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  1. Article ; Online: Prediction of peptide mass spectral libraries with machine learning.

    Cox, Jürgen

    Nature biotechnology

    2022  Volume 41, Issue 1, Page(s) 33–43

    Abstract: The recent development of machine learning methods to identify peptides in complex mass spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods for peptide identification, such as search engines and experimental spectral ... ...

    Abstract The recent development of machine learning methods to identify peptides in complex mass spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods for peptide identification, such as search engines and experimental spectral libraries, are being superseded by deep learning models that allow the fragmentation spectra of peptides to be predicted from their amino acid sequence. These new approaches, including recurrent neural networks and convolutional neural networks, use predicted in silico spectral libraries rather than experimental libraries to achieve higher sensitivity and/or specificity in the analysis of proteomics data. Machine learning is galvanizing applications that involve large search spaces, such as immunopeptidomics and proteogenomics. Current challenges in the field include the prediction of spectra for peptides with post-translational modifications and for cross-linked pairs of peptides. Permeation of machine-learning-based spectral prediction into search engines and spectrum-centric data-independent acquisition workflows for diverse peptide classes and measurement conditions will continue to push sensitivity and dynamic range in proteomics applications in the coming years.
    MeSH term(s) Peptide Library ; Tandem Mass Spectrometry ; Peptides/chemistry ; Amino Acid Sequence ; Machine Learning ; Databases, Protein
    Chemical Substances Peptide Library ; Peptides
    Language English
    Publishing date 2022-08-25
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 1311932-1
    ISSN 1546-1696 ; 1087-0156
    ISSN (online) 1546-1696
    ISSN 1087-0156
    DOI 10.1038/s41587-022-01424-w
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  2. Article ; Online: MaxQuant Module for the Identification of Genomic Variants Propagated into Peptides.

    Sinitcyn, Pavel / Gerwien, Maximilian / Cox, Jürgen

    Methods in molecular biology (Clifton, N.J.)

    2022  Volume 2456, Page(s) 339–347

    Abstract: Standard shotgun proteomics data analysis pipelines usually only identify peptides that are encoded in the reference genome. In many situations, it is desirable to identify peptides resulting from non-synonymous variations as well. Here, we present a new ...

    Abstract Standard shotgun proteomics data analysis pipelines usually only identify peptides that are encoded in the reference genome. In many situations, it is desirable to identify peptides resulting from non-synonymous variations as well. Here, we present a new module in the MaxQuant software that takes both DNA and RNA based next-generation sequencing (NGS) data as well as raw proteomics data as input. This allows for the identification of variant peptides that are otherwise missed.
    MeSH term(s) Genomics ; High-Throughput Nucleotide Sequencing ; Peptides/genetics ; Proteomics/methods ; Software
    Chemical Substances Peptides
    Language English
    Publishing date 2022-05-25
    Publishing country United States
    Document type Journal Article
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-2124-0_23
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  3. Article ; Online: Accurate and Automated High-Coverage Identification of Chemically Cross-Linked Peptides with MaxLynx.

    Yılmaz, Şule / Busch, Florian / Nagaraj, Nagarjuna / Cox, Jürgen

    Analytical chemistry

    2022  Volume 94, Issue 3, Page(s) 1608–1617

    Abstract: Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the three-dimensional (3D) structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated ... ...

    Abstract Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the three-dimensional (3D) structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to noncleavable and MS-cleavable cross-linkers. For both, we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For noncleavable peptides, we implemented a novel dipeptide Andromeda score, which is the basis for a computationally efficient
    MeSH term(s) Animals ; Cross-Linking Reagents/chemistry ; Drosophila melanogaster ; Mass Spectrometry/methods ; Peptides/chemistry ; Proteome/analysis ; Software
    Chemical Substances Cross-Linking Reagents ; Peptides ; Proteome
    Language English
    Publishing date 2022-01-11
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.1c03688
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  4. Article ; Online: Perseus plugin "Metis" for metabolic-pathway-centered quantitative multi-omics data analysis for static and time-series experimental designs.

    Hamzeiy, Hamid / Ferretti, Daniela / Robles, Maria S / Cox, Jürgen

    Cell reports methods

    2022  Volume 2, Issue 4, Page(s) 100198

    Abstract: We introduce Metis, a new plugin for the Perseus software aimed at analyzing quantitative multi-omics data based on metabolic pathways. Data from different omics types are connected through reactions of a genome-scale metabolic-pathway reconstruction. ... ...

    Abstract We introduce Metis, a new plugin for the Perseus software aimed at analyzing quantitative multi-omics data based on metabolic pathways. Data from different omics types are connected through reactions of a genome-scale metabolic-pathway reconstruction. Metabolite concentrations connect through the reactants, while transcript, protein, and protein post-translational modification (PTM) data are associated through the enzymes catalyzing the reactions. Supported experimental designs include static comparative studies and time-series data. As an example for the latter, we combine circadian mouse liver multi-omics data and study the contribution of cycles of phosphoproteome and metabolome to enzyme activity regulation. Our analysis resulted in 52 pairs of cycling phosphosites and metabolites connected through a reaction. The time lags between phosphorylation and metabolite peak show non-uniform behavior, indicating a major contribution of phosphorylation in the modulation of enzymatic activity.
    MeSH term(s) Animals ; Mice ; Metabolomics ; Multiomics ; Research Design ; Metabolic Networks and Pathways/genetics ; Proteome/metabolism ; Data Analysis
    Chemical Substances Proteome
    Language English
    Publishing date 2022-04-14
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2667-2375
    ISSN (online) 2667-2375
    DOI 10.1016/j.crmeth.2022.100198
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  5. Article ; Online: Tracing back variations in archaeal ESCRT-based cell division to protein domain architectures.

    Frohn, Béla P / Härtel, Tobias / Cox, Jürgen / Schwille, Petra

    PloS one

    2022  Volume 17, Issue 3, Page(s) e0266395

    Abstract: The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across domains of life suggests that a precursor ESCRT machinery existed ... ...

    Abstract The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across domains of life suggests that a precursor ESCRT machinery existed already at an evolutionary early stage of life, making it a promising candidate for the (re)construction of a minimal cell division machinery. There are, however, only few experimental data about ESCRT machineries in Archaea, due to high technical challenges in cultivation and microscopy. Here, we analyse the proteins of ESCRT machineries in archaea bioinformatically on a protein domain level, to enable mechanistical comparison without such challenging experiments. First, we infer that there are at least three different cell division mechanisms utilizing ESCRT proteins in archaea, probably similar in their constriction mechanisms but different in membrane tethering. Second, we show that ESCRT proteins in the archaeal super-phylum Asgard are highly similar to eukaryotic ESCRT proteins, strengthening the recently developed idea that all Eukaryotes descended from archaea. Third, we reconstruct a plausible evolutionary development of ESCRT machineries and suggest that a simple ESCRT-based constriction machinery existed in the last archaeal common ancestor. These findings not only give very interesting insights into the likely evolution of cell division in Archaea and Eukaryotes, but also offer new research avenues by suggesting hypothesis-driven experiments for both, cell biology and bottom-up synthetic biology.
    MeSH term(s) Archaea/genetics ; Archaea/metabolism ; Cell Division ; Endosomal Sorting Complexes Required for Transport/genetics ; Endosomal Sorting Complexes Required for Transport/metabolism ; Eukaryota/metabolism ; Protein Domains
    Chemical Substances Endosomal Sorting Complexes Required for Transport
    Language English
    Publishing date 2022-03-31
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0266395
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  6. Article ; Online: A Network Module for the Perseus Software for Computational Proteomics Facilitates Proteome Interaction Graph Analysis.

    Rudolph, Jan Daniel / Cox, Jürgen

    Journal of proteome research

    2019  Volume 18, Issue 5, Page(s) 2052–2064

    Abstract: Proteomics data analysis strongly benefits from not studying single proteins in isolation but taking their multivariate interdependence into account. We introduce PerseusNet, the new Perseus network module for the biological analysis of proteomics data. ... ...

    Abstract Proteomics data analysis strongly benefits from not studying single proteins in isolation but taking their multivariate interdependence into account. We introduce PerseusNet, the new Perseus network module for the biological analysis of proteomics data. Proteomics is commonly used to generate networks, e.g., with affinity purification experiments, but networks are also used to explore proteomics data. PerseusNet supports the biomedical researcher for both modes of data analysis with a multitude of activities. For affinity purification, a volcano-plot-based statistical analysis method for network generation is featured which is scalable to large numbers of baits. For posttranslational modifications of proteins, such as phosphorylation, a collection of dedicated network analysis tools helps in elucidating cellular signaling events. Co-expression network analysis of proteomics data adopts established tools from transcriptome co-expression analysis. PerseusNet is extensible through a plugin architecture in a multi-lingual way, integrating analyses in C#, Python, and R, and is freely available at http://www.perseus-framework.org .
    MeSH term(s) Animals ; Computational Biology/methods ; Computational Biology/statistics & numerical data ; Data Interpretation, Statistical ; Gene Regulatory Networks ; Humans ; Mice ; Mouse Embryonic Stem Cells/cytology ; Mouse Embryonic Stem Cells/metabolism ; Neural Stem Cells/cytology ; Neural Stem Cells/metabolism ; Polycomb Repressive Complex 1/genetics ; Polycomb Repressive Complex 1/metabolism ; Polycomb Repressive Complex 2/genetics ; Polycomb Repressive Complex 2/metabolism ; Protein Interaction Mapping/statistics & numerical data ; Protein Processing, Post-Translational ; Proteome/genetics ; Proteome/metabolism ; Software ; Tumor Suppressor Proteins/genetics ; Tumor Suppressor Proteins/metabolism ; Ubiquitin Thiolesterase/genetics ; Ubiquitin Thiolesterase/metabolism ; Ubiquitin-Protein Ligases/genetics ; Ubiquitin-Protein Ligases/metabolism
    Chemical Substances BAP1 protein, mouse ; Eed protein, mouse ; Proteome ; Tumor Suppressor Proteins ; Polycomb Repressive Complex 2 (EC 2.1.1.43) ; Polycomb Repressive Complex 1 (EC 2.3.2.27) ; Rnf2 protein, mouse (EC 2.3.2.27) ; Ubiquitin-Protein Ligases (EC 2.3.2.27) ; Ubiquitin Thiolesterase (EC 3.4.19.12)
    Language English
    Publishing date 2019-04-10
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2078618-9
    ISSN 1535-3907 ; 1535-3893
    ISSN (online) 1535-3907
    ISSN 1535-3893
    DOI 10.1021/acs.jproteome.8b00927
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  7. Article: Accurate and Automated High-Coverage Identification of Chemically Cross-Linked Peptides with MaxLynx

    Yılmaz, Şule / Busch, Florian / Nagaraj, Nagarjuna / Cox, Jürgen

    Analytical chemistry. 2022 Jan. 11, v. 94, no. 3

    2022  

    Abstract: Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the three-dimensional (3D) structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated ... ...

    Abstract Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the three-dimensional (3D) structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to noncleavable and MS-cleavable cross-linkers. For both, we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For noncleavable peptides, we implemented a novel dipeptide Andromeda score, which is the basis for a computationally efficient N-squared search engine. Additionally, partial scores summarize the evidence for the two constituents of the dipeptide individually. A posterior error probability (PEP) based on total and partial scores is used to control false discovery rates (FDRs). For MS-cleavable cross-linkers, a score of signature peaks is combined with the conventional Andromeda score on the cleavage products. The MaxQuant 3D peak detection was improved to ensure more accurate determination of the monoisotopic peak of isotope patterns for heavy molecules, which cross-linked peptides typically are. A wide selection of filtering parameters can replace the manual filtering of identifications, which is often necessary when using other pipelines. On benchmark data sets of synthetic peptides, MaxLynx outperforms all other tested software on data for both types of cross-linkers and on a proteome-wide data set of cross-linked Drosophila melanogaster cell lysate. The workflow also supports ion mobility-enhanced MS data. MaxLynx runs on Windows and Linux, contains an interactive viewer for displaying annotated cross-linked spectra, and is freely available at https://www.maxquant.org/.
    Keywords Andromeda ; Drosophila melanogaster ; analytical chemistry ; computer software ; crosslinking ; data collection ; databases ; dipeptides ; isotopes ; mass spectrometry ; probability ; proteomics ; synthetic peptides
    Language English
    Dates of publication 2022-0111
    Size p. 1608-1617.
    Publishing place American Chemical Society
    Document type Article
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.1c03688
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  8. Article ; Online: Tracing back variations in archaeal ESCRT-based cell division to protein domain architectures.

    Béla P Frohn / Tobias Härtel / Jürgen Cox / Petra Schwille

    PLoS ONE, Vol 17, Iss 3, p e

    2022  Volume 0266395

    Abstract: The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across domains of life suggests that a precursor ESCRT machinery existed ... ...

    Abstract The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across domains of life suggests that a precursor ESCRT machinery existed already at an evolutionary early stage of life, making it a promising candidate for the (re)construction of a minimal cell division machinery. There are, however, only few experimental data about ESCRT machineries in Archaea, due to high technical challenges in cultivation and microscopy. Here, we analyse the proteins of ESCRT machineries in archaea bioinformatically on a protein domain level, to enable mechanistical comparison without such challenging experiments. First, we infer that there are at least three different cell division mechanisms utilizing ESCRT proteins in archaea, probably similar in their constriction mechanisms but different in membrane tethering. Second, we show that ESCRT proteins in the archaeal super-phylum Asgard are highly similar to eukaryotic ESCRT proteins, strengthening the recently developed idea that all Eukaryotes descended from archaea. Third, we reconstruct a plausible evolutionary development of ESCRT machineries and suggest that a simple ESCRT-based constriction machinery existed in the last archaeal common ancestor. These findings not only give very interesting insights into the likely evolution of cell division in Archaea and Eukaryotes, but also offer new research avenues by suggesting hypothesis-driven experiments for both, cell biology and bottom-up synthetic biology.
    Keywords Medicine ; R ; Science ; Q
    Subject code 500
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Isobaric Matching between Runs and Novel PSM-Level Normalization in MaxQuant Strongly Improve Reporter Ion-Based Quantification.

    Yu, Sung-Huan / Kyriakidou, Pelagia / Cox, Jürgen

    Journal of proteome research

    2020  Volume 19, Issue 10, Page(s) 3945–3954

    Abstract: Isobaric labeling has the promise of combining high sample multiplexing with precise quantification. However, normalization issues and the missing value problem of ... ...

    Abstract Isobaric labeling has the promise of combining high sample multiplexing with precise quantification. However, normalization issues and the missing value problem of complete
    MeSH term(s) Chromatography, Liquid ; Ions ; Proteomics ; Software ; Tandem Mass Spectrometry
    Chemical Substances Ions
    Language English
    Publishing date 2020-09-16
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2078618-9
    ISSN 1535-3907 ; 1535-3893
    ISSN (online) 1535-3907
    ISSN 1535-3893
    DOI 10.1021/acs.jproteome.0c00209
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  10. Article ; Online: Assessment of a polygenic hazard score for the onset of pre-clinical Alzheimer's disease.

    Vacher, Michael / Doré, Vincent / Porter, Tenielle / Milicic, Lidija / Villemagne, Victor L / Bourgeat, Pierrick / Burnham, Sam C / Cox, Timothy / Masters, Colin L / Rowe, Christopher C / Fripp, Jurgen / Doecke, James D / Laws, Simon M

    BMC genomics

    2022  Volume 23, Issue 1, Page(s) 401

    Abstract: Background: With a growing number of loci associated with late-onset (sporadic) Alzheimer's disease (AD), the polygenic contribution to AD is now well established. The development of polygenic risk score approaches have shown promising results for ... ...

    Abstract Background: With a growing number of loci associated with late-onset (sporadic) Alzheimer's disease (AD), the polygenic contribution to AD is now well established. The development of polygenic risk score approaches have shown promising results for identifying individuals at higher risk of developing AD, thereby facilitating the development of preventative and therapeutic strategies. A polygenic hazard score (PHS) has been proposed to quantify age-specific genetic risk for AD. In this study, we assessed the predictive power and transferability of this PHS in an independent cohort, to support its clinical utility.
    Results: Using genotype and imaging data from 780 individuals enrolled in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, we investigated associations between the PHS and several AD-related traits, including 1) cross-sectional Aβ-amyloid (Aβ) deposition, 2) longitudinal brain atrophy, 3) longitudinal cognitive decline, 4) age of onset. Except in the cognitive domain, we obtained results that were consistent with previously published findings. The PHS was associated with increased Aβ burden, faster regional brain atrophy and an earlier age of onset.
    Conclusion: Overall, the results support the predictive power of a PHS, however, with only marginal improvement compared to apolipoprotein E alone.
    MeSH term(s) Alzheimer Disease/genetics ; Atrophy ; Australia ; Cross-Sectional Studies ; Humans ; Multifactorial Inheritance
    Language English
    Publishing date 2022-05-26
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041499-7
    ISSN 1471-2164 ; 1471-2164
    ISSN (online) 1471-2164
    ISSN 1471-2164
    DOI 10.1186/s12864-022-08617-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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