AIMC Topic: Databases, Protein

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Potent pairing: ensemble of long short-term memory networks and support vector machine for chemical-protein relation extraction.

Database : the journal of biological databases and curation Jan 1, 2018
Biomedical researchers regularly discover new interactions between chemical compounds/drugs and genes/proteins, and report them in research literature. Having knowledge about these interactions is crucially important in many research areas such as pr...
Support Vector Machine Proteins Databases, Protein Deep Learning Protein Binding Pharmaceutical Preparations Data Mining Databases, Chemical Neural Networks, Computer Drug Discovery
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Extracting chemical-protein relations using attention-based neural networks.

Database : the journal of biological databases and curation Jan 1, 2018
Relation extraction is an important task in the field of natural language processing. In this paper, we describe our approach for the BioCreative VI Task 5: text mining chemical-protein interactions. We investigate multiple deep neural network (DNN) ...
Neural Networks, Computer Algorithms Proteins Databases, Protein Databases, Chemical
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Document triage for identifying protein-protein interactions affected by mutations: a neural network ensemble approach.

Database : the journal of biological databases and curation Jan 1, 2018
The precision medicine (PM) initiative promises to identify individualized treatment depending on a patients' genetic profile and their related responses. In order to help health professionals and researchers in the PM endeavor, BioCreative VI organi...
Neural Networks, Computer Databases, Protein Algorithms Mutation Protein Interaction Maps
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An end-to-end deep learning architecture for extracting protein-protein interactions affected by genetic mutations.

Database : the journal of biological databases and curation Jan 1, 2018
The BioCreative VI Track IV (mining protein interactions and mutations for precision medicine) challenge was organized in 2017 with the goal of applying biomedical text mining methods to support advancements in precision medicine approaches. As part ...
Databases, Protein Neural Networks, Computer Mutation Machine Learning Algorithms Protein Interaction Maps
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Hierarchical bi-directional attention-based RNNs for supporting document classification on protein-protein interactions affected by genetic mutations.

Database : the journal of biological databases and curation Jan 1, 2018
In this paper, we describe a hierarchical bi-directional attention-based Re-current Neural Network (RNN) as a reusable sequence encoder architecture, which is used as sentence and document encoder for document classification. The sequence encoder is ...
Neural Networks, Computer Algorithms Reproducibility of Results Databases, Protein Mutation Data Mining Protein Interaction Maps Models, Theoretical Support Vector Machine
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CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes.

BMC bioinformatics Dec 28, 2017
BACKGROUND: The β-Lactamase (BL) enzyme family is an important class of enzymes that plays a key role in bacterial resistance to antibiotics. As the newly identified number of BL enzymes is increasing daily, it is imperative to develop a computationa...
Amino Acid Sequence beta-Lactamases ROC Curve Databases, Protein Models, Molecular Neural Networks, Computer Algorithms Reproducibility of Results
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Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks.

Cell systems Dec 20, 2017
While genes are defined by sequence, in biological systems a protein's function is largely determined by its three-dimensional structure. Evolutionary information embedded within multiple sequence alignments provides a rich source of data for inferri...
Humans Databases, Protein Neural Networks, Computer Animals Models, Molecular Machine Learning Algorithms Computational Biology Probability Protein Conformation Forecasting Proteins Protein Folding Sequence Alignment
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Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

BMC bioinformatics Dec 6, 2017
BACKGROUND: Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has b...
Amino Acids Knowledge Bases Protein Interaction Mapping Models, Statistical Proteins Databases, Protein Software Computational Biology
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Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants.

Proteins Nov 29, 2017
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and a database of GO term predic...
Animals Transcriptome Proteomics Sequence Analysis, Protein Databases, Protein PTEN Phosphohydrolase Models, Biological Gene Ontology Humans Machine Learning
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isGPT: An optimized model to identify sub-Golgi protein types using SVM and Random Forest based feature selection.

Artificial intelligence in medicine Nov 26, 2017
The Golgi Apparatus (GA) is a key organelle for protein synthesis within the eukaryotic cell. The main task of GA is to modify and sort proteins for transport throughout the cell. Proteins permeate through the GA on the ER (Endoplasmic Reticulum) fac...
Proteins Animals Databases, Protein Amino Acid Sequence Computational Biology Humans Oligopeptides Support Vector Machine Reproducibility of Results Golgi Apparatus
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