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StableDNAm: stable and efficient DNA methylation prediction with adaptive feature correction learning (BMC Genomics, 2023)

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StableDNAm

Introduction

Any question is welcomed to be asked by issue and I will try my best to solve your problems.

basic dictionary

You can change parameters in configuration/config.py to train models.

You can change model structure in model/ClassificationDNAbert.py to train models.

You can change training process and dataset process in frame/ModelManager.py and frame/DataManager.py .

Besides, dataset in paper is also included in data/DNA_MS.

pretrain model

You should download pretrain model from relevant github repository.

For example, if you want to use DNAbert, you need to put them into the pretrain folder and rename the relevant choice in the model.

Usage

python main/train.py

About

StableDNAm: stable and efficient DNA methylation prediction with adaptive feature correction learning (BMC Genomics, 2023)

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