Popular repositories Loading

1. LSTM-COX-CODE LSTM-COX-CODE Public

   The source code is an implementation of our method described in the paper "Survival Analysis of Breast Cancer Utilizing Integrated Features with Ordinal Cox Model and Auxiliary Loss".

   R 4 1

2. Bioimage-based-Prediction-of-Protein-Subcellular-Location-in-Human-Tissue-with-bp_neral_network Bioimage-based-Prediction-of-Protein-Subcellular-Location-in-Human-Tissue-with-bp_neral_network Public

   To prove the efficacy of SAE-RF method proposed, we need to compare the result with an equivalent neural network. So, we designed this bp_neral_network to verify our proposed metod.

   MATLAB 1

3. bp_neral_network_for_Bioimage_based_Prediction bp_neral_network_for_Bioimage_based_Prediction Public

   To prove the efficacy of SAE-RF method proposed, we need to compare the result with an equivalent neural network. So, we designed this bp_neral_network to verify our proposed metod.

   MATLAB

4. CAFFE_CNN_for_Bioimage_based_Prediction CAFFE_CNN_for_Bioimage_based_Prediction Public

   we designed this end-to-end CNN code in CAFFE to compare our proposed metod.

   MATLAB

5. SAE-RF-CODE SAE-RF-CODE Public

   The source code is an implementation of our method described in the paper "Bioimage-based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks".

   MATLAB

6. SAE-RF-CODE-data SAE-RF-CODE-data Public

   the collection of 2,413 IHC bioimages, containing 21 proteins related to 46 normal human tissues, generated from the HPA served as our benchmark dataset.