AIMC Topic:
Cluster Analysis

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iDeLUCS: a deep learning interactive tool for alignment-free clustering of DNA sequences.

Bioinformatics (Oxford, England) Sep 2, 2023
SUMMARY: We present an interactive Deep Learning-based software tool for Unsupervised Clustering of DNA Sequences (iDeLUCS), that detects genomic signatures and uses them to cluster DNA sequences, without the need for sequence alignment or taxonomic ...
Algorithms Base Sequence Archaea Deep Learning Cluster Analysis
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Identification of Sleep Patterns via Clustering of Hypnodensities.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Sleep patterns vary widely between individuals. We explore methods for identifying populations exhibiting similar sleep patterns in an automated fashion using polysomnography data. Our novel approach applies unsupervised machine learning algorithms t...
Sleep Stages Humans Cluster Analysis Polysomnography Neural Networks, Computer Algorithms
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Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement.

Cerebral cortex (New York, N.Y. : 1991) Jun 20, 2023
Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode im...
Humans Brain Unsupervised Machine Learning Electroencephalography Support Vector Machine Cluster Analysis Mental Recall Random Forest Brain-Computer Interfaces Electrodes Memory, Episodic
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Ensemble deep learning of embeddings for clustering multimodal single-cell omics data.

Bioinformatics (Oxford, England) Jun 1, 2023
MOTIVATION: Recent advances in multimodal single-cell omics technologies enable multiple modalities of molecular attributes, such as gene expression, chromatin accessibility, and protein abundance, to be profiled simultaneously at a global level in i...
Cluster Analysis Chromatin Algorithms Deep Learning Single-Cell Analysis
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Application of Supervised and Unsupervised Learning Approaches for Mapping Storage Conditions of Biopharmaceutical Product-A Case Study of Human Serum Albumin.

Journal of chromatographic science May 30, 2023
The stability of biopharmaceutical therapeutics over the storage period/shelf life has been a challenging concern for manufacturers. A noble strategy for mapping best and suitable storage conditions for recombinant human serum albumin (rHSA) in labor...
Serum Albumin, Human Discriminant Analysis Glucose Unsupervised Machine Learning Temperature Humans Cluster Analysis
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A scalable unsupervised learning of scRNAseq data detects rare cells through integration of structure-preserving embedding, clustering and outlier detection.

Briefings in bioinformatics May 19, 2023
Single-cell RNA-seq analysis has become a powerful tool to analyse the transcriptomes of individual cells. In turn, it has fostered the possibility of screening thousands of single cells in parallel. Thus, contrary to the traditional bulk measurement...
Algorithms Gene Expression Profiling Sequence Analysis, RNA Cluster Analysis Unsupervised Machine Learning Single-Cell Analysis Single-Cell Gene Expression Analysis
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Clustering Similar Diagnosis Terms.

Studies in health technology and informatics May 18, 2023
A large clinical diagnosis list is explored with the goal to cluster syntactic variants. A string similarity heuristic is compared with a deep learning-based approach. Levenshtein distance (LD) applied to common words only (not tolerating deviations ...
Natural Language Processing Records Language Cluster Analysis Electronic Health Records
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DIST: spatial transcriptomics enhancement using deep learning.

Briefings in bioinformatics Mar 19, 2023
Spatially resolved transcriptomics technologies enable comprehensive measurement of gene expression patterns in the context of intact tissues. However, existing technologies suffer from either low resolution or shallow sequencing depth. Here, we pres...
Deep Learning Cluster Analysis Gene Expression Profiling Transcriptome
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A noise-robust deep clustering of biomolecular ions improves interpretability of mass spectrometric images.

Bioinformatics (Oxford, England) Feb 3, 2023
MOTIVATION: Mass Spectrometry Imaging (MSI) analyzes complex biological samples such as tissues. It simultaneously characterizes the ions present in the tissue in the form of mass spectra, and the spatial distribution of the ions across the tissue in...
Cluster Analysis Neural Networks, Computer Ions Mass Spectrometry
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Cancer subtyping with heterogeneous multi-omics data via hierarchical multi-kernel learning.

Briefings in bioinformatics Jan 19, 2023
Differentiating cancer subtypes is crucial to guide personalized treatment and improve the prognosis for patients. Integrating multi-omics data can offer a comprehensive landscape of cancer biological process and provide promising ways for cancer dia...
Neoplasms Deep Learning Multiomics Computer Simulation Humans Cluster Analysis Biomarkers, Tumor
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