Master's Dissertation
Code: 42402 ECTS Credits: 15| Degree | Type | Year |
|---|---|---|
| Bioinformatics | OB | 0 |
Contact
- Name:
- Marta Puig Font
- Email:
- marta.puig@uab.cat
Teachers
- Antoni Barbadilla Prados
- Leonardo Pardo Carrasco
- Miquel Àngel Senar Rosell
- Francisco Jose Rodriguez-Trelles Astruga
- Jean Didier Pierre Marechal
- Angel Gonzalez Wong
- Jaime Martinez Urtaza
- Isaac Salazar Ciudad
- Laura Masgrau Fontanet
- Alex Peralvarez Marin
- Marta Puig Font
- Ṣnia Casillas Viladerrams
- Maria Cinta Pegueroles Queralt
- Xavier Daura Ribera
Teaching groups languages
You can view this information at the end of this document.
Prerequisites
To study this module it is necessary to have passed previously the two mandatory modules (Programming in Bioinformatics and Core Bioinformatics) and one of the optative modules.
It is recommended you have a Level B2 of English or equivalent.
Objectives and Contextualisation
The Master’s Thesis (MT) is an autonomous and individually research work that gives the student the opportunity to focus on some of the topics dealt with in the academic modules of the Master, as well as, to integrate all together the capacities and competences achieved along the Master’s degree.
The MT must show that the student is capable of carrying out sound and rigorous academic research. It should present an original argument that is carefully documented from primary and secondary sources. The student must do the work themselves with the guide of an advisor. The MT does not imply a practice internship nor the collaboration of the student in a research group or department. However, the work can be related to the project developed by the student during the Professional Practice Module.
Competences
- Apply research results to obtain new good and services valuating their industrial and commercial viability to transfer them to society.
- Communicate research results clearly and effectively in English.
- Conceive, design and carry out scientific, technical or industrial projects in biocomputing and be able to interpret and extract knowledge from them.
- Design and apply scientific methodology in resolving problems.
- Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
- Propose biocomputing solutions for problems deriving from omic research.
- Propose innovative and creative solutions in the field of study
- Students should be able to integrate knowledge and face the complexity of making judgements based on information that may be incomplete or limited and includes reflections on the social and ethical responsibilities associated with the application of their knowledge and judgements
- Students should know how to apply the knowledge they have acquired and their capacity for problem solving in new or little known fields within wider (or multidisciplinary) contexts related to the area of study
- Students should know how to communicate their conclusions, knowledge and final reasoning that they hold in front of specialist and non-specialist audiences clearly and unambiguously
- Use and manage bibliographical information and computer resources in the area of study
- Work individually and as part of a team in an international and multidisciplinary context.
Learning Outcomes
- Apply research results to obtain new good and services valuating their industrial and commercial viability to transfer them to society.
- Communicate research results clearly and effectively in English.
- Design and apply scientific methodology in resolving problems.
- Design and carry out a project for bioinformatics research.
- Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
- Propose innovative and creative solutions in the field of study
- Students should be able to integrate knowledge and face the complexity of making judgements based on information that may be incomplete or limited and includes reflections on the social and ethical responsibilities associated with the application of their knowledge and judgements
- Students should know how to apply the knowledge they have acquired and their capacity for problem solving in new or little known fields within wider (or multidisciplinary) contexts related to the area of study
- Students should know how to communicate their conclusions, knowledge and final reasoning that they hold in front of specialist and non-specialist audiences clearly and unambiguously
- Use and manage bibliographical information and computer resources in the area of study
- Use the history of biocomputing and other related disciplines (computational biology, synthetic biology, systems biology, among others) to synthesise the current and future scope of the discipline.
- Work individually and as part of a team in an international and multidisciplinary context.
Content
There will be a workshop/lecture about how to write a Master's Thesis.
Activities and Methodology
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Supervised | |||
| Regular meetings with the supervisor | 10 | 0.4 | |
| Type: Autonomous | |||
| Elaboration of the Master Thesis document | 365 | 14.6 |
The Master Thesis (MT) must show that the student is capable of carrying out sound and rigorous academic research. It should present an original argument that is carefully documented from primary and secondary sources. The students must do the work by themselves with the guide of an advisor.
The coordination the MT module appoints an academic tutor from the UAB to each student of the master, depending on the topic of their work.
The MT must be written under the guidance of an advisor (the academic tutor). The advisor has to be a PhD professor from a department or a research centre of the UAB. The academic tutor will supervise the student’s follow-up, providing general guidance, and helping the student to refine the objective of the work and to develop the argument of the thesis. Once the student has met the academic tutor, they will agree on a timetable for meetings and submission of drafts.
The Master’s Thesis Module is scheduled on the second term of the course and involves 375 hours of student work including the tutoring hours with the advisor. These tutoring hours will take place during several meetings, and at least 3 meetings are recommended (an initial meeting, a progress meeting and a final meeting).
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Assessment
Continous Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Master Thesis Document | 50% | 0 | 0 | 1, 2, 3, 4, 6, 8, 9, 7, 11, 5, 12, 10 |
| Oral presentation | 50% | 0 | 0 | 1, 2, 3, 4, 6, 8, 9, 7, 11, 5, 12, 10 |
To evaluate the Master Thesis (MT), the student has to deliver three printed copies of the work to the Master's Coordination and present orally the results to the Master Thesis Committee.
The final assessment will result of:
- The MT written document (50%)
- The oral exposition and defense of the MT (50%)
The MT document must not exceed 15,000 words, excluding appendices and bibliography. It must be written in English.
The MT Committee will consist of three PhD members and UAB professors. The MT defense will be in Englisht and it will include:
- The student’s turn: the student exposes their work during 15 minutes approximately.
- Question time: The three committee members ask questions during approximately 10 minutes to evaluate the exposed thesis.
Students will obtain the grade of "Not assessed" when the evaluated activities have a weight of less than 67% in the final grade.
Use of AI
For this subject, the use of Artificial Intelligence (AI) technologies is allowed exclusively in support tasks, such as bibliographic or information search, text correction or translations. The student must identify clearly which parts have been generated with this technology, specify the tools used, and include a critical reflection on how they have influenced the process and the final result of the activity. Non-transparency of the use of AI in this activity or its use for tasks where this is not allowed will be considered a lack of academic honesty and may result in a partial or total penalty in the grade of the activity, or greater penalties in serious cases.
Bibliography
Readings
- What is considered plagiarism:
- Editorial (2017) Responsible referencing Nature Methods 2017 14:209
Videos
Software
- Software for creating reference lists
- PowerPoint
- Prezi
Groups and Languages
Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.