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references.bib
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@inproceedings{rizzo2016,
title = {A Deep Learning Approach to DNA Sequence Classification},
author = {Rizzo, Riccardo and Fiannaca, Antonino and La Rosa, Massimo and Urso, Alfonso},
editor = {Angelini, Claudia and Rancoita, Paola MV and Rovetta, Stefano},
year = {2016},
date = {2016},
publisher = {Springer International Publishing},
pages = {129--140},
series = {Lecture Notes in Computer Science},
doi = {10.1007/978-3-319-44332-4_10},
address = {Cham},
langid = {en}
}
@article{deregt2005,
title = {A Contextual Approach to Scientific Understanding},
author = {De Regt, Henk W. and Dieks, Dennis},
year = {2005},
month = {03},
date = {2005-03-01},
journal = {Synthese},
pages = {137--170},
volume = {144},
number = {1},
doi = {10.1007/s11229-005-5000-4},
url = {https://doi.org/10.1007/s11229-005-5000-4},
langid = {en}
}
@inproceedings{desai2020,
title = {Deep Ensemble Models for 16S Ribosomal Gene Classification},
author = {Desai, Heta P. and Parameshwaran, Anuja P. and Sunderraman, Rajshekhar and Weeks, Michael},
editor = {Cai, Zhipeng and Mandoiu, Ion and Narasimhan, Giri and Skums, Pavel and Guo, Xuan},
year = {2020},
date = {2020},
publisher = {Springer International Publishing},
pages = {282--290},
series = {Lecture Notes in Computer Science},
doi = {10.1007/978-3-030-57821-3_25},
address = {Cham},
langid = {en}
}
@inproceedings{rizzo2016a,
title = {A Deep Learning Approach to DNA Sequence Classification},
author = {Rizzo, Riccardo and Fiannaca, Antonino and La Rosa, Massimo and Urso, Alfonso},
editor = {Angelini, Claudia and Rancoita, Paola MV and Rovetta, Stefano},
year = {2016},
date = {2016},
publisher = {Springer International Publishing},
pages = {129--140},
series = {Lecture Notes in Computer Science},
doi = {10.1007/978-3-319-44332-4_10},
address = {Cham},
langid = {en}
}
@article{deregt2005a,
title = {A Contextual Approach to Scientific Understanding},
author = {De Regt, Henk W. and Dieks, Dennis},
year = {2005},
month = {03},
date = {2005-03-01},
journal = {Synthese},
pages = {137--170},
volume = {144},
number = {1},
doi = {10.1007/s11229-005-5000-4},
url = {https://doi.org/10.1007/s11229-005-5000-4},
langid = {en}
}
@inproceedings{desai2020a,
title = {Deep Ensemble Models for 16S Ribosomal Gene Classification},
author = {Desai, Heta P. and Parameshwaran, Anuja P. and Sunderraman, Rajshekhar and Weeks, Michael},
editor = {Cai, Zhipeng and Mandoiu, Ion and Narasimhan, Giri and Skums, Pavel and Guo, Xuan},
year = {2020},
date = {2020},
publisher = {Springer International Publishing},
pages = {282--290},
series = {Lecture Notes in Computer Science},
doi = {10.1007/978-3-030-57821-3_25},
address = {Cham},
langid = {en}
}
@inproceedings{rizzo2016b,
title = {A Deep Learning Approach to DNA Sequence Classification},
author = {Rizzo, Riccardo and Fiannaca, Antonino and La Rosa, Massimo and Urso, Alfonso},
editor = {Angelini, Claudia and Rancoita, Paola MV and Rovetta, Stefano},
year = {2016},
date = {2016},
publisher = {Springer International Publishing},
pages = {129--140},
series = {Lecture Notes in Computer Science},
doi = {10.1007/978-3-319-44332-4_10},
address = {Cham},
langid = {en}
}
@article{callahan2016,
title = {DADA2: High-resolution sample inference from Illumina amplicon data},
author = {Callahan, Benjamin J. and McMurdie, Paul J. and Rosen, Michael J. and Han, Andrew W. and Johnson, Amy Jo A. and Holmes, Susan P.},
year = {2016},
month = {07},
date = {2016-07},
journal = {Nature Methods},
pages = {581--583},
volume = {13},
number = {7},
doi = {10.1038/nmeth.3869},
url = {https://www.nature.com/articles/nmeth.3869},
note = {Number: 7
Publisher: Nature Publishing Group},
langid = {en}
}
@article{zhao2021,
title = {Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network},
author = {Zhao, Zhengqiao and Woloszynek, Stephen and Agbavor, Felix and Mell, Joshua Chang and Sokhansanj, Bahrad A. and Rosen, Gail L.},
year = {2021},
month = {09},
date = {2021-09-22},
journal = {PLOS Computational Biology},
pages = {e1009345},
volume = {17},
number = {9},
doi = {10.1371/journal.pcbi.1009345},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009345},
note = {Publisher: Public Library of Science},
langid = {en}
}
@article{shin2016,
title = {Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning},
author = {Shin, Hoo-Chang and Roth, Holger R. and Gao, Mingchen and Lu, Le and Xu, Ziyue and Nogues, Isabella and Yao, Jianhua and Mollura, Daniel and Summers, Ronald M.},
year = {2016},
month = {05},
date = {2016-05},
journal = {IEEE Transactions on Medical Imaging},
pages = {1285--1298},
volume = {35},
number = {5},
doi = {10.1109/TMI.2016.2528162},
note = {Conference Name: IEEE Transactions on Medical Imaging}
}
@inproceedings{NIPS2017_3f5ee243,
title = {Attention is all you need},
author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {{\L}ukasz} and Polosukhin, Illia},
editor = {Guyon, I. and Luxburg, U. Von and Bengio, S. and Wallach, H. and Fergus, R. and Vishwanathan, S. and Garnett, R.},
year = {2017},
date = {2017},
publisher = {Curran Associates, Inc.},
volume = {30},
url = {https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf},
note = {Citation Key: NIPS2017{\_}3f5ee243}
}
@article{angermueller2016,
title = {Deep learning for computational biology},
author = {Angermueller, Christof and {Pärnamaa}, Tanel and Parts, Leopold and Stegle, Oliver},
year = {2016},
month = {07},
date = {2016-07},
journal = {Molecular Systems Biology},
pages = {878},
volume = {12},
number = {7},
doi = {10.15252/msb.20156651},
url = {https://www.embopress.org/doi/full/10.15252/msb.20156651},
note = {Publisher: John Wiley & Sons, Ltd}
}
@inbook{NEURIPS2019_9015,
title = {PyTorch: An imperative style, high-performance deep learning library},
author = {Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and Desmaison, Alban and Kopf, Andreas and Yang, Edward and DeVito, Zachary and Raison, Martin and Tejani, Alykhan and Chilamkurthy, Sasank and Steiner, Benoit and Fang, Lu and Bai, Junjie and Chintala, Soumith},
year = {2019},
date = {2019},
publisher = {Curran Associates, Inc.},
pages = {8024{\textendash}8035},
url = {http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf},
note = {Citation Key: NEURIPS2019{\_}9015}
}