A comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction
Y Liu, X Wang, B Liu - Briefings in bioinformatics, 2019 - academic.oup.com
Intrinsically disordered proteins and regions are widely distributed in proteins, which are
associated with many biological processes and diseases. Accurate prediction of intrinsically …
associated with many biological processes and diseases. Accurate prediction of intrinsically …
Deep learning for mining protein data
The recent emergence of deep learning to characterize complex patterns of protein big data
reveals its potential to address the classic challenges in the field of protein data mining …
reveals its potential to address the classic challenges in the field of protein data mining …
iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data
With the explosive growth of biological sequences generated in the post-genomic era, one
of the most challenging problems in bioinformatics and computational biology is to …
of the most challenging problems in bioinformatics and computational biology is to …
Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone …
Motivation The accuracy of predicting protein local and global structural properties such as
secondary structure and solvent accessible surface area has been stagnant for many years …
secondary structure and solvent accessible surface area has been stagnant for many years …
Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks
Motivation Capturing long-range interactions between structural but not sequence neighbors
of proteins is a long-standing challenging problem in bioinformatics. Recently, long short …
of proteins is a long-standing challenging problem in bioinformatics. Recently, long short …
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Protein secondary structure prediction began in 1951 when Pauling and Corey predicted
helical and sheet conformations for protein polypeptide backbone even before the first …
helical and sheet conformations for protein polypeptide backbone even before the first …
Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of …
Motivation Sequence-based prediction of one dimensional structural properties of proteins
has been a long-standing subproblem of protein structure prediction. Recently, prediction …
has been a long-standing subproblem of protein structure prediction. Recently, prediction …
SPOT-Disorder2: improved protein intrinsic disorder prediction by ensembled deep learning
Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to
be important in a wide range of biological functions and implicated in many diseases. Due to …
be important in a wide range of biological functions and implicated in many diseases. Due to …
The structural context of posttranslational modifications at a proteome-wide scale
The recent revolution in computational protein structure prediction provides folding models
for entire proteomes, which can now be integrated with large-scale experimental data. Mass …
for entire proteomes, which can now be integrated with large-scale experimental data. Mass …
Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network
T Luo, C Zhou, F Chao - BMC bioinformatics, 2018 - Springer
Background Conventional methods of motor imagery brain computer interfaces (MI-BCIs)
suffer from the limited number of samples and simplified features, so as to produce poor …
suffer from the limited number of samples and simplified features, so as to produce poor …