AIMC Topic: Protein Interaction Mapping

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Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.

Bioinformatics (Oxford, England) Dec 1, 2018
MOTIVATION: Accurate prediction of a protein contact map depends greatly on capturing as much contextual information as possible from surrounding residues for a target residue pair. Recently, ultra-deep residual convolutional networks were found to b...
Proteins Amino Acid Sequence Protein Interaction Mapping Neural Networks, Computer Computational Biology
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Predicting protein-protein interactions through sequence-based deep learning.

Bioinformatics (Oxford, England) Sep 1, 2018
MOTIVATION: High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data, but their coverage is still low and the PPI data is also very noisy. Computational prediction of PPIs can be used to discover ...
Mice Proteins Area Under Curve Deep Learning Protein Binding Protein Interaction Mapping Software Animals Humans
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Leveraging prior knowledge for protein-protein interaction extraction with memory network.

Database : the journal of biological databases and curation Jan 1, 2018
Automatically extracting protein-protein interactions (PPIs) from biomedical literature provides additional support for precision medicine efforts. This paper proposes a novel memory network-based model (MNM) for PPI extraction, which leverages prior...
Algorithms Databases, Protein Knowledge Protein Interaction Mapping Statistics as Topic Neural Networks, Computer
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Revisit of Machine Learning Supported Biological and Biomedical Studies.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2018
Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should h...
Precision Medicine Biomedical Research Big Data Machine Learning Software Protein Interaction Mapping Sequence Analysis Computational Biology Data Mining Image Processing, Computer-Assisted
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Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

Cancer genomics & proteomics Jan 1, 2018
Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in h...
Humans Protein Interaction Mapping Genes, Neoplasm Drug Discovery Genomics Support Vector Machine Biomarkers, Tumor Neoplasms
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Using neural networks for reducing the dimensions of single-cell RNA-Seq data.

Nucleic acids research Sep 29, 2017
While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges. These include ...
Protein Interaction Mapping Computational Biology Multifactor Dimensionality Reduction Datasets as Topic Sequence Analysis, RNA Neural Networks, Computer Gene Expression Regulation Single-Cell Analysis Software Cluster Analysis Databases, Genetic Gene Expression Profiling RNA Humans
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Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network.

Molecular bioSystems Jun 27, 2017
Protein-protein interactions (PPIs) play an important role in most of the biological processes. How to correctly and efficiently detect protein interaction is a problem that is worth studying. Although high-throughput technologies provide the possibi...
Neural Networks, Computer Algorithms Computational Biology Support Vector Machine Protein Interaction Mapping Protein Binding
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Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.

Oncotarget Apr 4, 2017
Identification of protein-protein interactions (PPIs) is of critical importance for deciphering the underlying mechanisms of almost all biological processes of cell and providing great insight into the study of human disease. Although much effort has...
Saccharomyces cerevisiae Protein Interaction Mapping Saccharomyces cerevisiae Proteins Humans Bacterial Proteins Algorithms Computational Biology Reproducibility of Results Support Vector Machine Helicobacter pylori Databases, Protein Protein Binding
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Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

Medicinal chemistry (Shariqah (United Arab Emirates)) Jan 1, 2017
BACKGROUND: Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determini...
Humans Computational Biology Animals Machine Learning Protein Interaction Mapping
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Computational Methods to Predict Protein Functions from Protein-Protein Interaction Networks.

Current protein & peptide science Jan 1, 2017
Predicting functions of proteins is a key issue in the post-genomic era. Some experimental methods have been designed to predict protein functions. However, these methods cannot accommodate the vast amount of sequence data due to their inherent diffi...
Protein Interaction Mapping Humans Decision Trees Neural Networks, Computer Computational Biology Proteins Machine Learning Support Vector Machine
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