Genetic Programming Bibliography entries for Marylyn D Ritchie

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GP coauthors/coeditors: William S Bush, Alison A Motsinger, Scott M Dudek, Nicholas E Hardison, Theresa J Fanelli, David M Reif, Emily Rose Holzinger, Carrie C Buchanan, Eric C Torstenson, Stephen D Turner, Alex T Frase, Brooke L Fridley, Prabhakar Chalise, Dokyoon Kim, Ruowang Li, Sarah A Pendergrass, Natalio Krasnogor, Pier Luca Lanzi, Andries P Engelbrecht, David A Pelta, Carlos Gershenson, Giovanni Squillero, Alex Alves Freitas, Mike Preuss, Christian Gagne, Yew-Soon Ong, Gunther R Raidl, Marcus Gallager, Jose A Lozano, Carlos Artemio Coello Coello, Dario Landa-Silva, Nikolaus Hansen, Silja Meyer-Nieberg, James Smith, Gusz Eiben, Ester Bernado-Mansilla, Will N Browne, Lee Spector, Tina Yu, Jeff Clune, Gregory S Hornby, Man Leung Wong, Pierre Collet, Steven M Gustafson, Jean-Paul Watson, Moshe Sipper, Simon M Poulding, Gabriela Ochoa, Marc Schoenauer, Carsten Witt, Anne Auger, Rachit Kumar, Joseph Romano, Jason H Moore, Molly A Hall, Yuki Bradford, Peggy L Peissig, Murray H Brilliant, James G Linneman, Catherine A McCarty, Le Bao, Stephen L Lee, George Mellick, Lance W Hahn, Kelli K Ryckman, Anna C Davis, Rick L Riolo, Ekaterina (Katya) Vladislavleva, Bill C White, Joel S Parker, Christopher S Coffey, Pankhuri Singhal, Shefali S Verma,

Genetic Programming Articles by Marylyn D Ritchie

  1. Ruowang Li and Scott M. Dudek and Dokyoon Kim and Molly A. Hall and Yuki Bradford and Peggy L. Peissig and Murray H. Brilliant and James G. Linneman and Catherine A. McCarty and Le Bao and Marylyn D. Ritchie. Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network. BioData Mining, 9(1):18, 2016. details

  2. Dokyoon Kim and Ruowang Li and Scott M Dudek and Alex T Frase and Sarah A Pendergrass and Marylyn D Ritchie. Knowledge-driven genomic interactions: an application in ovarian cancer. BioData Mining, 7(20) 2014. details

  3. Dokyoon Kim and Ruowang Li and Scott M. Dudek and Marylyn D. Ritchie. ATHENA: Identifying interactions between different levels of genomic data associated with cancer clinical outcomes using grammatical evolution neural network. BioData Mining, 6 2013. details

  4. Alison A Motsinger-Reif and Theresa J Fanelli and Anna C Davis and Marylyn D Ritchie. Power of grammatical evolution neural networks to detect gene-gene interactions in the presence of error. BMC Research Notes, 1(65) 2008. details

  5. Alison A Motsinger-Reif and Marylyn D Ritchie. Neural networks for genetic epidemiology: past, present, and future. BioData Mining, 1(3) 2008. details

  6. Marylyn D. Ritchie and Alison A. Motsinger and William S. Bush and Christopher S. Coffey and Jason H. Moore. Genetic programming neural networks: A powerful bioinformatics tool for human genetics. Applied Soft Computing, 7(1):471-479, 2007. details

  7. Alison A Motsinger and Stephen L Lee and George Mellick and Marylyn D Ritchie. GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease. BMC bioinformatics [electronic resource], 7(1):39-39, 2006. details

  8. Marylyn D. Ritchie and Bill C. White and Joel S. Parker and Lance W. Hahn and Jason H. Moore. Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases. BMC Bioinformatics, 4(28) 2003. details

Genetic Programming PhD doctoral thesis Marylyn D Ritchie

Genetic Programming Conference proceedings edited by Marylyn D Ritchie

Genetic Programming conference papers by Marylyn D Ritchie

  1. Rachit Kumar and Joseph Romano and Marylyn Ritchie and Jason Moore. Extending Tree-Based Automated Machine Learning to Biomedical Image and Text Data Using Custom Feature Extractors. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 599-602, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  2. Pankhuri Singhal and Shefali S. Verma and Scott M. Dudek and Marylyn D. Ritchie. Neural network-based multiomics data integration in Alzheimer's disease. In 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 editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 403-404, Prague, Czech Republic, 2019. ACM. details

  3. Emily R. Holzinger and Scott M. Dudek and Alex T. Frase and Brooke Fridley and Prabhakar Chalise and Marylyn D. Ritchie. Comparison of methods for meta-dimensional data analysis using in silico and biological data sets. In Mario Giacobini and Leonardo Vanneschi and William S. Bush editors, 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, volume 7246, pages 134-143, Malaga, Spain, 2012. Springer Verlag. details

  4. Stephen D. Turner and Scott M. Dudek and Marylyn D. Ritchie. Grammatical Evolution of Neural Networks for Discovering Epistasis among Quantitative Trait Loci. In Clara Pizzuti and Marylyn D. Ritchie and Mario Giacobini editors, 8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EvoBIO 2010), volume 6023, pages 86-97, Istanbul, Turkey, 2010. Springer. details

  5. Emily Rose Holzinger and Carrie C. Buchanan and Scott M. Dudek and Eric C. Torstenson and Stephen D. Turner and Marylyn D. Ritchie. Initialization parameter sweep in ATHENA: optimizing neural networks for detecting gene-gene interactions in the presence of small main effects. In Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano van Hemert and Leonardo Vanneschi and Carsten Witt editors, GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 203-210, Portland, Oregon, USA, 2010. ACM. details

  6. Stephen D. Turner and Marylyn D. Ritchie and William S. Bush. Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks. In Clara Pizzuti and Marylyn Ritchie editors, EvoBIO 2009, Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, volume 5483, pages 80-91, Tuebingen, Germany, 2009. Springer. details

  7. Nicholas E. Hardison and Theresa J. Fanelli and Scott M. Dudek and David M. Reif and Marylyn D. Ritchie and Alison A. Motsinger-Reif. A balanced accuracy fitness function leads to robust analysis using grammatical evolution neural networks in the case of class imbalance. In Maarten Keijzer and Giuliano Antoniol and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Nikolaus Hansen and John H. Holmes and Gregory S. Hornby and Daniel Howard and James Kennedy and Sanjeev Kumar and Fernando G. Lobo and Julian Francis Miller and Jason Moore and Frank Neumann and Martin Pelikan and Jordan Pollack and Kumara Sastry and Kenneth Stanley and Adrian Stoica and El-Ghazali Talbi and Ingo Wegener editors, GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pages 353-354, Atlanta, GA, USA, 2008. ACM. details

  8. Alison A. Motsinger and David M. Reif and Theresa J. Fanelli and Anna C. Davis and Marylyn D. Ritchie. Linkage Disequilibrium in Genetic Association Studies Improves the Performance of Grammatical Evolution Neural Networks. In IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, CIBCB '07, pages 1-8, Honolulu, HI, USA, 2007. IEEE. details

  9. Alison A. Motsinger and David M. Reif and Scott M. Dudek and Marylyn D. Ritchie. Understanding the Evolutionary Process of Grammatical Evolution Neural Networks for Feature Selection in Genetic Epidemiology. In Dan Ashlock editor, IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, CIBCB '06, pages 1-8, Toronto, Canada, 2006. IEEE. details

  10. Alison A. Motsinger and Lance W. Hahn and Scott M. Dudek and Kelli K. Ryckman and Marylyn D. Ritchie. Alternative cross-over strategies and selection techniques for grammatical evolution optimized neural networks. In Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos Coello Coello and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens editors, GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, volume 1, pages 947-948, Seattle, Washington, USA, 2006. ACM Press. details

  11. William S. Bush and Alison A. Motsinger and Scott M. Dudek and Marylyn D. Ritchie. Can neural network constraints in GP provide power to detect genes associated with human disease?. In Franz Rothlauf and Juergen Branke and Stefano Cagnoni and David W. Corne and Rolf Drechsler and Yaochu Jin and Penousal Machado and Elena Marchiori and Juan Romero and George D. Smith and Giovanni Squillero editors, Applications of Evolutionary Computing, EvoWorkshops2005: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, EvoSTOC, volume 3449, pages 44-53, Lausanne, Switzerland, 2005. Springer Verlag. details

  12. Marylyn D. Ritchie and Christopher S. Coffey and Jason H. Moore. Genetic Programming Neural Networks as a Bioinformatics Tool for Human Genetics. In Kalyanmoy Deb and Riccardo Poli and Wolfgang Banzhaf and Hans-Georg Beyer and Edmund Burke and Paul Darwen and Dipankar Dasgupta and Dario Floreano and James Foster and Mark Harman and Owen Holland and Pier Luca Lanzi and Lee Spector and Andrea Tettamanzi and Dirk Thierens and Andy Tyrrell editors, Genetic and Evolutionary Computation -- GECCO-2004, Part I, volume 3102, pages 438-448, Seattle, WA, USA, 2004. Springer-Verlag. details

  13. Marylyn D. Ritchie. Model Validation in Biological Applications of Evolutionary Computation. In R. Poli and S. Cagnoni and M. Keijzer and E. Costa and F. Pereira and G. Raidl and S. C. Upton and D. Goldberg and H. Lipson and E. de Jong and J. Koza and H. Suzuki and H. Sawai and I. Parmee and M. Pelikan and K. Sastry and D. Thierens and W. Stolzmann and P. L. Lanzi and S. W. Wilson and M. O'Neill and C. Ryan and T. Yu and J. F. Miller and I. Garibay and G. Holifield and A. S. Wu and T. Riopka and M. M. Meysenburg and A. W. Wright and N. Richter and J. H. Moore and M. D. Ritchie and L. Davis and R. Roy and M. Jakiela editors, GECCO 2004 Workshop Proceedings, Seattle, Washington, USA, 2004. details

  14. Marylyn D. Ritchie and Bill C. White and Joel S. Parker and Lance W. Hahn and Jason H. Moore. Optimization of Neural Networks using Genetic Programming Improves Detection and Modeling of Gene-Gene Interactions in Studies of Human Diseases. In Bart Rylander editor, Genetic and Evolutionary Computation Conference Late Breaking Papers, pages 255-259, Chicago, USA, 2003. details

  15. Marylyn D. Ritchie and Bill C. White and Joel S. Parker and Lance W. Hahn and Jason H. Moore. Optimization of Neural Networks using Genetic Programming to Improve Detection and Modeling of Gene-Gene Interactions in Studies of Human Diseases. In Alwyn M. Barry editor, GECCO 2003: Proceedings of the Bird of a Feather Workshops, Genetic and Evolutionary Computation Conference, pages 72-74, Chigaco, 2003. AAAI. details

Genetic Programming book chapters by Marylyn D Ritchie