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Module

CSC3432 : Biomedical Data Analytics (Inactive)

  • Inactive for Year: 2020/21
  • Module Leader(s): Dr Jaume Bacardit
  • Lecturer: Professor Natalio Krasnogor
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 20
ECTS Credits: 10.0

Aims

1.       To familiarise students with the fundamental computational approaches used for tackling biological and biomedical data handling and analysis
2.       To introduce the concepts of algorithm design for biological/biomedical data
3.       To develop skills in algorithm design with an emphasis on solving biological/biomedical problems
4.       To understand the most appropriate type of algorithms for differing analytical problems in biology and biomedicine and to introduce some of the most appropriate implementation strategies.

Outline Of Syllabus

1.       The broad spectrum of data types in biology and biomedicine
2.       Fundamental computational algorithms for the analysis of biological/biomedical data
3.       Basic biological/biomedical algorithm design
4.       Algorithms for sequence assembly and annotation
5.       Sequence alignment
6.       Protein structure prediction
7.       Analysis of high-throughput biological data
8.       Biological network construction

Teaching Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Assessment Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Reading Lists

Timetable