Neural network-based multiomics data integration in Alzheimer's disease

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Singhal:2019:GECCOcomp,

• author = "Pankhuri Singhal and Shefali S. Verma and Scott M. Dudek and Marylyn D. Ritchie",
• title = "Neural network-based multiomics data integration in {Alzheimer's} disease",
• booktitle = "GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion",
• year = "2019",
• editor = "Richard Allmendinger and Carlos Cotta and Carola Doerr and Pietro S. Oliveto and Thomas Weise and Ales Zamuda and Anne Auger and Dimo Brockhoff and Nikolaus Hansen and Tea Tusar and Konstantinos Varelas and David Camacho-Fernandez and Massimiliano Vasile and Annalisa Riccardi and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Ozgur Akman and Khulood Alyahya and Juergen Branke and Jonathan Fieldsend and Tinkle Chugh and Jussi Hakanen and Josu {Ceberio Uribe} and Valentino Santucci and Marco Baioletti and John McCall and Emma Hart and Daniel R. Tauritz and John R. Woodward and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Eneko Osaba and Javier {Del Ser} and Pascal Kerschke and Boris Naujoks and Vanessa Volz and Anna I Esparcia-Alcazar and Riyad Alshammari and Erik Hemberg and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and Silvino {Fernandez Alzueta} and Pablo {Valledor Pellicer} and Thomas Stuetzle and David Walker and Matt Johns and Nick Ross and Ed Keedwell and Masaya Nakata and Anthony Stein and Takato Tatsumi and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen Smith and Stefano Cagnoni and Robert M. Patton and William {La Cava} and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Marcus Gallagher and Mike Preuss and Olivier Teytaud and Fernando Lezama and Joao Soares and Zita Vale",
• isbn13 = "978-1-4503-6748-6",
• pages = "403--404",
• address = "Prague, Czech Republic",
• DOI = "doi:10.1145/3319619.3321920",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• month = "13-17 " # jul,
• organisation = "SIGEVO",
• keywords = "genetic algorithms, genetic programming",
• abstract = "Alzheimer's Disease (AD) is a growing pandemic affecting over 50 million individuals worldwide. While individual molecular traits have been found to be associated with AD at the DNA, RNA, protein, and epigenetic level, the underlying genetic etiology of AD remains unknown. Integrating multiple omics data types simultaneously has the potential to reveal interactions within and between these molecular features. In order to identify disease driving mechanism, a standardized framework for integrating multiomics data is needed. Due to high variability in size, structure, and availability of high-throughput omics data, there is currently no gold standard for combining different data types together in a biologically meaningful way. Thus, we propose a pathway-centric, neural network-based framework to integrate multiomics AD data. In this knowledge-driven approach, we evaluate different gene ontologies to map data to the pathway level. Preliminary results show integrating multiple datatypes under this framework produces more robust AD pathway models compared to models from single data types alone.",
• notes = "Also known as \cite{3321920} GECCO-2019 A Recombination of the 28th International Conference on Genetic Algorithms (ICGA) and the 24th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Pankhuri Singhal Shefali S Verma Scott M Dudek Marylyn D Ritchie

Citations