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README.md

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-## DeepPBS
+# DeepPBS
 Motivation:Accurate all-atom protein structures play an important role in various research and applications. However, in most cases, only coarse-grained models can be obtained for reasons. Precisely predict protein backbone structures based on alpha-carbon traces, the most-used coarse-grained model, is a pivotal step for precise all-atom modeling for protein structures. 
 
 Results: In this study, we proposed a deep learning-based method to predict protein backbone structures from alpha-carbon traces. Our method achieved comparable performance as the best previous method with cRMSD between predicted coordinates and reference coordinates as measurement.
 
 [点击进入骨架结构预测网页](deeppbs.com)
 
-[image](https://github.com/ElvinJun/DeepPBS/edit/master/process.jpg)
+# Protein structure prediction process
+![](https://github.com/ElvinJun/DeepPBS/blob/master/process.jpg?raw=true)
+
+
 # Recurrent Geometric Networks
 This is the reference (TensorFlow) implementation of recurrent geometric networks (RGNs), described in the paper [End-to-end differentiable learning of protein structure](https://www.biorxiv.org/content/early/2018/08/29/265231).