- deep_learning_DNA - Classifying human DNA sequence and random ATCG sequences, using keras CNN
- DeepMod - takes long-read signals as input and outputs modification summary for each genomic position in a reference genome together with modification prediction for each base in a long read.
- janggu - a python package that facilitates deep learning in the context of genomics
- genomelake
- deepvariant - deep learning-based variant caller
- Keras-genomics - A Keras-based deep learning platform to perform hyper-parameter tuning, training and prediction on genomics data
- https://github.com/danforthcenter/plantcv
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- 2016-05 | Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping | Michael P. Pound, Alexandra J. Burgess, Michael H. Wilson, Jonathan A. Atkinson, Marcus Griffiths, Aaron S. Jackson, Adrian Bulat, Yorgos Tzimiropoulos, Darren M. Wells, Erik H. Murchie, Tony P. Pridmore, Andrew P. French | Biorxiv
- 2016-03 | DeepNano: Deep Recurrent Neural Networks for Base Calling in MinION Nanopore Reads | Vladimír Boža, Broňa Brejová, Tomáš Vinař | Arxiv | code
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2016-02 | Gene expression inference with deep learning | Yifei Chen, Yi Li, Rajiv Narayan, Aravind Subramanian, Xiaohui Xie | Bioinformatics
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2016-03 | deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks | Byunghan Lee, Junghwan Baek, Seunghyun Park, Sungroh Yoon | Arxiv
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- 2016-06 | DeepLNC, a long non-coding RNA prediction tool using deep neural network | Rashmi Tripathi, Sunil Patel, Vandana Kumari, Pavan Chakraborty, Pritish Kumar Varadwaj | Network Modeling Analysis in Health Informatics and Bioinformatics
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2016-08 | DeepChrome: deep-learning for predicting gene expression from histone modifications | Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi | Bioinformatics
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2016-11 | RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach | Xiaoyong Pan, Hong-Bin Shen | bioRxiv
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2015-03 | Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters | Yifeng Li, Chih-Yu Chen, and Wyeth W. Wasserman | 19th Annual International Conference, RECOMB 2015, Warsaw, Proceedings
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2015-07 | DeepBind: Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning | Babak Alipanahi, Andrew Delong, Matthew T. Weirauch & Brendan J. Frey | Nature Biotechnology
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2015-08 | Deep learning for regulatory genomics | Yongjin Park & Manolis Kellis | Nature Biotechnology
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2015-08 | DeepSEA: Predicting effects of noncoding variants with deep learning–based sequence model | Jian Zhou & Olga G. Troyanskaya | Nature Methods: Short intro & Nature Methods
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2016-03 | Genome-Wide Prediction of cis-Regulatory Regions Using Supervised Deep Learning Methods | Yifeng Li, Wenqiang Shi, Wyeth W Wasserman | Biorxiv
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2016-05 | Denoising genome-wide histone ChIP-seq with convolutional neural networks | Pang Wei Koh, Emma Pierson, Anshul Kundaje | Biorxiv
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2016-05 | Deep Motif: Visualizing Genomic Sequence Classifications | Jack Lanchantin, Ritambhara Singh, Zeming Lin, Yanjun Qi | Arxiv
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2016-11 | Predicting Enhancer-Promoter Interaction from Genomic Sequence with Deep Neural Networks | Shashank Singh, Yang Yang, Barnabas Poczos, Jian Ma | bioRxiv
- 2016-08 | DeepWAS: Directly integrating regulatory information into GWAS using deep learning supports master regulator MEF2C as risk factor for major depressive disorder | Gökcen Eraslan, Janine Arloth, Jade Martins, Stella Iurato, Darina Czamara, Elisabeth B. Binder, Fabian J. Theis, Nikola S. Mueller | bioRxiv
- 2016-12 | Unsupervised Learning from Noisy Networks with Applications to Hi-C Data | Wang, Bo, Junjie Zhu, Armin Pourshafeie, Oana Ursu, Serafim Batzoglou, and Anshul Kundaje | Advances in Neural Information Processing Systems (NIPS 2016)
- https://github.com/gokceneraslan/awesome-deepbio
- https://github.com/josephmisiti/awesome-machine-learning
- https://github.com/visenger/awesome-mlops
- https://github.com/windmaple/awesome-AutoML
- https://github.com/danielecook/Awesome-Bioinformatics#readme
