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MAS8406 : Numeric Skills for Digital Biology

  • Offered for Year: 2021/22
  • Module Leader(s): Dr Aamir Khan
  • Owning School: Mathematics, Statistics and Physics
  • Teaching Location: Newcastle City Campus
Semester 1 Credit Value: 10
ECTS Credits: 5.0


To introduce fundamental statistical and mathematical concepts and techniques of importance in Bioinformatics, Synthetic Biology and Neuroinformatics (collectively referred to as digital biology)

Module Summary

This module provides an introduction to the basic statistics and mathematics skills that you need for computational aspects of biology. The module covers both statistics and aspects of discrete mathematics

Outline Of Syllabus

Introduction to data analysis; probability axioms; combinatorics; conditional probability; discrete probability models; continuous probability models; properties of estimators; sampling distributions; central limit theorem; statistical inference; maximum likelihood estimation.

Set theory; (basic sets,; functions.

Linear algebra.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Structured Guided LearningLecture materials161:0016:00Non-Synchronous (Pre-recorded) Lectures
Guided Independent StudyAssessment preparation and completion110:0010:00Revision and practice for computer based assessment
Scheduled Learning And Teaching ActivitiesLecture41:004:00Present in person tutorial/problems class
Scheduled Learning And Teaching ActivitiesPractical42:008:00Present in person practical
Guided Independent StudyProject work34:0012:00Coursework
Scheduled Learning And Teaching ActivitiesDrop-in/surgery41:004:00Present in person drop-in
Guided Independent StudyIndependent study114:0014:00Background reading
Guided Independent StudyIndependent study162:0032:00Lecture follow up
Teaching Rationale And Relationship

Pre-recorded lectures and set reading are used for the delivery of theory and explanation of methods, illustrated with examples. Practicals are used both for solution of problems and work requiring extensive computation and to give insight into the ideas/methods studied. There is one present-in-person practical session per week to ensure rapid feedback on understanding. There is one present-in-person tutorial each week which are used to help develop the students’ abilities at applying the theory to solving problems and to identify and resolve specific queries raised by students. There is one present-in-person drop-in each week to provide opportunity to ask questions and receive immediate feedback. Students unable to attend PiP will be able to complete the practical work at home and will be able to receive immediate feedback through joining the drop-ins virtually.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Prob solv exercises1M80Mathematical and statistical problem-solving exercises
Computer assessment1M20Computer based assessment (NUMBAS)
Assessment Rationale And Relationship

The module is assessed through coursework and computer based assessment. The tutorials provide formative learning and feedback opportunities.

Reading Lists