Suchergebnisse - "Bioinformatic and algorithmical studies"

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  1. 1

    Application of Neural Networks for classification of Patau, Edwards, Down, Turner and Klinefelter Syndrome based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics von Catic, Aida, Gurbeta, Lejla, Kurtovic-Kozaric, Amina, Mehmedbasic, Senad, Badnjevic, Almir

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 13.02.2018
    Veröffentlicht in BMC medical genomics (13.02.2018)
    “… Background The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been …”
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    Journal Article
  2. 2

    Machine learning based refined differential gene expression analysis of pediatric sepsis von Abbas, Mostafa, EL-Manzalawy, Yasser

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 28.08.2020
    Veröffentlicht in BMC medical genomics (28.08.2020)
    “… In general, identified differentially expressed genes (DEGs) can be subject to further downstream analysis for obtaining more biological insights such as determining enriched functional pathways or gene ontologies …”
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    Journal Article
  3. 3

    Characterization of disease-specific cellular abundance profiles of chronic inflammatory skin conditions from deconvolution of biopsy samples von Félix Garza, Zandra C., Lenz, Michael, Liebmann, Joerg, Ertaylan, Gökhan, Born, Matthias, Arts, Ilja C. W., Hilbers, Peter A. J., van Riel, Natal A. W.

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 17.08.2019
    Veröffentlicht in BMC medical genomics (17.08.2019)
    “… Background Psoriasis and atopic dermatitis are two inflammatory skin diseases with a high prevalence and a significant burden on the patients. Underlying …”
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    Journal Article
  4. 4

    Genome-wide association study identifies two loci influencing plasma neurofilament light levels von Li, Jie-Qiong, Yuan, Xiang-Zhen, Li, Hai-Yan, Cao, Xi-Peng, Yu, Jin-Tai, Tan, Lan, Chen, Wei-An

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 10.05.2018
    Veröffentlicht in BMC medical genomics (10.05.2018)
    “… ), and 172 patients with AD. All subjects were restricted to non-Hispanic Caucasian derived from the ADNI cohort and met all quality control (QC) criteria …”
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    Journal Article
  5. 5

    Exploring and analysing single cell multi-omics data with VDJView von Samir, Jerome, Rizzetto, Simone, Gupta, Money, Luciani, Fabio

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 18.02.2020
    Veröffentlicht in BMC medical genomics (18.02.2020)
    “… Background Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B …”
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    Journal Article
  6. 6

    Vitamin D related genes in lung development and asthma pathogenesis von Kho, Alvin T, Sharma, Sunita, Qiu, Weiliang, Gaedigk, Roger, Klanderman, Barbara, Niu, Simin, Anderson, Chris, Leeder, James S, Weiss, Scott T, Tantisira, Kelan G

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 05.11.2013
    Veröffentlicht in BMC medical genomics (05.11.2013)
    “… Background Poor maternal vitamin D intake is a risk factor for subsequent childhood asthma, suggesting that in utero changes related to vitamin D responsive …”
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    Journal Article
  7. 7

    Unraveling the molecular heterogeneity in type 2 diabetes: a potential subtype discovery followed by metabolic modeling von Khoshnejat, Maryam, Kavousi, Kaveh, Banaei-Moghaddam, Ali Mohammad, Moosavi-Movahedi, Ali Akbar

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 24.08.2020
    Veröffentlicht in BMC medical genomics (24.08.2020)
    “… Background Type 2 diabetes mellitus (T2DM) is a complex multifactorial disease with a high prevalence worldwide. Insulin resistance and impaired insulin …”
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    Journal Article
  8. 8

    Clinical analysis of germline copy number variation in DMD using a non-conjugate hierarchical Bayesian model von Kozareva, Velina, Stroff, Clayton, Silver, Maxwell, Freidin, Jonathan F., Delaney, Nigel F.

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 20.10.2018
    Veröffentlicht in BMC medical genomics (20.10.2018)
    “… Background Detection of copy number variants (CNVs) is an important aspect of clinical testing for several disorders, including Duchenne muscular dystrophy, …”
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    Journal Article
  9. 9

    Visualization and identification of health space, based on personalized molecular phenotype and treatment response to relevant underlying biological processes von Bouwman, Jildau, Vogels, Jack TWE, Wopereis, Suzan, Rubingh, Carina M, Bijlsma, Sabina, van Ommen, Ben

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 06.01.2012
    Veröffentlicht in BMC medical genomics (06.01.2012)
    “… This makes the effects of treatment difficult to interpret. Methods A statistical visualization method is presented, which analyses and visualizes the effects of treatment in individual subjects …”
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    Journal Article
  10. 10

    Investigation of coordination and order in transcription regulation of innate and adaptive immunity genes in type 1 diabetes von Gao, Shouguo, Wolanyk, Nathaniel, Chen, Ye, Jia, Shuang, Hessner, Martin J., Wang, Xujing

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 31.01.2017
    Veröffentlicht in BMC medical genomics (31.01.2017)
    “… Background Type 1 diabetes (T1D) is an autoimmune disease and extensive evidence has indicated a critical role of both the innate and the adaptive arms of …”
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    Journal Article
  11. 11

    Integrative network analysis reveals different pathophysiological mechanisms of insulin resistance among Caucasians and African Americans von Das, Swapan Kumar, Sharma, Neeraj Kumar, Zhang, Bin

    ISSN: 1755-8794, 1755-8794
    Veröffentlicht: London BioMed Central 07.02.2015
    Veröffentlicht in BMC medical genomics (07.02.2015)
    “… Methods We performed integrative gene network analyses of transcriptomic data in subcutaneous adipose tissue of 99 CA and 37 AA subjects metabolically characterized as non-diabetic, with a range of S I and BMI values …”
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    Journal Article