- Park Y, Kellis M (2015) Deep learning for
 regulatory genomics. Nat Biotechnol 33
 (8):825–826. https://doi.org/10.1038/
 nbt.3313
- Angermueller C, Parnamaa T, Parts L, Stegle
 O (2016) Deep learning for computational
 biology. Mol Syst Biol 12(7):878.https://
 doi.org/10.15252/msb.20156651
- Min S, Lee B, Yoon S (2016) Deep learning in
 bioinformatics. Brief Bioinform.https://doi.
 org/10.1093/bib/bbw068
- Miotto R, Wang F, Wang S, Jiang X, Dudley
 JT (2017) Deep learning for healthcare:
 review, opportunities and challenges. Brief
 Bioinform. https://doi.org/10.1093/bib/
 bbx044
- Uziela K, Menendez Hurtado D, Shu N,
 Wallner B, Elofsson A (2017) ProQ3D:
 improved model quality assessments using
 deep learning. Bioinformatics 33
 (10):1578–1580.https://doi.org/10.1093/
 bioinformatics/btw819
- Liu F, Ren C, Li H, Zhou P, Bo X, Shu W
 (2016) De novo identification of replication-
 timing domains in the human genome by
 deep learning. Bioinformatics 32
 (5):641–649.https://doi.org/10.1093/bio
 informatics/btv643
- Kelley DR, Snoek J, Rinn JL (2016) Basset:
 learning the regulatory code of the accessible
 genome with deep convolutional neural net-
 works. Genome Res 26(7):990–999.https://
 doi.org/10.1101/gr.200535.115
- Yang B, Liu F, Ren C, Ouyang Z, Xie Z, Bo X,
 Shu W (2017) BiRen: predicting enhancers
 with a deep-learning-based model using the
 DNA sequence alone. Bioinformatics.
 https://doi.org/10.1093/bioinformatics/
 btx105
- Zhang S, Zhou J, Hu H, Gong H, Chen L,
 Cheng C, Zeng J (2016) A deep learning
 framework for modeling structural features
 of RNA-binding protein targets. Nucleic
 Acids Res 44(4):e32. https://doi.org/10.
 1093/nar/gkv1025
- Quang D, Xie X (2016) DanQ: a hybrid con-
 volutional and recurrent deep neural network
 for quantifying the function of DNA
 sequences. Nucleic Acids Res 44(11):e107.
 https://doi.org/10.1093/nar/gkw226
- Wang S, Sun S, Li Z, Zhang R, Xu J (2017)
 Accurate de novo prediction of protein con-
 tact map by ultra-deep learning model. PLoS
 Comput Biol 13(1):e1005324.https://doi.
 org/10.1371/journal.pcbi.1005324
- Xiong D, Zeng J, Gong H (2017) A deep
 learning framework for improving long-
range residue-residue contact prediction
using a hierarchical strategy. Bioinformatics.
https://doi.org/10.1093/bioinformatics/
btx296- Yuan Y, Shi Y, Li C, Kim J, Cai W, Han Z,
 Feng DD (2016) DeepGene: an advanced
 cancer type classifier based on deep learning
 and somatic point mutations. BMC Bioinfor-
 matics 17(Suppl 17):476.https://doi.org/
 10.1186/s12859-016-1334-9
- Kraus OZ, Ba JL, Frey BJ (2016) Classifying
 and segmenting microscopy images with deep
 multiple instance learning. Bioinformatics 32
 (12):i52–i59. https://doi.org/10.1093/bio
 informatics/btw252
- Kraus OZ, Grys BT, Ba J, Chong Y, Frey BJ,
 Boone C, Andrews BJ (2017) Automated
 analysis of high-content microscopy data
 with deep learning. Mol Syst Biol 13(4):924.
 https://doi.org/10.15252/msb.20177551
- Buggenthin F, Buettner F, Hoppe PS,
 Endele M, Kroiss M, Strasser M,
 Schwarzfischer M, Loeffler D, Kokkaliaris
 KD, Hilsenbeck O, Schroeder T, Theis FJ,
 Marr C (2017) Prospective identification of
 hematopoietic lineage choice by deep
 learning. Nat Methods 14(4):403–406.
 https://doi.org/10.1038/nmeth.4182
- Hazlett HC, Gu H, Munsell BC, Kim SH,
 Styner M, Wolff JJ, Elison JT, Swanson MR,
 Zhu H, Botteron KN, Collins DL, Constan-
 tino JN, Dager SR, Estes AM, Evans AC,
 Fonov VS, Gerig G, Kostopoulos P, McKins-
 try RC, Pandey J, Paterson S, Pruett JR,
 Schultz RT, Shaw DW, Zwaigenbaum L,
 Piven J, IBIS Network; Clinical Sites; Data
 Coordinating Center; Image Processing
 Core; Statistical Analysis (2017) Early brain
 development in infants at high risk for autism
 spectrum disorder. Nature 542
 (7641):348–351.https://doi.org/10.1038/
 nature21369
- Esteva A, Kuprel B, Novoa RA, Ko J, Swetter
 SM, Blau HM, Thrun S (2017)
 Dermatologist-level classification of skin can-
 cer with deep neural networks. Nature 542
 (7639):115–118.https://doi.org/10.1038/
 nature21056
- Chen Y, Li Y, Narayan R, Subramanian A, Xie
 X (2016) Gene expression inference with
 deep learning. Bioinformatics 32
 (12):1832–1839.https://doi.org/10.1093/
 bioinformatics/btw074
- Chen JH, Asch SM (2017) Machine learning
 and prediction in medicine - beyond the peak
 of inflated expectations. N Engl J Med 376
 (26):2507–2509.https://doi.org/10.1056/
 NEJMp1702071
204 Xiang-tian Yu et al.
