AIMC Topic: Sequence Analysis

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pysster: classification of biological sequences by learning sequence and structure motifs with convolutional neural networks.

Bioinformatics (Oxford, England) Sep 1, 2018
SUMMARY: Convolutional neural networks (CNNs) have been shown to perform exceptionally well in a variety of tasks, including biological sequence classification. Available implementations, however, are usually optimized for a particular task and diffi...
Neural Networks, Computer Machine Learning Software Binding Sites Sequence Analysis
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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...
Machine Learning Software Precision Medicine Biomedical Research Big Data Image Processing, Computer-Assisted Computational Biology Data Mining Protein Interaction Mapping Sequence Analysis
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A Machine Learning Based Approach to de novo Sequencing of Glycans from Tandem Mass Spectrometry Spectrum.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2015
Recently, glycomics has been actively studied and various technologies for glycomics have been rapidly developed. Currently, tandem mass spectrometry (MS/MS) is one of the key experimental tools for identification of structures of oligosaccharides. M...
Machine Learning Algorithms Reproducibility of Results Sensitivity and Specificity Polysaccharides Tandem Mass Spectrometry Pattern Recognition, Automated Carbohydrate Sequence Molecular Sequence Data Sequence Analysis Glycomics
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Classification of imbalanced bioinformatics data by using boundary movement-based ELM.

Bio-medical materials and engineering Jan 1, 2015
To address the imbalanced classification problem emerging in Bioinformatics, a boundary movement-based extreme learning machine (ELM) algorithm called BM-ELM was proposed. BM-ELM tries to firstly explore the prior information about data distribution ...
Machine Learning Algorithms Computer Simulation Models, Genetic Support Vector Machine Databases, Genetic Models, Statistical Data Mining High-Throughput Nucleotide Sequencing Pattern Recognition, Automated Sequence Alignment Sequence Analysis
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