Computer-assisted protein domain boundary prediction using the Dom-Pred server
Computer-assisted protein domain boundary prediction using the Dom-Pred server
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DOI：
10.2174/138920307780363415
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发表时间：
2007-04-01
影响因子：
2.8
通讯作者：
Jones, David T.
中科院分区：
文献类型：
--
作者：
Bryson, Kevin;Cozzetto, Domenico;Jones, David T.
从序列中进行域预测是一项特别具有挑战性的任务，目前，各种不同的方法被用于解决该任务。在这里，我们试图将这些不同的方法分为若干大类。目前，仅从序列中进行完全自动的领域预测充满了问题，但这并不奇怪，因为即使给定了结构，人类专家目前在领域分配上也存在重大分歧。可以认为，我们应该只在人类专家同意的基准数据上测试领域预测方法，这就是我们在本文中采用的方法。即使对于人类专家一致同意的数据集，基于结构的自动领域分配仍然不总是一致的，因此领域预测方法仍然不可能完全自动地可靠地获得正确的结果。我们认为，计算机辅助领域预测是一个更容易实现的目标。带着这个目标，我们介绍了DomPred服务器。该服务器向用户提供两种完全不同的方法（DPS和DomSSEA）的结果。在本文中，每一种方法都针对最新的领域预测基准进行了单独的基准测试，以提供有关其各自可靠性的信息。由于领域预测方法的准确性主要取决于希望获得的结果类型（单/多领域分类、领域数量、剩余连接子位置等），因此采用了各种不同的基准分数。此外，在DomPred服务器中实现的这两种方法都可以建议替代的域预测，允许用户根据这些结果做出最终决策，并将自己的背景知识应用于问题。从URL中可以获得DomPred服务器。
Domain prediction from sequence is a particularly challenging task, and currently, a large variety of different methodologies are employed to tackle the task. Here we try to classify these diverse approaches into a number of broad categories. Completely automatic domain prediction from sequence alone is currently fraught with problems, but this should not be so surprising since human experts currently have significant disagreement on domain assignment even when given the structures. It can be argued that we should only test the domain prediction methods on benchmark data that human experts agree upon and this is the approach we take in this paper. Even for the data sets on which human experts agree, automatic structure-based domain assignment still cannot always agree, and so again it is still unlikely that domain prediction methods will reliably obtain correct results completely automatically. We make the argument that computer-assisted domain prediction is a more achievable goal. With this aim in mind, we present the DomPred server. This server provides the user with the results from two completely different categories of method (DPS and DomSSEA). In this paper, each method is individually benchmarked against one of the latest domain prediction benchmarks to provide information about their respective reliabilities. A variety of different benchmark scores are employed since the accuracy of a domain prediction method depends critically on what types of results one wishes to obtain (single/multi-domain classification, domain number, residue linker positions, etc.). Also both of these methods, implemented within the DomPred server, can suggest alternative domain predictions, allowing the user to make the final decision based on these results and applying their own background knowledge to the problem. The DomPred server is available from the URL.