Legacy Notes

Switch language: 旧版保留说明

This page preserves the essential writing from the original documentation rather than replacing it.

Original QuickStart highlights

  • CPU memory is recommended as 16GB

  • GPU memory is recommended as 8GB

  • Python 3.8

  • Keras == 2.4.0

  • TensorFlow == 2.3.0

  • numpy >= 1.15.4

  • scipy >= 1.2.1

  • scikit-learn >= 0.20.3

  • seaborn >=0.9.0

  • matplotlib >=3.1.0

Original motivation

Though deep learning methods have been widely developed for predicting chromatin interactions using flanking DNA sequence in identified chromatin interaction regions, a comprehensive software toolkit to integrate and evaluate different deep learning architectures are under-developed.

Original model inventory

  • onehot_cnn_one_branch

  • onehot_cnn_two_branch

  • onehot_embedding_dense

  • onehot_embedding_cnn_one_branch

  • onehot_embedding_cnn_two_branch

  • onehot_dense

  • onehot_resnet18

  • embedding_cnn_one_branch

  • embedding_cnn_two_branch

Original data organization highlights

The original project centered on:

  • DeepChrInteract.py as the main entry file;

  • data_preprocessing.py for preprocessing;

  • model.py for model definitions;

  • train.py for training;

  • test.py for evaluation;

  • embedding_matrix.npy for pretrained DNA2Vec features;

  • data/ for labeled sequence folders;

  • h5_weights/ and result/ for saved outputs.

Preservation policy

The current documentation keeps these legacy concepts visible and extends them with the modern PyTorch redesign rather than erasing them.

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