transmembrane region prediction toolWe present a novel approach combining mathematical methods and artificial neural networks to predict the transmembrane regions of transmembrane proteins, considering protein sequence information alone. We have focused on developing a data-driven model based on a non-linear...
Because it is difficult to determinate the membrane protein's structure by wet-lab experiments,accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called Mem Brain, whose input is the amino acid sequence. Mem ...
Motivated by the success of intra-protein contact predictions in monomer structure prediction26,27,28, various advanced deep learning methods have been developed to predict the inter-chain contacts for protein complexes29,30,31,32,33,34,35,36,37,38,39,40. Our previous work, DeepHomo29, utiliz...
The alpha transmembrane region prediction tool is a data-driven model based on a counter-propagation neural network (CPNN) classifier built using transmembrane and non-transmembrane protein segments, which are characterized mathematically using amino acid adjacency matrix. The developed classifier shows ...
waveTM is a web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. Prediction is performed by a dynamic programming algorithm on wavelet-denoised 'hydropathy' signals. Users submit a protein sequence and receive interactively the results. Topology prediction can also...
Jones, The transmembrane topology of Batten disease protein CLN3 determined by consensus computational prediction constrained by experimental data,... T Nugent,SE Mole,DT Jones - 《Febs Letters》 被引量: 58发表: 2008年 A novel tool for the prediction of transmembrane protein topology based on a...
Protein sequence data and structural information may be acquired from public protein knowledge bases, emanate from prediction algorithms, or even be defined by the user. Several important biological and physical sequence attributes can be embedded in the graphical representation....
structure predictionprotein foldingA hallmark of membrane protein structure is the large number of distorted transmembrane helices. Because of the prevalence of bends, it is important to not only understand how they are generated but also to learn how to predict their occurrence. Here, we find ...
The predictor implemented by an end-to-end deep learning model can identify potential interactions from protein primary sequence information. The experimental results over the independent validation demonstrated considerable prediction performance with an MCC of 0.541. Conclusions To our knowledge, we were ...
Here, we present a database of the human α-helical transmembrane proteome, including the predicted and/or experimentally established topology of each transmembrane protein, together with the reliability of the prediction. In order to distinguish transmembrane proteins in the proteome as well as for ...