Learning with Hilbert–Schmidt independence criterion: A review and new perspectives
T Wang, X Dai, Y Liu - Knowledge-based systems, 2021 - Elsevier
Abstract The Hilbert–Schmidt independence criterion (HSIC) was originally designed to
measure the statistical dependence of the distribution-based Hilbert space embedding in …
measure the statistical dependence of the distribution-based Hilbert space embedding in …
Sequence representation approaches for sequence-based protein prediction tasks that use deep learning
Deep learning has been increasingly used in bioinformatics, especially in sequence-based
protein prediction tasks, as large amounts of biological data are available and deep learning …
protein prediction tasks, as large amounts of biological data are available and deep learning …
MK-FSVM-SVDD: a multiple kernel-based fuzzy SVM model for predicting DNA-binding proteins via support vector data description
Background: Detecting DNA-binding proteins (DBPs) based on biological and chemical
methods is time-consuming and expensive. Objective: In recent years, the rise of …
methods is time-consuming and expensive. Objective: In recent years, the rise of …
DeepM6ASeq-EL: prediction of human N6-methyladenosine (m6A) sites with LSTM and ensemble learning
Abstract N6-methyladenosine (m 6 A) is a prevalent methylation modification and plays a
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …
sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks
Key message We proposed an ensemble convolutional neural network model to identify
sgRNA high on-target activity in four crops and we used one-hot encoding and k-mers for …
sgRNA high on-target activity in four crops and we used one-hot encoding and k-mers for …
CRBPDL: Identification of circRNA-RBP interaction sites using an ensemble neural network approach
Circular RNAs (circRNAs) are non-coding RNAs with a special circular structure produced
formed by the reverse splicing mechanism. Increasing evidence shows that circular RNAs …
formed by the reverse splicing mechanism. Increasing evidence shows that circular RNAs …
Identification of sub-Golgi protein localization by use of deep representation learning features
Abstract Motivation The Golgi apparatus has a key functional role in protein biosynthesis
within the eukaryotic cell with malfunction resulting in various neurodegenerative diseases …
within the eukaryotic cell with malfunction resulting in various neurodegenerative diseases …
A method for identifying vesicle transport proteins based on LibSVM and MRMD
Z Tao, Y Li, Z Teng, Y Zhao - Computational and Mathematical …, 2020 - Wiley Online Library
With the development of computer technology, many machine learning algorithms have
been applied to the field of biology, forming the discipline of bioinformatics. Protein function …
been applied to the field of biology, forming the discipline of bioinformatics. Protein function …
iTTCA-RF: a random forest predictor for tumor T cell antigens
S Jiao, Q Zou, H Guo, L Shi - Journal of translational medicine, 2021 - Springer
Background Cancer is one of the most serious diseases threatening human health. Cancer
immunotherapy represents the most promising treatment strategy due to its high efficacy and …
immunotherapy represents the most promising treatment strategy due to its high efficacy and …
StackPDB: predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier
Q Zhang, P Liu, X Wang, Y Zhang, Y Han, B Yu - Applied Soft Computing, 2021 - Elsevier
DNA-binding proteins (DBPs) not only play an important role in all aspects of genetic
activities such as DNA replication, recombination, repair, and modification but also are used …
activities such as DNA replication, recombination, repair, and modification but also are used …