health practice in Canada

E. Wright, H. Robinson, J. Rossiter
2011 Journal of Epidemiology and Community Health  
expert clinical judgement, followed by validation against case note review (n¼1058). Results The algorithm developed had sensitivity 74% (95% CI 69% to 78%) and estimated specificity was 94%.  ...  Applied to all Scottish hospital activity data for 2005 (n¼883 K), the algorithm gave an estimate of annual incidence of severe sepsis (2.7%) and case mortality (34%).  ...  In 2008 we established the Asia Breast Cancer Consortium to search for genetic risk variants for breast cancer.  ... 
doi:10.1136/jech.2011.142976c.55 fatcat:ni3n4k3xqjcixdmnd4hdon4tey
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