An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images.
about
Modeling Beta-Traces for Beta-Barrels from Cryo-EM Density Maps.Comparing an Atomic Model or Structure to a Corresponding Cryo-electron Microscopy Image at the Central Axis of a Helix.Deep Convolutional Neural Networks for Detecting Secondary Structures in Protein Density Maps from Cryo-Electron Microscopy.CHALLENGES IN MATCHING SECONDARY STRUCTURES IN CRYO-EM: AN EXPLORATION.
P2860
An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
An Effective Computational Met ...... ermination for Cryo-EM Images.
@en
type
label
An Effective Computational Met ...... ermination for Cryo-EM Images.
@en
prefLabel
An Effective Computational Met ...... ermination for Cryo-EM Images.
@en
P2093
P2860
P1476
An Effective Computational Met ...... ermination for Cryo-EM Images.
@en
P2093
Abhishek Biswas
Desh Ranjan
Kamal Al Nasr
Mohammad Zubair
Stephanie Zeil
P2860
P304
P356
10.1109/TCBB.2016.2543721
P577
2016-03-17T00:00:00Z