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  1. Article: Applications and Challenges of Machine Learning Methods in Alzheimer's Disease Multi-Source Data Analysis.

    Li, Xiong / Qiu, Yangping / Zhou, Juan / Xie, Ziruo

    Current genomics

    2022  Volume 22, Issue 8, Page(s) 564–582

    Abstract: Background: Recent development in neuroimaging and genetic testing technologies have made it possible to measure pathological features associated with Alzheimer's disease (AD) : Objective: To introduce and summarize the applications and challenges of ...

    Abstract Background: Recent development in neuroimaging and genetic testing technologies have made it possible to measure pathological features associated with Alzheimer's disease (AD)
    Objective: To introduce and summarize the applications and challenges of machine learning methods in Alzheimer's disease multi-source data analysis.
    Methods: The literature selected in the review is obtained from Google Scholar, PubMed, and Web of Science. The keywords of literature retrieval include Alzheimer's disease, bioinformatics, image genetics, genome-wide association research, molecular interaction network, multi-omics data integration, and so on.
    Conclusion: This study comprehensively introduces machine learning-based processing techniques for AD neuroimaging data and then shows the progress of computational analysis methods in omics data, such as the genome, proteome, and so on. Subsequently, machine learning methods for AD imaging analysis are also summarized. Finally, we elaborate on the current emerging technology of multi-modal neuroimaging, multi-omics data joint analysis, and present some outstanding issues and future research directions.
    Language English
    Publishing date 2022-04-07
    Publishing country United Arab Emirates
    Document type Journal Article ; Review
    ZDB-ID 2033677-9
    ISSN 1875-5488 ; 1389-2029
    ISSN (online) 1875-5488
    ISSN 1389-2029
    DOI 10.2174/1389202923666211216163049
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5571: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  2. Article ; Online: An L

    Li, Xiong / Lin, Yangkai / Meng, Xu / Qiu, Yangping / Hu, Bo

    IEEE journal of biomedical and health informatics

    2021  Volume 25, Issue 9, Page(s) 3677–3684

    Abstract: Although the neuroimaging measures build a bridge between genetic variants and disease phenotypes, an assessment of single nucleotide variants changes in brain structure and their clinically influence on the progression of Alzheimer's disease remain ... ...

    Abstract Although the neuroimaging measures build a bridge between genetic variants and disease phenotypes, an assessment of single nucleotide variants changes in brain structure and their clinically influence on the progression of Alzheimer's disease remain largely preliminary. Note that each variant has very weak correlation signal to neuroimaging measures or Alzheimer's disease phenotypes. Therefore, traditional sparse regression-based image genetics approaches confront with unresolvable features, relative high regression error or inapplicability of high-dimensional data. Adopting an [Formula: see text] regularization method, we significantly elevate the regression accuracy of imaging genetics compared with group-sparse multitask regression method. With further analysis on the simulation results, we conclude that multiple regression tasks model may be unsuitable for image genetics. In addition, we carried out a whole genome association analysis between genetic variants (about 388 million loci) and phenotypes (cognition normal, mild cognitive impairment and Alzheimer's disease) with using the [Formula: see text] regularization method. After annotating the effect of all variants by Ensembl Variant Effect Predictor (VEP), our method locates 33 missense variants which can explain 40% phenotype variance. Then, we mapped each missense variant to the nearest gene and carried out pathway enrichment analysis. The Notch signaling pathway and Apoptosis pathway have been reported to be related to the formation of Alzheimer's disease.
    MeSH term(s) Alzheimer Disease/diagnostic imaging ; Alzheimer Disease/genetics ; Brain/diagnostic imaging ; Cognitive Dysfunction/diagnostic imaging ; Cognitive Dysfunction/genetics ; Genome-Wide Association Study ; Humans ; Magnetic Resonance Imaging ; Neuroimaging ; Polymorphism, Single Nucleotide/genetics
    Language English
    Publishing date 2021-09-03
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2695320-1
    ISSN 2168-2208 ; 2168-2194
    ISSN (online) 2168-2208
    ISSN 2168-2194
    DOI 10.1109/JBHI.2021.3093027
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5483: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: Annotating whole genome variants and constructing a multi-classifier based on samples of ADNI.

    Zhou, Juan / Qiu, Yangping / Liu, Xiangyu / Xie, Ziruo / Lv, Shanguo / Peng, Yuanyuan / Li, Xiong

    Frontiers in bioscience (Landmark edition)

    2022  Volume 27, Issue 1, Page(s) 37

    Abstract: Introduction: Alzheimer's disease (AD) is the most common progressive neurodegenerative disorder in the elderly, which will eventually lead to dementia without an effective precaution and treatment. As a typical complex disease, the mechanism of AD's ... ...

    Abstract Introduction: Alzheimer's disease (AD) is the most common progressive neurodegenerative disorder in the elderly, which will eventually lead to dementia without an effective precaution and treatment. As a typical complex disease, the mechanism of AD's occurrence and development still lacks sufficient understanding.
    Research design and methods: In this study, we aim to directly analyze the relationship between DNA variants and phenotypes based on the whole genome sequencing data. Firstly, to enhance the biological meanings of our study, we annotate the deleterious variants and mapped them to nearest protein coding genes. Then, to eliminate the redundant features and reduce the burden of downstream analysis, a multi-objective evaluation strategy based on entropy theory is applied for ranking all candidate genes. Finally, we use multi-classifier XGBoost for classifying unbalanced data composed with 46 AD samples, 483 mild cognitive impairment (MCI) samples and 279 cognitive normal (CN) samples.
    Results: The experimental results on real whole genome sequencing data from Alzheimer's Disease Neuroimaging Initiative (ADNI) show that our method not only has satisfactory classification performance but also finds significance correlation between AD and
    Conclusions: From the experimental results, we demonstrated that the efficacy of our proposed method has practical significance.
    MeSH term(s) Aged ; Alzheimer Disease/genetics ; Brain ; Cognitive Dysfunction ; Humans ; Magnetic Resonance Imaging/methods ; Neuroimaging/methods
    Language English
    Publishing date 2022-01-28
    Publishing country Singapore
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2704569-9
    ISSN 2768-6698 ; 2768-6698
    ISSN (online) 2768-6698
    ISSN 2768-6698
    DOI 10.31083/j.fbl2701037
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: A Novel Three-Stage Framework for Association Analysis Between SNPs and Brain Regions.

    Zhou, Juan / Qiu, Yangping / Chen, Shuo / Liu, Liyue / Liao, Huifa / Chen, Hongli / Lv, Shanguo / Li, Xiong

    Frontiers in genetics

    2020  Volume 11, Page(s) 572350

    Abstract: Motivation: ...

    Abstract Motivation:
    Language English
    Publishing date 2020-09-24
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2020.572350
    Database MEDical Literature Analysis and Retrieval System OnLINE

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