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Bioinformatics

Code: 101951
Credits: 6
2026/2027
Degree programme Type Course
Genetics OB 3

Contact lecturer

Name :
Sònia Casillas Viladerrams
Email :
sonia.casillas@uab.cat

Teaching staff

Antoni Barbadilla Prados
Marta Coronado Zamora
Oscar Conchillo Solé
Jose Francisco Sanchez Herrero
Olga Dolgova Konjushenko

Group languages

You can consult this information at the end of the document.

Prerequisites

It is convenient for the student to review the basic concepts acquired in the subjects of the second grade:

  • The module of Fundamentals of programming within the subject Instrumental Techniques
  • Molecular Genetics of Eukaryotes
  • Molecular Genetics of Prokaryotes
  • Population Genetics

Also, this subject is complemented by the Genomics, proteomics and interactomics course that is done during the same semester, so taking both together is recommended.

Knowledge of English is highly recommended for reading information.

A basic level of any programming language (Python preferably) will be essential to be able to follow the sessions, both theoretical and practical, and complete the proposed activities.

 

Objectives

Bioinformatics -the treatment, computer analysis and the interpretation and modeling of molecular and genomic data- has acquired a fundamental role in genetics nowadays. The subject taught during this course constitutes an introductory vision to bioinformatics. The main objectives are:

  • To provide students with the basic bioinformatics knowledge that will allow them both to use a variety of tools to perform information searches in the databases and to approach the computational analysis of sequences of nucleic acids, proteins and genomes
  • To apply scripting for the automation of bioinformatic tasks that have been previously studied in class, in order to develop computational thinking
  • To give a perspective of the potential of this discipline both in the research and professional shperes

Learning outcomes

  • CM27 (Integrate knowledge about the organisation, structure and study methods of genomics for the resolution of complex biological problems.) Integrate knowledge about the organisation, structure and study methods of genomics for the resolution of complex biological problems.
  • KM22 (Describe experimental technologies and methods for structural and functional analysis of genomes and other omics.) Describe experimental technologies and methods for structural and functional analysis of genomes and other omics.
  • KM23 (Explain the role of genomic techniques in the analysis of intraspecific variability and genotype-phenotype association studies.) Explain the role of genomic techniques in the analysis of intraspecific variability and genotype-phenotype association studies.
  • SM25 (Use bioinformatics tools and databases for the management and analysis of genomic and sequencing data.) Use bioinformatics tools and databases for the management and analysis of genomic and sequencing data.

Contents

Topic 1. Introduction to bioinformatics. Bioinformatics in genomic research. The three corners of bioinformatic analysis. The bioinformatic challenges of data integration.


Topic 2. Databases of interest for biosciences. Bibliographic databases. Construction of search strategies. Molecular databases. Search engines.


Topic 3. Sequence formats. Extraction of sequences from the primary databases. Sequence Formats. Tools for conversion between formats.


Topic 4. Sequence statistics. Sequence visualization, editing and analysis tools. Sequence statistics.


Topic 5. Sequence alignment. Comparison of sequences. Local and global alignment for dynamic programming. Scoring matrices: identity and similarity. Penalties for gaps. Dot-plots.


Topic 6. Similarity searches. Heuristic algorithms for similarity searching against databases: BLAST. Applications of BLAST. Search for remote counterparts using PSI-Blast. Tools for the automation of similarity searches.


Topic 7. Multiple alignment. Multiple sequence alignment. Progressive alignments. Distance matrices. The CLUSTAL package. Applications of multiple alignment. Tools for the automation of multiple alignment. Matrices of position (weight) and LOGOS.


Topic 8. Molecular phylogenetic reconstruction. The molecular phylogeny. Methods of phylogenetic inference. Tools for phylogenetic reconstruction. Examples of phylogenetic reconstruction.


Topic 9. Comparative and functional genomics. Different levels of comparison. Synthenic blocks. Rearrangement hotspots. Comparative view using genome browsers.


Topic 10. Genome assembly. Algorithms for mapping reads against reference genomes. Formats and tools.


Topic 11. Genetic variability. Description of genetic variability from VCF files. Calculation of different measures of variability and tests of neutrality. Databases of SNPs and phenotypes. 


 

Learning activities and methodology

Title Hours ECTS Learning outcomes
Elaboration of works 25 1 CM27, KM22, KM23, SM25
Study 24 0.96 CM27, KM22, KM23, SM25
Tutoring 4 0.16 CM27, KM22, KM23, SM25
Bibliography reading 2 0.08 CM27, KM22, KM23, SM25
Seminars 3 0.12 CM27, KM22, KM23, SM25
Computer room practices 27 1.08 CM27, KM22, KM23, SM25
Theory 25 1 CM27, KM22, KM23, SM25
Computational problem solving 40 1.6 CM27, KM22, KM23, SM25

The teaching methodology includes two types of differentiated activities: classes of theory and practical classes in the computer room. Learning will also have individual and/or collective tutoring of students that will support them to solve specific questions or that they require because of their complexity or difficulty.

Theoretical classes

Classes to transmit the basic concepts and information necessary to develop self-learning. Promotion of active participation of students.

Computer classroom practices

These practices will be organized based on problems posed by teachers that will need to be solved using the different tools and bioinformatics analyzes.

Seminars and/or conferences

In the last sessions of the course there will be seminars and/or conferences of researchers in the field of bioinformatics.

Tutorials

Individuals or small groups for the resolution of doubts related to the subject. This type of activity can be done at the request of the students.

 
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

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Optional problems or the student's own creation Can add up to 1 point on the final grade 0 0 CM27, KM22, KM23, SM25
Partial exam 2 (theoretical-practical contents) 30 0 0 CM27, KM22, KM23, SM25
ADAPT YOURSELF-Bioinformatics (Integrative work) 15 0 0 CM27, KM22, KM23, SM25
Partial exam 1 (theoretical-practical contents) 30 0 0 CM27, KM22, KM23, SM25
Computer room practices Can substract up to 1 point from the final grade 0 0 CM27, KM22, KM23, SM25
ROSALIND-Computational problems 25 0 0 CM27, KM22, KM23, SM25

The evaluation system is organized in five main activities and there will be, in addition, a recovery exam and an optional final improvement activity. The details of the activities are:

Main evaluation activities

  • Partial evaluations (1 and 2). Overall Weight 60%

Partial assessments are combined tests that can consist of multiple-choice questions, written answers and problem solving. These tests will evaluate all the contents taught in the subject in the form of a theoretical-practical test.

The weight of each one of the assessments will be 30%.

In order to pass these evaluations, a minimum grade of 4.0 must be obtained in each of them.

  • ROSALIND-Computational problems. Overall Weight 25%

Throughout the course, professors will present computational problems or issues related to the subject matter that students will have to solve in the form of evaluations.

The continued nature of this assessment means that the subject can not be evaluated unless there is a minimum participation of 50% of the proposed tests.

  • ADAPT YOURSELF-Bioinformatics (integrative work). Overall Weight 15%

This activity is linked to the ADAPT YOURSELF teaching innovation project and gives the option to participate in a learning and service experience in the second semester, recognized with 2 ECTS (https://adaptat.omicsuab.org).

The work will consist of solving a problem that will contain questions related to the different thematic blocks presented during the classes of theory and practices.

These works will be carried out in groups of 3-5 students and are of an autonomous nature. Professors will tutor the work and solve doubtsand questions of approach.

The students will deliver the work following the content guidelines, presentation and deadlines.

This activity is compulsory and non-participation will entail non-evaluation of the subject.

  • Computer classroom practices. They can subtract up to 1 point from the final grade

This activity is compulsory and the absence without justification or non-profit of the activity may substract up to 1 point from the final grade of the subject.

The continuous nature of this assessment means that the subject can not be evaluated unless thereis a minimum participation in 50% of the proposed sessions.

  • Optional problems or the student's own creations, and active participation in class/forum. They can add up to 1 point on the final grade

Throughout the course the professors will propose complex computational problems that will be optional. Their resolution may add up to 1 point on the final grade of the subject.

Retake exam

To be eligible for the retake process, students should have been previously evaluated in a set of activities equaling at least two thirds of the final score of the course.

The evaluations 1 and/or 2 can be retaken individually and the grade, if >=4, will make an average with those passed in the partial exams. In the event that the grade of the retake exam does not reach a minimum of 4.0, it cannot make an average and the student does not pass the subject.

Continuous assessment, integrative work and attendance to the computer classroom practices, due to its continued nature, cannot be retaken.

Improvement of the final qualification

Students who have passed the assessments 1 and 2 and want to improve their final qualification, may opt for a final test. This test will include all of the subject matter. It is not possible to improve the note through works or other types of activities.

The degree of difficulty of this test will correspond to the objective of the test and, therefore, may be superior to that of the partial evaluations.

The student who submits to this test waives the previous qualifications and therefore, the grade of this improvement test will be the one that will prevail in the final grade even though it islowerthan that obtained by partial.

In no case will the students that take this test opt for the qualification of Matrícula d'Honor.

Formula of weighting of the final note

Final note = [(Evaluation 1 x 0.3) +(Evaluation 2 x 0.3) + (ROSALIND x 0.25) + (ADAPT YOURSELF x 0.15)]

Passed

The subject is considered passed if the final grade is > = 5.0

Non-gradable

The student will be graded as "Non-gradable" if the weighthin of all conducted evaluation activities is less than 67% of the final score.

Unique assessment

The unique assessment consists of a single synthesis test in which the contents of the entire theory and practical program of the subject will be evaluated in the form of a theoretical-practical test. The test will consist of multiple-choice questions, written answers and problem solving. The grade obtained in this synthesis test will account for 60%of the final grade of the subject. In order to pass this synthesis test, a minimum grade of 4.0 must be obtained.

The assessment of ROSALIND-Computational Problems and ADAPT YOURSELF-Bioinformatics (integrative work) will follow the same process as the continuous assessment. The grade obtained will account for 25% and 15% of the final grade of the subject, respectively. Students taking the single assessmentcan hand in these two pieces of evidence together on the same day as the one set for the synthesis test.

The single assessment test will coincide with the same date fixed in the calendar for the last partial assessment test and the same recovery system will be applied as for the conventional assessment.

Students who take the single assessment must do the Computer classroom practices (PLAB) in face-to-face sessions and under the same conditions as in the conventional assessment.

Any irregularity committed during an assessment activity (academic misconduct, plagiarism, or improper use of AI, unless such use is expressly authorized in the course guide) that may lead to a significant change in the grade will result in that assessment activity being graded with a 0. If the course guide establishes that obtaining a minimum grade in that assessment activity is an essential requirement to pass the course, or if several irregularities occur in the assessment activities of the same course, the final grade for that course will be 0. In addition, disciplinary proceedings may be initiated against any student who commits any of these irregularities.

Bibliography

Books

MOOCS and online resources:

Software

Basic software

Databases

Analysis tools

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TE) Theory 63 Catalan/Spanish first semester morning-mixed
(PLAB) Practical laboratories 631 Catalan/Spanish first semester morning-mixed
(SEM) Seminars 631 Catalan/Spanish first semester afternoon
(PLAB) Practical laboratories 632 Catalan/Spanish first semester morning-mixed
(PLAB) Practical laboratories 633 Catalan/Spanish first semester afternoon