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Machine Learning and Its Applications to Biology

Author

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  • Adi L Tarca
  • Vincent J Carey
  • Xue-wen Chen
  • Roberto Romero
  • Sorin Drăghici

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Suggested Citation

  • Adi L Tarca & Vincent J Carey & Xue-wen Chen & Roberto Romero & Sorin Drăghici, 2007. "Machine Learning and Its Applications to Biology," PLOS Computational Biology, Public Library of Science, vol. 3(6), pages 1-11, June.
    • Handle: RePEc:plo:pcbi00:0030116
    DOI: 10.1371/journal.pcbi.0030116
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    Cited by:

    1. Parag Parashar & Chun Han Chen & Chandni Akbar & Sze Ming Fu & Tejender S Rawat & Sparsh Pratik & Rajat Butola & Shih Han Chen & Albert S Lin, 2019. "Analytics-statistics mixed training and its fitness to semisupervised manufacturing," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-18, August.
    2. Dennis Pischel & Jörn H Buchbinder & Kai Sundmacher & Inna N Lavrik & Robert J Flassig, 2018. "A guide to automated apoptosis detection: How to make sense of imaging flow cytometry data," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-17, May.
    3. Willcock, Simon & Martínez-López, Javier & Hooftman, Danny A.P. & Bagstad, Kenneth J. & Balbi, Stefano & Marzo, Alessia & Prato, Carlo & Sciandrello, Saverio & Signorello, Giovanni & Voigt, Brian & , 2018. "Machine learning for ecosystem services," Ecosystem Services, Elsevier, vol. 33(PB), pages 165-174.
    4. Stephen Gang Wu & Yuxuan Wang & Wu Jiang & Tolutola Oyetunde & Ruilian Yao & Xuehong Zhang & Kazuyuki Shimizu & Yinjie J Tang & Forrest Sheng Bao, 2016. "Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-22, April.
    5. Lyaqini, S. & Nachaoui, M. & Hadri, A., 2022. "An efficient primal-dual method for solving non-smooth machine learning problem," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    6. Dolores Wolfram & Ravi Starzl & Hubert Hackl & Derek Barclay & Theresa Hautz & Bettina Zelger & Gerald Brandacher & W P Andrew Lee & Nadine Eberhart & Yoram Vodovotz & Johann Pratschke & Gerhard Piere, 2014. "Insights from Computational Modeling in Inflammation and Acute Rejection in Limb Transplantation," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-11, June.
    7. Malka N. Halgamuge, 2020. "Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells," IJERPH, MDPI, vol. 17(12), pages 1-27, June.
    8. Asa Ben-Hur & Cheng Soon Ong & Sören Sonnenburg & Bernhard Schölkopf & Gunnar Rätsch, 2008. "Support Vector Machines and Kernels for Computational Biology," PLOS Computational Biology, Public Library of Science, vol. 4(10), pages 1-10, October.
    9. Takaya Saito & Marc Rehmsmeier, 2015. "The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
    10. Früh, Linus & Kampen, Helge & Kerkow, Antje & Schaub, Günter A. & Walther, Doreen & Wieland, Ralf, 2018. "Modelling the potential distribution of an invasive mosquito species: comparative evaluation of four machine learning methods and their combinations," Ecological Modelling, Elsevier, vol. 388(C), pages 136-144.
    11. Wang, Jia & Hu, Jun & Shen, Shifei & Zhuang, Jun & Ni, Shunjiang, 2020. "Crime risk analysis through big data algorithm with urban metrics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    12. Lior Shamir & John D Delaney & Nikita Orlov & D Mark Eckley & Ilya G Goldberg, 2010. "Pattern Recognition Software and Techniques for Biological Image Analysis," PLOS Computational Biology, Public Library of Science, vol. 6(11), pages 1-10, November.
    13. Ribeiro, Haroldo V. & Lopes, Diego D. & Pessa, Arthur A.B. & Martins, Alvaro F. & da Cunha, Bruno R. & Gonçalves, Sebastián & Lenzi, Ervin K. & Hanley, Quentin S. & Perc, Matjaž, 2023. "Deep learning criminal networks," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    14. Joana Rosado Coelho & João André Carriço & Daniel Knight & Jose-Luis Martínez & Ian Morrissey & Marco Rinaldo Oggioni & Ana Teresa Freitas, 2013. "The Use of Machine Learning Methodologies to Analyse Antibiotic and Biocide Susceptibility in Staphylococcus aureus," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-10, February.
    15. Guido Zampieri & Supreeta Vijayakumar & Elisabeth Yaneske & Claudio Angione, 2019. "Machine and deep learning meet genome-scale metabolic modeling," PLOS Computational Biology, Public Library of Science, vol. 15(7), pages 1-24, July.
    16. Bahareh Torkzaban & Amir Hossein Kayvanjoo & Arman Ardalan & Soraya Mousavi & Roberto Mariotti & Luciana Baldoni & Esmaeil Ebrahimie & Mansour Ebrahimi & Mehdi Hosseini-Mazinani, 2015. "Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-17, November.
    17. Shun Adachi, 2017. "Rigid geometry solves “curse of dimensionality” effects in clustering methods: An application to omics data," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-20, June.

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