Evaluating deep learning for predicting epigenomic profiles

NIAID Data Ecosystem2026-03-14 收录

表观基因组预测

深度学习基因组学

数据链接：

https://zenodo.org/record/6464031 数据链接链接失效反馈

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资源简介：

Datasets and static codebase to replicate figures and results from the project.

创建时间：

2022-10-06

Enformer predicted epigenomic features for 1000G Geuvadis people (individual batch 2)

表观基因组预测

基因功能注释

Here each .h5 file contains matrices of 4 central bins(128bp for each bin) * 5313 epigenomic features for ~19,668 protein coding genes. The gene name/id to key name in .h5 mapping is coded in the meta

Zenodo2025-05-27 更新40

Supplementary Data and Models for: "Evaluation of a structure-based method for ab initio gene detection using deep learning"

基因结构预测

深度学习基因组学

Overview: This record contains a subset of the data and model assets for the research project described in the preprint "Evaluation of a structure-based method for ab initio gene detection using deep

Zenodo2026-03-19 更新30

Performance comparison of DNABERT2-Enhancer and Enhancer-IF on Basith’s testing datasets for eight cell types.

增强子识别

深度学习基因组学

Performance comparison of DNABERT2-Enhancer and Enhancer-IF on Basith’s testing datasets for eight cell types.

NIAID Data Ecosystem10

processed datasets of deepsignal-plant

植物DNA甲基化检测

深度学习基因组学

processed datasets of deepsignal-plant

NIAID Data Ecosystem40

Additional file 1 of MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning

变异致病性预测

深度学习基因组学

Additional file 1: Includes 11 tables for training and testing data sets used in the study. The names of the tables are: Table S1. Training variants for MetaRNN; Table S2. Training variants for MetaRN

NIAID Data Ecosystem30

Evaluating deep learning for predicting epigenomic profiles

资源简介：

相关数据集