Gordon Life Science Institute, Boston, MA 02478, USA; Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.
Gordon Life Science Institute, Boston, MA 02478, USA; Computer Science, Jingdezhen Ceramic Institute, Jingdezhen, China.
Genomics. 2019 Dec;111(6):1274-1282. doi: 10.1016/j.ygeno.2018.08.007. Epub 2018 Sep 1.
A cell contains numerous protein molecules. One of the fundamental goals in molecular cell biology is to determine their subcellular locations since this information is extremely important to both basic research and drug development. In this paper, we report a novel and very powerful predictor called "pLoc_bal-mHum" for predicting the subcellular localization of human proteins based on their sequence information alone. Cross-validation tests on exactly the same experiment-confirmed dataset have indicated that the new predictor is remarkably superior to the existing state-of-the-art predictor in identifying the subcellular localization of human proteins. To maximize the convenience for the majority of experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mHum/, by which users can easily get their desired results without the need to go through the detailed mathematics.
细胞内含有大量的蛋白质分子。在分子细胞生物学中，一个基本目标就是确定这些蛋白质的亚细胞位置，因为这对于基础研究和药物开发都非常重要。在本文中，我们报道了一种新的、非常强大的预测器，称为“pLoc_bal-mHum”，它可以仅基于蛋白质序列信息预测人类蛋白质的亚细胞定位。在完全相同的经过实验验证的数据集上进行的交叉验证测试表明，与现有的最先进的预测器相比，新的预测器在识别人类蛋白质的亚细胞定位方面具有显著的优越性。为了最大限度地方便大多数实验科学家，我们在 http://www.jci-bioinfo.cn/pLoc_bal-mHum/ 上建立了一个易于使用的新预测器的网络服务器，用户可以轻松地获得他们所需的结果，而无需了解详细的数学原理。
