首页> 外文会议> >A bi-recursive neural network architecture for the prediction of protein coarse contact maps

【24h】

A bi-recursive neural network architecture for the prediction of protein coarse contact maps

机译：用于蛋白质粗接触图预测的双递归神经网络架构

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

Prediction of contact maps may be seen as a strategic step towards the solution of fundamental open problems in structural genomics. In this paper we focus on coarse grained maps that describe the spatial neighborhood relation between secondary structure elements (helices, strands, and coils) of a protein. We introduce a new machine learning approach for scoring candidate contact maps. The method combines a specialized noncausal recursive connectionist architecture and a heuristic graph search algorithm. The network is trained using candidate graphs generated during search. We show how the process of selecting and generating training examples is important for tuning the precision of the predictor.

机译：接触图的预测可以看作是解决结构基因组学中根本性开放性问题的战略性步骤。在本文中，我们关注于粗糙的颗粒图，这些图描述了蛋白质的二级结构元素（螺旋，链和螺旋）之间的空间邻域关系。我们引入了一种新的机器学习方法来对候选联系人地图进行评分。该方法结合了专门的非因果递归连接主义体系结构和启发式图搜索算法。使用搜索过程中生成的候选图来训练网络。我们展示了选择和生成训练示例的过程对于调整预测变量的精度如何重要。

著录项

来源
《》|2002年|p.187-196|共10页
会议地点
作者
Vullo; A.; Frasconi; P.;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类无线电电子学、电信技术;
关键词
proteins; biology computing; neural nets; learning (artificial intelligence); search problems; graph theory; probability; protein contact maps; structural genomics; contact maps; recursive connectionist architecture; heuristic graph search algorithm;

机译：蛋白质生物计算;神经网络学习（人工智能）;搜索问题;图论可能性;蛋白质接触图;结构基因组学;联系地图;递归连接主义架构;启发式图搜索算法;

相似文献

外文文献
中文文献
专利

1. Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks [J] . Hanson Jack, Paliwal Kuldip, Litfin Thomas, Bioinformatics . 2019,第14期

机译：通过使用预测的联系地图和经常性和残余卷积神经网络的集合来改善蛋白质二级结构，骨干角，溶剂可访问性和接触号的预测
2. Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks [J] . Hanson Jack, Peliwal Kuldip, Litfin Thomas, Bioinformatics . 2018,第23期

机译：通过耦合与卷积神经网络的剩余二维双向短期内记忆，精确预测蛋白质联系地图
3. NNcon: improved protein contact map prediction using 2D-recursive neural networks [J] . Allison N. Tegge, Jesse Eickholt, Jianlin Cheng, Nucleic acids research . 2009,第suppla2期

机译：NNcon：使用2D递归神经网络改进的蛋白质接触图预测
4. A Bi-Recursive neural network architecture for the prediction of protein coarse contact maps [C] . Alessandro Vullo, Paolo Frasconi IEEE Computer Society Bioinformatics Conference . 2002

机译：一种用于预测蛋白质粗致密地图的双递归神经网络架构
5. Learning protein structure contact maps using neural networks. [D] . Poulson, Vaughn. 2007

机译：使用神经网络学习蛋白质结构接触图。
6. CNNcon: Improved Protein Contact Maps Prediction Using Cascaded Neural Networks [O] . Wang Ding, Jiang Xie, Dongbo Dai, -1

机译：CNNcon：使用级联神经网络的改进的蛋白质接触图预测
7. A bi-recursive neural network architecture for the prediction of protein coarse contact maps [O] . Alessandro Vullo, Paolo Frasconi 2002

机译：用于蛋白质粗接触图预测的双递归神经网络架构

A bi-recursive neural network architecture for the prediction of protein coarse contact maps

摘要

著录项

相似文献

相关主题

期刊订阅