2db: a Proteomics Database for Storage, Analysis, Presentation, and Retrieval of Information From Mass Spectrometric Experiments

dc.contributor.author Allmer, Jens
dc.contributor.author Kuhlgert, Sebastian
dc.contributor.author Hippler, Michael
dc.date.accessioned 2023-06-16T14:36:01Z
dc.date.available 2023-06-16T14:36:01Z
dc.date.issued 2008
dc.description.abstract Background: The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed. Results: In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application. Conclusion: We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling. Import functionality, automatic protein detection, and summary creation act together to facilitate data analysis. In addition, supporting information for these findings is readily accessible via the graphical user interface provided. The database schema and the implementation, which can easily be installed on virtually any server, can be downloaded in the form of a compressed file from our project webpage. en_US
dc.identifier.doi 10.1186/1471-2105-9-302
dc.identifier.issn 1471-2105
dc.identifier.scopus 2-s2.0-47749112438
dc.identifier.uri https://doi.org/10.1186/1471-2105-9-302
dc.identifier.uri https://hdl.handle.net/20.500.14365/2255
dc.language.iso en en_US
dc.publisher Biomed Central Ltd en_US
dc.relation.ispartof Bmc Bıoınformatıcs en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Polyacrylamide-Gel Electrophoresis en_US
dc.subject Peptide-Identification en_US
dc.subject High-Throughput en_US
dc.subject Protein en_US
dc.subject Tandem en_US
dc.subject Probability en_US
dc.title 2db: a Proteomics Database for Storage, Analysis, Presentation, and Retrieval of Information From Mass Spectrometric Experiments en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Allmer, Jens/0000-0002-2164-7335
gdc.author.id Michael, Hippler/0000-0001-9670-6101
gdc.author.scopusid 24821311300
gdc.author.scopusid 24474544000
gdc.author.scopusid 56254003700
gdc.author.wosid Allmer, Jens/E-2335-2016
gdc.bip.impulseclass C4
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Kuhlgert, Sebastian; Hippler, Michael] Univ Munster, Inst Plant Biochem & Biotechnol, Munster, Germany; [Allmer, Jens] Izmir Univ Econ, Izmir, Turkey en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.volume 9 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W2037371061
gdc.identifier.pmid 18605993
gdc.identifier.wos WOS:000257832600001
gdc.index.type WoS
gdc.index.type Scopus
gdc.index.type PubMed
gdc.oaire.accesstype GOLD
gdc.oaire.diamondjournal false
gdc.oaire.impulse 7.0
gdc.oaire.influence 2.8004865E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Proteomics
gdc.oaire.keywords QH301-705.5
gdc.oaire.keywords Abstracting and Indexing
gdc.oaire.keywords Computer applications to medicine. Medical informatics
gdc.oaire.keywords R858-859.7
gdc.oaire.keywords Data Compression
gdc.oaire.keywords Biochemistry
gdc.oaire.keywords Peptide Mapping
gdc.oaire.keywords Mass Spectrometry
gdc.oaire.keywords Computer Science Applications
gdc.oaire.keywords User-Computer Interface
gdc.oaire.keywords Artificial Intelligence
gdc.oaire.keywords Research Design
gdc.oaire.keywords Animals
gdc.oaire.keywords Database Management Systems
gdc.oaire.keywords Humans
gdc.oaire.keywords Biology (General)
gdc.oaire.keywords Databases, Protein
gdc.oaire.keywords Molecular Biology
gdc.oaire.keywords Software
gdc.oaire.keywords Algorithms
gdc.oaire.popularity 4.798319E-10
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0301 basic medicine
gdc.oaire.sciencefields 0303 health sciences
gdc.oaire.sciencefields 03 medical and health sciences
gdc.openalex.collaboration International
gdc.openalex.fwci 1.14877543
gdc.openalex.normalizedpercentile 0.75
gdc.opencitations.count 8
gdc.plumx.crossrefcites 6
gdc.plumx.mendeley 57
gdc.plumx.pubmedcites 2
gdc.plumx.scopuscites 7
gdc.scopus.citedcount 7
gdc.virtual.author Allmer, Jens
gdc.wos.citedcount 6
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