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啤酒厂:深度学习和更深入的蛋白质一维结构注释预测。

Brewery: deep learning and deeper profiles for the prediction of 1D protein structure annotations.

机构信息

School of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland.

出版信息

Bioinformatics. 2020 Jun 1;36(12):3897-3898. doi: 10.1093/bioinformatics/btaa204.

Abstract

MOTIVATION

Protein structural annotations (PSAs) are essential abstractions to deal with the prediction of protein structures. Many increasingly sophisticated PSAs have been devised in the last few decades. However, the need for annotations that are easy to compute, process and predict has not diminished. This is especially true for protein structures that are hardest to predict, such as novel folds.

RESULTS

We propose Brewery, a suite of ab initio predictors of 1D PSAs. Brewery uses multiple sources of evolutionary information to achieve state-of-the-art predictions of secondary structure, structural motifs, relative solvent accessibility and contact density.

AVAILABILITY AND IMPLEMENTATION

The web server, standalone program, Docker image and training sets of Brewery are available at http://distilldeep.ucd.ie/brewery/.

CONTACT

gianluca.pollastri@ucd.ie.

摘要

动机

蛋白质结构注释(PSAs)是处理蛋白质结构预测的重要抽象概念。在过去的几十年中,已经设计出了许多越来越复杂的 PSA。然而,对于易于计算、处理和预测的注释的需求并没有减少。对于最难预测的蛋白质结构,如新型折叠,更是如此。

结果

我们提出了 Brewery,这是一套用于从头预测一维 PSA 的工具。Brewery 使用多种进化信息来源,实现了对二级结构、结构基序、相对溶剂可及性和接触密度的最先进预测。

可用性和实现

Brewery 的网络服务器、独立程序、Docker 镜像和培训集可在 http://distilldeep.ucd.ie/brewery/ 获得。

联系信息

gianluca.pollastri@ucd.ie

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