Transcript Intelligent Instrument Control

IIC Information Flow
sample
Step 1
Step 2
N
Interesting ions?
Y
Priority list of interesting ions
Empty priority list?
N
Step 3
N
N
QA/QC?
Peptide identification
Y
Protein identification
External Databases query
Y
IIC Architecture
Intelligent Instrument Control
• Algorithms design
– Design of the MS simulator, Task 1: Hazem
– Spectra Deconvolution (Data filters and noise removal) Task 2:
Mohamed Eltabakh
– Protein/peptide identification Task3: Mingwu
– Other simple algorithms, e.g., priority list,
– IIC design and architecture (API, … ) Dr. Ahmed
– Integrated Access to external databases (protDB to support identification
and other BioDBs to support correlation with other information, for example
interactive proteins, related metabolites, etc.)
• Experimental Simulation
– In silico generation of spectrum, Task 1: Hazem
– Algorithms implementation (simulation)
Intelligent Instrument Control
• Integration with the instrument
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Data collection (API)
Control of the instrument (API)
Actual implementation (algorithms)
Database design:
• Data representation (streams, database)
• Optimized storage of massive data
– Raw data
– Analyzed data
• Experimental settings Dr.
– Selection of a biology system, e.g., yeast
– Two types of experiments
• Target analysis
• Global analysis
Intelligent Instrument Control
• Prediction of upcoming peaks (need more
data to build math model)
• Online data mining
Integrated Access to External Bio-databases
• Context: Informatics tools
– Glycosylated peptide identification
– Non-glycosylated peptide identification
• Goal: Enabling uniform access to different
protein databases
Integrated Access to External Bio-databases
• Tasks
– Database description and organization, and Schema
mediation
– Query Processing
– Data correlation
• E.g., Sequence alignment
• Non-overlapping schemas
• Contradictory information
– Web service enabled access
• Settings: Target databases selection (focus)