ProteinCenter™ Data Interpretation Software
ProteinCenter™ is a web-based data interpretation tool that enables scientists to compare and interpret data sets in minutes instead of months ProteinCenter is a web-based tool that enables scientists to compare and interpret proteomics data sets in minutes and overcomes the hurdle of proteins existing under different names and accession keys in different databases. Regularly updated from all major protein databases, ProteinC…
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ProteinCenter™ is a web-based data interpretation tool that enables scientists to compare and interpret data sets in minutes instead of months
ProteinCenter is a web-based tool that enables scientists to compare and interpret proteomics data sets in minutes and overcomes the hurdle of proteins existing under different names and accession keys in different databases. Regularly updated from all major protein databases, ProteinCenter provides a consolidated, biologically annotated, protein sequence database to enable filtering, clustering and statistical bioinformatic analysis from single, combined or comparison data sets.
ProteinCenter enables filtering, clustering and statistical bioinformatics analysis utilizing a regularly updated, consolidated protein sequence database containing >10 million non-redundant proteins.
ProteinCenter™ Data Interpretation Software Features:
- Reveal the biological context of data set comparisons - independent of search engine and database
- Reveal the biological context of each data set
- Reveal the biological context in quantitative studies
- Reveal the biological context for a single protein
An Information System Enabling the Organization and Automatic Annotation of Proteomic Experiments with User-Specific Proteins
Researchers studying engineered proteins or other proteins not defined in public sequence repositories wish to quantitatively analyze and annotate their results in the same manner as with publicly known sequences. Thermo Scientific™ ProteinCenter™ software provides an annotation framework allowing the interpretation of proteomics results in a biological context using established protein databases and annotated sequence variants, including proteoforms. To demonstrate the new functionalities of ProteinCenter we show a differential analysis from an interactomics study using a proximity-dependent strategy where a point-mutation is expected to interfere with biologically relevant interactions.
