NCBI Papers with Code
List of awesome NCBI Papers with Code Supplement.

CNN

  1. 1.
    Dual CNN for Relation Extraction with Knowledge-Based Attention and Word Embeddings Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6664687/ Code: https://github.com/mrlijun2017/Dual-CNN-RE​
  2. 2.
    CNN-BLPred: a Convolutional neural network based predictor for Ξ²-Lactamases (BL) and their classes Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751796/ Code: https://github.com/whiteclarence/CNN-BLPred​
  3. 3.
    Design of deep convolutional networks for prediction of image rapid serial visual presentation events Paper: https://www.ncbi.nlm.nih.gov/pubmed/29060296 Code: https://github.com/ZijingMao/ROICNN​
  4. 4.
    A simple convolutional neural network for prediction of enhancer-promoter interactions with DNA sequence data Paper: https://www.ncbi.nlm.nih.gov/pubmed/30649185 Code: https://github.com/zzUMN/Combine-CNN-Enhancer-and-Promoters​
  5. 5.
    A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition Paper:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207326/ Code: https://github.com/biopatrec/biopatrec​
  6. 6.
    GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text Paper: https://www.ncbi.nlm.nih.gov/pubmed/29272325 Code: https://github.com/valdersoul/GRAM-CNN​
  7. 7.
    Simple tricks of convolutional neural network architectures improve DNA-protein binding prediction Paper: https://www.ncbi.nlm.nih.gov/pubmed/30351403 Code: https://github.com/zhanglabtools/DNADataAugmentation​
  8. 8.
    EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937476/ Code: https://github.com/shervinea/enzynet​
  9. 9.
    Multi-timescale drowsiness characterization based on a video of a driver's face Paper: https://www.telecom.ulg.ac.be/mts-drowsiness/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165048/ Code: https://github.com/QMassoz/mts-drowsiness​
  10. 10.
    CLoDSA: a tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567576/ Code: https://github.com/joheras/CLoDSA​
  11. 11.
    Deep learning with convolutional neural networks for EEG decoding and visualization Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655781/ Code: https://github.com/robintibor/braindecode/ Code: https://github.com/TNTLFreiburg/braindecode​

Rice/Paddy Classification

  1. 1.
    Classifying Oryza sativa accessions into Indica and Japonica using logistic regression model with phenotypic data Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842562/ Code: https://github.com/bongsongkim/logit.regression.rice​
  2. 2.
    SNNRice6mA: A Deep Learning Method for Predicting DNA N6-Methyladenine Sites in Rice Genome Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797597/ Code: https://github.com/yuht4/SNNRice6mA​
  3. 3.
    Automatic estimation of heading date of paddy rice using deep learning Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6626381/ Code: https://github.com/svdesai/heading-date-estimation​
  4. 4.
    Distillation of crop models to learn plant physiology theories using machine learning Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541271/ Code: https://github.com/ky0on/simriw​
  5. 5.
    Evaluating remote sensing datasets and machine learning algorithms for mapping plantations and successional forests in Phnom Kulen National Park of Cambodia Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814064/ Code: https://github.com/Jojo666/PKNP-Data​
  6. 6.
    PlantCV v2: Image analysis software for high-throughput plant phenotyping Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5713628/ Code: https://github.com/danforthcenter/plantcv-v2-paper​
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  8. 9.
    Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500639/ Code: https://github.com/p2irc/deepplantphenomics​
  9. 10.
    DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375952/ Code: https://github.com/AlexOlsen/DeepWeeds​