PamStation® 12
Location: Genomic Center Building E lower floor
Description
The PamStation 12 is a fully automated instrument designed for processing PamChip 4 microarrays. It is controlled by a dedicated computer which comes with advanced software for data analysis, called the BioNavigator. The instrument is CE marked.
Key attributes:
- Fully integrated incubation, washing and image acquisition.
- Dimensions are 49cm (height) x 66cm (width) x 58cm (depth), weight is 82 kgs.
- Instrument is controlled by dedicated computer with proprietory software (included).
- Real-time detection offers unique capability of generating kinetic data on enzyme/substrate interactions.
- Easy to operate, very limited maintenance required.
Features/Specifications
Software
PamGene developed 2 software packages which are installed on the computer that comes with the instrument: Evolve (for running the instrument) and BioNavigator (for data analysis). Bionavigator enables easy data capture and analysis using built-in statistical tools, and uses simple drag-and-drop procedures to compare acquired data to existing external databases. Read more in the BioNavigator section.
Applications:
Pathway Elucidation study
Data analysis workflow for elucidating pathways. Results are uploaded to a pathway tool or enriched with biological information, such as from literature or from recombinant kinase data. In addition to the basic analysis, pathways are ranked by p-values.
Target Discovery study
Data analysis workflow for Identifying targets that, for example, differ between groups. Significant peptides between groups are identified and uploaded to a pathway tool.
Kinase Substrate Identification study
Data analysis workflow for identifying specific peptides for a targeted kinase. In addition to the basic data analysis, quality criteria are checked (concentration dependencies of the kinases, the kinase inhibitors and ATP).
Enzymological study
Data analysis workflow to determine the enzymological parameters of a kinase of interest (Michaelis Menten constants, maximal velocity, mechanism of substrate conversion, etc.).
Diagnostic Biomarker Identification study
Data analysis workflow to evaluate if a specific kinase activity is associated with a disease and stage of a disease. Data analysis workflow for finding biomarkers for the diagnosis and/or disease staging of patients and algorithms to determine the sensitivity and specificity.
Prognosis Biomarker Discovery study
Data analysis workflow for finding biomarkers for identification of cancer patients with good and bad prognosis in order to steer treatment decisions using prediction models such PLS-DA.
Predictive Biomarker Discovery study
Data analysis workflow for finding biomarkers to predict the beneficial effects of medicines. Measurements are enriched with kinase information and prediction models.
Toxicological & Cardiovascular Biomarkers study
Data analysis workflow for finding cardiovascular biomarkers to identify potential toxic side effects of drugs. Measurements are enriched using patient drug response information to help build prediction models.
Toxicological Pathway Studies study
Data analysis workflow for higher throughput and high content profiling of toxicants to understand the mechanism of action. Results are uploaded to a pathway tool or enriched with biological information, such as from literature or from recombinant kinase data.
Biomarkers Classification study
Data analysis workflow for finding biomarkers that identify Non Responder from Responder patients for a specific treatment (kinase inhibitor/chemotherapy). A classification algorithm is employed and the results are presented using PamIndX .
Target Interaction Study study
Data analysis workflow for biomarkers that follow the interaction between compounds/medicines and their target during a clinical trail. In addition to fundamental classification algorithms there is a focus on using the Bionavigator repository.
Clinical Utility Marker study
Data analysis workflow for finding biomarkers with clinical utility. In addition to fundamental classification algorithms there is a focus on integrating data with clinical information.
Tutoring: First time users must order a tutoring session.
