LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 307

Search options

  1. Book ; Online ; Thesis: Tailoring bioinformatics methods for studying the challenges in 16S rRNA gene sequencing data analysis

    Matchado, Monica Steffi [Verfasser] / Baumbach, Jan [Akademischer Betreuer] / Haller, Dirk [Gutachter] / Baumbach, Jan [Gutachter]

    2024  

    Author's details Monica Steffi Matchado ; Gutachter: Dirk Haller, Jan Baumbach ; Betreuer: Jan Baumbach
    Keywords Naturwissenschaften ; Science
    Subject code sg500
    Language English
    Publisher Universitätsbibliothek der TU München
    Publishing place München
    Document type Book ; Online ; Thesis
    Database Digital theses on the web

    Full text 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.

  2. Article: KeyPathwayMineR:

    Mechteridis, Konstantinos / Lauber, Michael / Baumbach, Jan / List, Markus

    Frontiers in genetics

    2022  Volume 12, Page(s) 812853

    Abstract: ... De ... ...

    Abstract De novo
    Language English
    Publishing date 2022-01-31
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2021.812853
    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.

  3. Book ; Online ; Thesis: Leveraging policy setting, impact measurement and privacy technology for an increased implementation of Artificial Intelligence in healthcare

    Wolff, Justus Richard [Verfasser] / Baumbach, Jan [Akademischer Betreuer] / Frischmann, Dimitri [Gutachter] / Baumbach, Jan [Gutachter]

    2023  

    Author's details Justus Richard Wolff ; Gutachter: Dimitri Frischmann, Jan Baumbach ; Betreuer: Jan Baumbach
    Keywords Wirtschaft ; Economics
    Subject code sg330
    Language English
    Publisher Universitätsbibliothek der TU München
    Publishing place München
    Document type Book ; Online ; Thesis
    Database Digital theses on the web

    Full text 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.

  4. Book ; Online ; Thesis: A network-based, multi-omics integration framework for Alzheimer's disease

    Ulmer geb. Wörheide, Maria Anna Verfasser] / Baumbach, Jan [Akademischer Betreuer] / [Suhre, Karsten [Gutachter] / Baumbach, Jan [Gutachter]

    2023  

    Author's details Maria Anna Ulmer geb. Wörheide ; Gutachter: Karsten Suhre, Jan Baumbach ; Betreuer: Jan Baumbach
    Keywords Technische Chemie ; Technical Chemistry
    Subject code sg660
    Language English
    Publisher Universitätsbibliothek der TU München
    Publishing place München
    Document type Book ; Online ; Thesis
    Database Digital theses on the web

    Full text 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 ; Online: Network-based approaches for modeling disease regulation and progression

    Galindez, Gihanna / Sadegh, Sepideh / Baumbach, Jan / Kacprowski, Tim / List, Markus

    Computational and Structural Biotechnology Journal. 2023, v. 21 p.780-795

    2023  

    Abstract: Molecular interaction networks lay the foundation for studying how biological functions are controlled by the complex interplay of genes and proteins. Investigating perturbed processes using biological networks has been instrumental in uncovering ... ...

    Abstract Molecular interaction networks lay the foundation for studying how biological functions are controlled by the complex interplay of genes and proteins. Investigating perturbed processes using biological networks has been instrumental in uncovering mechanisms that underlie complex disease phenotypes. Rapid advances in omics technologies have prompted the generation of high-throughput datasets, enabling large-scale, network-based analyses. Consequently, various modeling techniques, including network enrichment, differential network extraction, and network inference, have proven to be useful for gaining new mechanistic insights. We provide an overview of recent network-based methods and their core ideas to facilitate the discovery of disease modules or candidate mechanisms. Knowledge generated from these computational efforts will benefit biomedical research, especially drug development and precision medicine. We further discuss current challenges and provide perspectives in the field, highlighting the need for more integrative and dynamic network approaches to model disease development and progression.
    Keywords biomedical research ; biotechnology ; data collection ; drug development ; precision medicine ; Network enrichment ; Network inference ; Disease modeling ; Network medidince ; Systems medicine
    Language English
    Size p. 780-795.
    Publishing place Elsevier B.V.
    Document type Article ; Online
    Note Use and reproduction
    ZDB-ID 2694435-2
    ISSN 2001-0370
    ISSN 2001-0370
    DOI 10.1016/j.csbj.2022.12.022
    Database NAL-Catalogue (AGRICOLA)

    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.

  6. Book ; Online ; Thesis: Privacy-aware Artificial Intelligence in Systems Medicine

    Matschinske, Julian Oskar [Verfasser] / Baumbach, Jan [Akademischer Betreuer]

    2023  

    Author's details Julian Oskar Matschinske ; Betreuer: Jan Baumbach
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language English
    Publisher Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
    Publishing place Hamburg
    Document type Book ; Online ; Thesis
    Database Digital theses on the web

    Full text 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.

  7. Article: Network-based approaches for modeling disease regulation and progression.

    Galindez, Gihanna / Sadegh, Sepideh / Baumbach, Jan / Kacprowski, Tim / List, Markus

    Computational and structural biotechnology journal

    2022  Volume 21, Page(s) 780–795

    Abstract: Molecular interaction networks lay the foundation for studying how biological functions are controlled by the complex interplay of genes and proteins. Investigating perturbed processes using biological networks has been instrumental in uncovering ... ...

    Abstract Molecular interaction networks lay the foundation for studying how biological functions are controlled by the complex interplay of genes and proteins. Investigating perturbed processes using biological networks has been instrumental in uncovering mechanisms that underlie complex disease phenotypes. Rapid advances in omics technologies have prompted the generation of high-throughput datasets, enabling large-scale, network-based analyses. Consequently, various modeling techniques, including network enrichment, differential network extraction, and network inference, have proven to be useful for gaining new mechanistic insights. We provide an overview of recent network-based methods and their core ideas to facilitate the discovery of disease modules or candidate mechanisms. Knowledge generated from these computational efforts will benefit biomedical research, especially drug development and precision medicine. We further discuss current challenges and provide perspectives in the field, highlighting the need for more integrative and dynamic network approaches to model disease development and progression.
    Language English
    Publishing date 2022-12-16
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 2694435-2
    ISSN 2001-0370
    ISSN 2001-0370
    DOI 10.1016/j.csbj.2022.12.022
    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 ; Online: A Systematic Review of Tissue and Single Cell Transcriptome/Proteome Studies of the Brain in Multiple Sclerosis.

    Elkjaer, Maria L / Röttger, Richard / Baumbach, Jan / Illes, Zsolt

    Frontiers in immunology

    2022  Volume 13, Page(s) 761225

    Abstract: Multiple sclerosis (MS) is an inflammatory demyelinating and degenerative disease of the central nervous system (CNS). Although inflammatory responses are efficiently treated, therapies for progression are scarce and suboptimal, and biomarkers to predict ...

    Abstract Multiple sclerosis (MS) is an inflammatory demyelinating and degenerative disease of the central nervous system (CNS). Although inflammatory responses are efficiently treated, therapies for progression are scarce and suboptimal, and biomarkers to predict the disease course are insufficient. Cure or preventive measures for MS require knowledge of core pathological events at the site of the tissue damage. Novelties in systems biology have emerged and paved the way for a more fine-grained understanding of key pathological pathways within the CNS, but they have also raised questions still without answers. Here, we systemically review the power of tissue and single-cell/nucleus CNS omics and discuss major gaps of integration into the clinical practice. Systemic search identified 49 transcriptome and 11 proteome studies of the CNS from 1997 till October 2021. Pioneering molecular discoveries indicate that MS affects the whole brain and all resident cell types. Despite inconsistency of results, studies imply increase in transcripts/proteins of semaphorins, heat shock proteins, myelin proteins, apolipoproteins and HLAs. Different lesions are characterized by distinct astrocytic and microglial polarization, altered oligodendrogenesis, and changes in specific neuronal subtypes. In all white matter lesion types,
    MeSH term(s) Brain/pathology ; Humans ; Multiple Sclerosis/genetics ; Multiple Sclerosis/pathology ; Proteome ; Transcriptome ; White Matter/pathology
    Chemical Substances Proteome
    Language English
    Publishing date 2022-03-02
    Publishing country Switzerland
    Document type Research Support, Non-U.S. Gov't ; Systematic Review
    ZDB-ID 2606827-8
    ISSN 1664-3224 ; 1664-3224
    ISSN (online) 1664-3224
    ISSN 1664-3224
    DOI 10.3389/fimmu.2022.761225
    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.

  9. Article: Comprehensive benchmark of differential transcript usage analysis for static and dynamic conditions.

    Lio, Chit Tong / Düz, Tolga / Hoffmann, Markus / Willruth, Lina-Liv / Baumbach, Jan / List, Markus / Tsoy, Olga

    bioRxiv : the preprint server for biology

    2024  

    Abstract: RNA sequencing offers unique insights into transcriptome diversity, and a plethora of tools have been developed to analyze alternative splicing. One important task is to detect changes in the relative transcript abundance in differential transcript usage ...

    Abstract RNA sequencing offers unique insights into transcriptome diversity, and a plethora of tools have been developed to analyze alternative splicing. One important task is to detect changes in the relative transcript abundance in differential transcript usage (DTU) analysis. The choice of the right analysis tool is non-trivial and depends on experimental factors such as the availability of single- or paired-end and bulk or single-cell data. To help users select the most promising tool for their task, we performed a comprehensive benchmark of DTU detection tools. We cover a wide array of experimental settings, using simulated bulk and single-cell RNA-seq data as well as real transcriptomics datasets, including time-series data. Our results suggest that DEXSeq, edgeR, and LimmaDS are better choices for paired-end data, while DSGseq and DEXSeq can be used for single-end data. In single-cell simulation settings, we showed that satuRn performs better than DTUrtle. In addition, we showed that Spycone is optimal for time series DTU/IS analysis based on the evidence provided using GO terms enrichment analysis.
    Language English
    Publishing date 2024-01-15
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.01.14.575548
    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.

  10. Article ; Online: Online in silico validation of disease and gene sets, clusterings or subnetworks with DIGEST.

    Adamowicz, Klaudia / Maier, Andreas / Baumbach, Jan / Blumenthal, David B

    Briefings in bioinformatics

    2022  Volume 23, Issue 4

    Abstract: As the development of new drugs reaches its physical and financial limits, drug repurposing has become more important than ever. For mechanistically grounded drug repurposing, it is crucial to uncover the disease mechanisms and to detect clusters of ... ...

    Abstract As the development of new drugs reaches its physical and financial limits, drug repurposing has become more important than ever. For mechanistically grounded drug repurposing, it is crucial to uncover the disease mechanisms and to detect clusters of mechanistically related diseases. Various methods for computing candidate disease mechanisms and disease clusters exist. However, in the absence of ground truth, in silico validation is challenging. This constitutes a major hurdle toward the adoption of in silico prediction tools by experimentalists who are often hesitant to carry out wet-lab validations for predicted candidate mechanisms without clearly quantified initial plausibility. To address this problem, we present DIGEST (in silico validation of disease and gene sets, clusterings or subnetworks), a Python-based validation tool available as a web interface (https://digest-validation.net), as a stand-alone package or over a REST API. DIGEST greatly facilitates in silico validation of gene and disease sets, clusterings or subnetworks via fully automated pipelines comprising disease and gene ID mapping, enrichment analysis, comparisons of shared genes and variants and background distribution estimation. Moreover, functionality is provided to automatically update the external databases used by the pipelines. DIGEST hence allows the user to assess the statistical significance of candidate mechanisms with regard to functional and genetic coherence and enables the computation of empirical $P$-values with just a few mouse clicks.
    MeSH term(s) Cluster Analysis ; Databases, Factual ; Software
    Language English
    Publishing date 2022-06-23
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2068142-2
    ISSN 1477-4054 ; 1467-5463
    ISSN (online) 1477-4054
    ISSN 1467-5463
    DOI 10.1093/bib/bbac247
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 6262: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

    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