LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 155

Search options

  1. Book ; Online ; E-Book: Big data in omics and imaging

    Xiong, Momiao

    association analysis

    (Chapman & Hall/CRC mathematical and computational biology series)

    2018  

    Author's details Momiao Xiong
    Series title Chapman & Hall/CRC mathematical and computational biology series
    Keywords Biometry/Data processing ; Imaging systems in biology/Statistical methods ; Big data/Statistical methods
    Subject code 610.15195
    Language English
    Size 1 Online-Ressource (xxxii, 668 Seiten), Illustrationen
    Publisher CRC Press
    Publishing place Boca Raton, FL
    Publishing country United States
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT019590189
    ISBN 978-1-4987-2580-4 ; 978-1-315-35341-8 ; 978-1-315-33435-6 ; 978-1-315-37050-7 ; 9781498725781 ; 1-4987-2580-5 ; 1-315-35341-5 ; 1-315-33435-6 ; 1-315-37050-6 ; 1498725783
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    Full text online

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  2. Book ; Online: Epigenetic Biomarker and Personalized Precision Medicine

    Wang, Jiucun / He, Dongyi / Xiong, Momiao / Liu, Yun

    2020  

    Keywords Science: general issues ; Medical genetics ; DNA methylation ; Epigenetic ; Biomarker ; Personalized and Precision Medicine
    Size 1 electronic resource (485 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021231605
    ISBN 9782889661848 ; 2889661849
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Book: Next generation sequencing

    Xiong, Momiao

    (Journal of biomedicine and biotechnology ; 2010, Spec. iss.)

    2010  

    Title variant Next-generation sequencing
    Author's details guest ed.: Momiao Xiong
    Series title Journal of biomedicine and biotechnology ; 2010, Spec. iss.
    Journal of biomedicine & biotechnology
    Collection Journal of biomedicine & biotechnology
    Language English
    Size Getr. Zählung : Ill., graph. Darst.
    Publisher Hindawi
    Publishing place S.l.
    Publishing country United States
    Document type Book
    HBZ-ID HT016906941
    Database Catalogue ZB MED Medicine, Health

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    Zs A 5540 -2010,Spec.iss.- not available for loan Zeitschriften-Lesesaal

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  4. Article: Graphical Learning and Causal Inference for Drug Repurposing.

    Xu, Tao / Zhao, Jinying / Xiong, Momiao

    medRxiv : the preprint server for health sciences

    2023  

    Abstract: Gene expression profiles that connect drug perturbations, disease gene expression signatures, and clinical data are important for discovering potential drug repurposing indications. However, the current approach to gene expression reversal has several ... ...

    Abstract Gene expression profiles that connect drug perturbations, disease gene expression signatures, and clinical data are important for discovering potential drug repurposing indications. However, the current approach to gene expression reversal has several limitations. First, most methods focus on validating the reversal expression of individual genes. Second, there is a lack of causal approaches for identifying drug repurposing candidates. Third, few methods for passing and summarizing information on a graph have been used for drug repurposing analysis, with classical network propagation and gene set enrichment analysis being the most common. Fourth, there is a lack of graph-valued association analysis, with current approaches using real-valued association analysis one gene at a time to reverse abnormal gene expressions to normal gene expressions. To overcome these limitations, we propose a novel causal inference and graph neural network (GNN)-based framework for identifying drug repurposing candidates. We formulated a causal network as a continuous constrained optimization problem and developed a new algorithm for reconstructing large-scale causal networks of up to 1,000 nodes. We conducted large-scale simulations that demonstrated good false positive and false negative rates. To aggregate and summarize information on both nodes and structure from the spatial domain of the causal network, we used directed acyclic graph neural networks (DAGNN). We also developed a new method for graph regression in which both dependent and independent variables are graphs. We used graph regression to measure the degree to which drugs reverse altered gene expressions of disease to normal levels and to select potential drug repurposing candidates. To illustrate the application of our proposed methods for drug repurposing, we applied them to phase I and II L1000 connectivity map perturbational profiles from the Broad Institute LINCS, which consist of gene-expression profiles for thousands of perturbagens at a variety of time points, doses, and cell lines, as well as disease gene expression data under-expressed and over-expressed in response to SARS-CoV-2.
    Language English
    Publishing date 2023-08-02
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.07.29.23293346
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Article: Causal Genomic and Epigenomic Network Analysis emerges as a New Generation of Genetic Studies of Complex Diseases.

    Xiong, Momiao

    Journal of phylogenetics & evolutionary biology

    2015  Volume 3, Issue 2

    Language English
    Publishing date 2015-05-30
    Publishing country United States
    Document type Journal Article
    ISSN 2329-9002
    ISSN 2329-9002
    DOI 10.4172/2329-9002.1000e113
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  6. Article ; Online: Genome-Wide Causation Studies of Complex Diseases.

    Jiao, Rong / Chen, Xiangning / Boerwinkle, Eric / Xiong, Momiao

    Journal of computational biology : a journal of computational molecular cell biology

    2022  Volume 29, Issue 8, Page(s) 908–931

    Abstract: Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), the signals identified by association analysis may not have specific pathological relevance to diseases so that a large ... ...

    Abstract Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), the signals identified by association analysis may not have specific pathological relevance to diseases so that a large fraction of disease-causing genetic variants is still hidden. Association is used to measure dependence between two variables or two sets of variables. GWAS test association between a disease and single-nucleotide polymorphisms (SNPs) (or other genetic variants) across the genome. Association analysis may detect superficial patterns between disease and genetic variants. Association signals provide limited information on the causal mechanism of diseases. The use of association analysis as a major analytical platform for genetic studies of complex diseases is a key issue that may hamper discovery of disease mechanisms, calling into the questions the ability of GWAS to identify loci-underlying diseases. It is time to move beyond association analysis toward techniques, which enables the discovery of the underlying causal genetic structures of complex diseases. To achieve this, we propose the concept of genome-wide causation studies (GWCS) as an alternative to GWAS and develop additive noise models (ANMs) for genetic causation analysis. Type 1 error rates and power of the ANMs in testing causation are presented. We conducted GWCS of schizophrenia. Both simulation and real data analysis show that the proportion of the overlapped association and causation signals is small. Thus, we anticipate that our analysis will stimulate serious discussion of the applicability of GWAS and GWCS.
    MeSH term(s) Computer Simulation ; Genome ; Genome-Wide Association Study/methods ; Humans ; Linkage Disequilibrium ; Polymorphism, Single Nucleotide ; Schizophrenia/genetics
    Language English
    Publishing date 2022-04-22
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2030900-4
    ISSN 1557-8666 ; 1066-5277
    ISSN (online) 1557-8666
    ISSN 1066-5277
    DOI 10.1089/cmb.2021.0676
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  7. Article ; Online: Equilibrium points and their stability of COVID-19 in US.

    Hu, Xiaoxi / Hu, Zixin / Xu, Tao / Zhang, Kai / Lu, Henry H / Zhao, Jinying / Boerwinkle, Eric / Jin, Li / Xiong, Momiao

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 1628

    Abstract: This study aims to develop an advanced mathematic model and investigate when and how will the COVID-19 in the US be evolved to endemic. We employed a nonlinear ordinary differential equations-based model to simulate COVID-19 transmission dynamics, ... ...

    Abstract This study aims to develop an advanced mathematic model and investigate when and how will the COVID-19 in the US be evolved to endemic. We employed a nonlinear ordinary differential equations-based model to simulate COVID-19 transmission dynamics, factoring in vaccination efforts. Multi-stability analysis was performed on daily new infection data from January 12, 2021 to December 12, 2022 across 50 states in the US. Key indices such as eigenvalues and the basic reproduction number were utilized to evaluate stability and investigate how the pandemic COVD-19 will evolve to endemic in the US. The transmissional, recovery, vaccination rates, vaccination effectiveness, eigenvalues and reproduction numbers ([Formula: see text] and [Formula: see text]) in the endemic equilibrium point were estimated. The stability attractor regions for these parameters were identified and ranked. Our multi-stability analysis revealed that while the endemic equilibrium points in the 50 states remain unstable, there is a significant trend towards stable endemicity in the US. The study's stability analysis, coupled with observed epidemiological waves in the US, suggested that the COVID-19 pandemic may not conclude with the virus's eradication. Nevertheless, the virus is gradually becoming endemic. Effectively strategizing vaccine distribution is pivotal for this transition.
    MeSH term(s) Humans ; COVID-19/epidemiology ; Pandemics/prevention & control ; Models, Theoretical ; Nonlinear Dynamics
    Language English
    Publishing date 2024-01-18
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-51729-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  8. Article: Genetic Studies of Complex Diseases in the Sequence Era.

    Xiong, Momiao

    Journal of genetic disorders & disease information

    2012  Volume 1, Issue 1

    Language English
    Publishing date 2012-06-25
    Publishing country United States
    Document type Journal Article
    ISSN 2324-9331
    ISSN 2324-9331
    DOI 10.4172/2327-5790.1000e102
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  9. Article: Application of Causal Inference to Genomic Analysis: Advances in Methodology.

    Hu, Pengfei / Jiao, Rong / Jin, Li / Xiong, Momiao

    Frontiers in genetics

    2018  Volume 9, Page(s) 238

    Abstract: The current paradigm of genomic studies of complex diseases is association and correlation analysis. Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), the identified genetic ...

    Abstract The current paradigm of genomic studies of complex diseases is association and correlation analysis. Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), the identified genetic variants by GWAS can only explain a small proportion of the heritability of complex diseases. A large fraction of genetic variants is still hidden. Association analysis has limited power to unravel mechanisms of complex diseases. It is time to shift the paradigm of genomic analysis from association analysis to causal inference. Causal inference is an essential component for the discovery of mechanism of diseases. This paper will review the major platforms of the genomic analysis in the past and discuss the perspectives of causal inference as a general framework of genomic analysis. In genomic data analysis, we usually consider four types of associations: association of discrete variables (DNA variation) with continuous variables (phenotypes and gene expressions), association of continuous variables (expressions, methylations, and imaging signals) with continuous variables (gene expressions, imaging signals, phenotypes, and physiological traits), association of discrete variables (DNA variation) with binary trait (disease status) and association of continuous variables (gene expressions, methylations, phenotypes, and imaging signals) with binary trait (disease status). In this paper, we will review algorithmic information theory as a general framework for causal discovery and the recent development of statistical methods for causal inference on discrete data, and discuss the possibility of extending the association analysis of discrete variable with disease to the causal analysis for discrete variable and disease.
    Language English
    Publishing date 2018-07-10
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2018.00238
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  10. Article ; Online: Dynamic Model for RNA-seq Data Analysis.

    Li, Lerong / Xiong, Momiao

    BioMed research international

    2015  Volume 2015, Page(s) 916352

    Abstract: By measuring messenger RNA levels for all genes in a sample, RNA-seq provides an attractive option to characterize the global changes in transcription. RNA-seq is becoming the widely used platform for gene expression profiling. However, real ... ...

    Abstract By measuring messenger RNA levels for all genes in a sample, RNA-seq provides an attractive option to characterize the global changes in transcription. RNA-seq is becoming the widely used platform for gene expression profiling. However, real transcription signals in the RNA-seq data are confounded with measurement and sequencing errors and other random biological/technical variation. To extract biologically useful transcription process from the RNA-seq data, we propose to use the second ODE for modeling the RNA-seq data. We use differential principal analysis to develop statistical methods for estimation of location-varying coefficients of the ODE. We validate the accuracy of the ODE model to fit the RNA-seq data by prediction analysis and 5-fold cross validation. To further evaluate the performance of the ODE model for RNA-seq data analysis, we used the location-varying coefficients of the second ODE as features to classify the normal and tumor cells. We demonstrate that even using the ODE model for single gene we can achieve high classification accuracy. We also conduct response analysis to investigate how the transcription process responds to the perturbation of the external signals and identify dozens of genes that are related to cancer.
    MeSH term(s) Animals ; Humans ; Models, Genetic ; Neoplasms/genetics ; Neoplasms/metabolism ; RNA, Messenger/biosynthesis ; RNA, Messenger/genetics ; RNA, Neoplasm/biosynthesis ; RNA, Neoplasm/genetics ; Sequence Analysis, RNA/methods ; Transcription, Genetic
    Chemical Substances RNA, Messenger ; RNA, Neoplasm
    Language English
    Publishing date 2015
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2698540-8
    ISSN 2314-6141 ; 2314-6133
    ISSN (online) 2314-6141
    ISSN 2314-6133
    DOI 10.1155/2015/916352
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

To top