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Databases, Protein

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EL_LSTM: Prediction of DNA-Binding Residue from Protein Sequence by Combining Long Short-Term Memory and Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Most past works for DNA-binding residue prediction did not consider the relationships between residues. In this paper, we propose a novel approach for DNA-binding residue prediction, referred to as EL_LSTM, which includes two main components. The fir...

RFAmyloid: A Web Server for Predicting Amyloid Proteins.

International journal of molecular sciences
Amyloid is an insoluble fibrous protein and its mis-aggregation can lead to some diseases, such as Alzheimer's disease and Creutzfeldt⁻Jakob's disease. Therefore, the identification of amyloid is essential for the discovery and understanding of disea...

Convolutional neural network scoring and minimization in the D3R 2017 community challenge.

Journal of computer-aided molecular design
We assess the ability of our convolutional neural network (CNN)-based scoring functions to perform several common tasks in the domain of drug discovery. These include correctly identifying ligand poses near and far from the true binding mode when giv...

Using machine learning tools for protein database biocuration assistance.

Scientific reports
Biocuration in the omics sciences has become paramount, as research in these fields rapidly evolves towards increasingly data-dependent models. As a result, the management of web-accessible publicly-available databases becomes a central task in biolo...

Protein Secondary Structure Prediction Based on Data Partition and Semi-Random Subspace Method.

Scientific reports
Protein secondary structure prediction is one of the most important and challenging problems in bioinformatics. Machine learning techniques have been applied to solve the problem and have gained substantial success in this research area. However ther...

Protein-Protein Interactions Prediction via Multimodal Deep Polynomial Network and Regularized Extreme Learning Machine.

IEEE journal of biomedical and health informatics
Predicting the protein-protein interactions (PPIs) has played an important role in many applications. Hence, a novel computational method for PPIs prediction is highly desirable. PPIs endow with protein amino acid mutation rate and two physicochemica...

Predicting human protein function with multi-task deep neural networks.

PloS one
Machine learning methods for protein function prediction are urgently needed, especially now that a substantial fraction of known sequences remains unannotated despite the extensive use of functional assignments based on sequence similarity. One majo...

Development of a machine-learning model to predict Gibbs free energy of binding for protein-ligand complexes.

Biophysical chemistry
The possibility of using the atomic coordinates of protein-ligand complexes to assess binding affinity has a beneficial impact in the early stages of drug development and design. From the computational view, the creation of reliable scoring functions...

Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications.

Journal of molecular biology
Understanding the genetic basis of complex diseases is challenging. Prior work shows that disease-related proteins do not typically function in isolation. Rather, they often interact with each other to form a network module that underlies dysfunction...

Consistent prediction of GO protein localization.

Scientific reports
The GO-Cellular Component (GO-CC) ontology provides a controlled vocabulary for the consistent description of the subcellular compartments or macromolecular complexes where proteins may act. Current machine learning-based methods used for the automat...