Clinical and Scientific Computing for the Physical Sciences 2 (SBI122)

30 credits

Aim of this module

This module provides the trainee with the knowledge that underpins the specialist rotations in the work based learning programme.

Advanced Information and communications technology Skills

To ensure that the trainee can apply Information and communications technology (ICT) hardware and software solutions safely within a clinical environment.

Database Management, Data Mining and Modelling

It will enable the trainee to design and develop a database, undertake data mining using a large data set, summarise and present the data, and develop models for biological systems.

Important information

The academic parts of this module will be detailed and communicated to you by your university. Please contact them if you have questions regarding this module and its assessments. The module titles in your MSc may not be exactly identical to the work-based modules shown in the e-portfolio. Your modules will be aligned, however, to ensure that your academic and work-based learning are complimentary.

Learning Outcomes

  1. Develop web-based solutions in a complex networking environment.
  2. Use a range of complex software techniques to solve clinical problems.
  3. Discuss and evaluate the range of issues encountered in the development of novel software engineering solutions in medicine.
  4. Critically evaluate computer models for biological systems.

Indicative Content

Project management

  • Risk management
  • Team management (personnel and technical)
  • Project planning (resource and technical)
  • Education and training
  • Cost estimation
  • Project scheduling

Hosting environments

  • Storage services
    • Backup, Archiving, Business Continuity & Disaster Recovery
    • RAID, SAN
  • Server virtualisation
  • Cloud computing
  • Web services (SOAP & REST)
  • Security and governance for cloud services

 Networking

  • Local and wide area networking, including:
    • Available architectures
    • Performance issues
    • Scalability
    • Bridging versus routing
    • Cabling infrastructure
    • Hubs
    • Traffic management
  • Data Exchange Protocols
  • Data exchange standards – Digital Imaging and Communications in Medicine (DICOM) and Healthcare Level 7 (HL7)
  • Links to hospital administration systems

Software techniques

  • Neural networks and their applications
  • Artificial intelligence and expert systems
  • Image processing software, including image reconstruction and registration
  • Finite element analysis
  • Genetic algorithms

Database management and data mining

  • The relational model of data
  • Implementation of relational databases
  • Advanced SQL programming
  • Query optimisation
  • Concurrency control and transaction management
  • Database performance tuning
  • Distributed relational systems and data replication
  • Columnstore/data warehousing database engines
  • Document-oriented databases (e.g. Lucene)
  • Security considerations
  • Data mining
  • Large data set methodologies
  • Database standards and standards for interoperability and integration
  • Data analysis and presentation

Modelling biological systems

  • Analysis of DNA, protein, biological diversity and molecular interaction data
  • Use of bioinformatics and systems biology databases
  • Data sources and data synthesis.
  • Detailed knowledge and understanding of algorithms in bioinformatics and theoretical systems biology.
  • Monte-Carlo modelling
  • Compartmental modelling