AIMC Topic: Sequence Analysis

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Alignment-Free Sequence Comparison: A Systematic Survey From a Machine Learning Perspective.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2023
The encounter of large amounts of biological sequence data generated during the last decades and the algorithmic and hardware improvements have offered the possibility to apply machine learning techniques in bioinformatics. While the machine learning...
Mathematics Sequence Alignment Sequence Analysis Machine Learning Algorithms
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Automated filtering of genome-wide large deletions through an ensemble deep learning framework.

Methods (San Diego, Calif.) Aug 28, 2022
Computational methods based on whole genome linked-reads and short-reads have been successful in genome assembly and detection of structural variants (SVs). Numerous variant callers that rely on linked-reads and short reads can detect genetic variati...
Genome, Human Sequence Analysis Humans High-Throughput Nucleotide Sequencing Deep Learning Base Sequence Sequence Analysis, DNA
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Deep learning of a bacterial and archaeal universal language of life enables transfer learning and illuminates microbial dark matter.

Nature communications May 11, 2022
The majority of microbial genomes have yet to be cultured, and most proteins identified in microbial genomes or environmental sequences cannot be functionally annotated. As a result, current computational approaches to describe microbial systems rely...
Deep Learning Bacteria Genome, Archaeal Genome, Bacterial Sequence Analysis Proteins Archaea
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Genomic sequence analysis of lung infections using artificial intelligence technique.

Interdisciplinary sciences, computational life sciences Feb 8, 2021
Attributable to the modernization of Artificial Intelligence (AI) procedures in healthcare services, various developments including Support Vector Machine (SVM), and profound learning. For example, Convolutional Neural systems (CNN) have prevalently ...
Lung Genomics Support Vector Machine Sequence Analysis
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Machine learning techniques for sequence-based prediction of viral-host interactions between SARS-CoV-2 and human proteins.

Biomedical journal Sep 3, 2020
BACKGROUND: COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-CoV-2 virus, has been declared as a pandemic by the World Health Organization on March 11, 2020. Over 15 million people have already been affected worldwide by COVID-19, resu...
Sequence Analysis Host Microbial Interactions Machine Learning COVID-19 SARS-CoV-2 Proteins Humans
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Accurate classification of membrane protein types based on sequence and evolutionary information using deep learning.

BMC bioinformatics Dec 24, 2019
BACKGROUND: Membrane proteins play an important role in the life activities of organisms. Knowing membrane protein types provides clues for understanding the structure and function of proteins. Though various computational methods for predicting memb...
Deep Learning Computational Biology Membrane Proteins Sequence Analysis
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Modeling aspects of the language of life through transfer-learning protein sequences.

BMC bioinformatics Dec 17, 2019
BACKGROUND: Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning and evolutionary information. However, for some applica...
Sequence Analysis Amino Acid Sequence Databases, Nucleic Acid Proteomics Databases, Protein Machine Learning Proteins Natural Language Processing Computational Biology Neural Networks, Computer
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Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms.

BMC systems biology Apr 5, 2019
BACKGROUND: Identification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (FNAB) of thyroid nodules is challenging. Resultingly, non-cancerous Hürthle lesions were conventionally distinguished from Hürthle cell cancers by hist...
Oxyphil Cells Neoplasms Humans Gene Expression Profiling Machine Learning Genomics Heterozygote Mitochondria Sequence Analysis
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Prediction of RNA-protein interactions by combining deep convolutional neural network with feature selection ensemble method.

Journal of theoretical biology Oct 12, 2018
RNA-protein interaction (RPI) plays an important role in the basic cellular processes of organisms. Unfortunately, due to time and cost constraints, it is difficult for biological experiments to determine the relationship between RNA and protein to a...
Datasets as Topic Sequence Analysis Support Vector Machine RNA Protein Binding Neural Networks, Computer Computational Biology
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Unified Deep Learning Architecture for Modeling Biology Sequence.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2017
Prediction of the spatial structure or function of biological macromolecules based on their sequences remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, long-range interaction, co...
Sequence Analysis Models, Genetic Deep Learning Models, Statistical Computational Biology
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