Randall Division of Cell and Molecular Biophysics, King's College London BHF Centre of Research Excellence, London SE1 1UL, UK.
Bioinformatics. 2017 Nov 1;33(21):3482-3485. doi: 10.1093/bioinformatics/btx424.
Large numbers of rare and unique titin missense variants have been discovered in both healthy and disease cohorts, thus the correct classification of variants as pathogenic or non-pathogenic has become imperative. Due to titin's large size (363 coding exons), current web applications are unable to map titin variants to domain structures. Here, we present a web application, TITINdb, which integrates titin structure, variant, sequence and isoform information, along with pre-computed predictions of the impact of non-synonymous single nucleotide variants, to facilitate the correct classification of titin variants.
TITINdb can be freely accessed at http://fraternalilab.kcl.ac.uk/TITINdb.
Supplementary data are available at Bioinformatics online.
在健康人群和疾病队列中都发现了大量罕见和独特的肌联蛋白错义变异，因此正确分类变异是致病性的还是非致病性的变得至关重要。由于肌联蛋白的体积庞大（363 个编码外显子），目前的网络应用程序无法将肌联蛋白变异映射到结构域。在这里，我们介绍了一个网络应用程序 TITINdb，它集成了肌联蛋白结构、变异、序列和异构体信息，以及预先计算的非同义单核苷酸变异的影响预测，以帮助正确分类肌联蛋白变异。
TITINdb 可在 http://fraternalilab.kcl.ac.uk/TITINdb 免费访问。
补充数据可在“Bioinformatics”在线获取。
