School: Science

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

Please note that given the circumstances of COVID-19, there may be some modifications to the assessment schedule promoted in Handbook for Semester 1 2020 Units. Students will be notified of all approved modifications by Unit Coordinators via email and Unit Blackboard sites. Where changes have been made, these are designed to ensure that you still meet the unit learning outcomes in the context of our adjusted teaching and learning arrangements.

  • Unit Title

    Biological Databases and Data Mining
  • Unit Code

    SCI6150
  • Year

    2020
  • Enrolment Period

    1
  • Version

    1
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr David Luke FIELD

Description

Biological databases provide a critical means for organising and efficiently accessing biological data that can be used. Database mining enables researchers to derive new information from the content of these databases. Data mining is particularly important in the data-driven research field of Systems Biology. This unit introduces students to commonly-used biological databases in the fields of genomics, proteomics, and metabolomics. Basic programming skills will also be introduced, enabling students to more efficiently access data from online biological databases and transform it into meaningful information.

Learning Outcomes

On completion of this unit students should be able to:

  1. Select appropriate online dataset for research outcome.
  2. Interrogate databases using open-source software tools.
  3. Curate and interpret data accessed from databases.
  4. Link data to biological pathways and processes.

Unit Content

  1. Overview of biological databases.
  2. Introduction to online database resources.
  3. Methods for retrieving information contained within databases.
  4. Computational tools to efficiently access databases.
  5. Data cleaning and curation.
  6. Mapping omic data to biological pathways and processes.

Learning Experience

ON-CAMPUS

Students will attend on campus classes as well as engage in learning activities through ECU Blackboard.

JoondalupMount LawleySouth West (Bunbury)
Semester 213 x 1 hour lectureNot OfferedNot Offered
Semester 212 x 3 hour tutorialNot OfferedNot Offered

For more information see the Semester Timetable

ONLINE

Students will engage in learning experiences through ECU Blackboard as well as additional ECU learning technologies.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant Board of Examiners.

ON CAMPUS
TypeDescriptionValue
TestTheory quiz20%
Case StudyDatabase case study40%
ProjectResearch project40%
ONLINE
TypeDescriptionValue
TestTheory quiz20%
Case StudyDatabase case study40%
ProjectResearch project40%

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

SCI6150|1|1

School: Science

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

Please note that given the circumstances of COVID-19, there may be some modifications to the assessment schedule promoted in Handbook for this unit. All assessment changes will be published by 27 July 2020. All students are reminded to check handbook at the beginning of semester to ensure they have the correct outline.

  • Unit Title

    Biological Databases and Data Mining
  • Unit Code

    SCI6150
  • Year

    2020
  • Enrolment Period

    2
  • Version

    1
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr David Luke FIELD

Description

Biological databases provide a critical means for organising and efficiently accessing biological data that can be used. Database mining enables researchers to derive new information from the content of these databases. Data mining is particularly important in the data-driven research field of Systems Biology. This unit introduces students to commonly-used biological databases in the fields of genomics, proteomics, and metabolomics. Basic programming skills will also be introduced, enabling students to more efficiently access data from online biological databases and transform it into meaningful information.

Learning Outcomes

On completion of this unit students should be able to:

  1. Select appropriate online dataset for research outcome.
  2. Interrogate databases using open-source software tools.
  3. Curate and interpret data accessed from databases.
  4. Link data to biological pathways and processes.

Unit Content

  1. Overview of biological databases.
  2. Introduction to online database resources.
  3. Methods for retrieving information contained within databases.
  4. Computational tools to efficiently access databases.
  5. Data cleaning and curation.
  6. Mapping omic data to biological pathways and processes.

Learning Experience

ON-CAMPUS

Students will attend on campus classes as well as engage in learning activities through ECU Blackboard.

JoondalupMount LawleySouth West (Bunbury)
Semester 213 x 1 hour lectureNot OfferedNot Offered
Semester 212 x 3 hour tutorialNot OfferedNot Offered

For more information see the Semester Timetable

ONLINE

Students will engage in learning experiences through ECU Blackboard as well as additional ECU learning technologies.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant Board of Examiners.

ON CAMPUS
TypeDescriptionValue
TestTheory quiz20%
Case StudyDatabase case study40%
ProjectResearch project40%
ONLINE
TypeDescriptionValue
TestTheory quiz20%
Case StudyDatabase case study40%
ProjectResearch project40%

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

SCI6150|1|2