Universitat Internacional de Catalunya

Introduction to Bioinformatics

Introduction to Bioinformatics
6
13489
2
Second semester
OB
BASIC HEALTH INFORMATICS TOOLS
Main language of instruction: Spanish

Other languages of instruction: Catalan, English

Teaching staff


Dr. CHOROSTECKI, Uciel Pablo - upchorostecki@uic.es

Questions will be answered in person before or after class, or via e-mail.

Teachers:

  • Dr. CHOROSTECKI, Uciel Pablo (upchorostecki@uic.es)

  • Dr. NAJLE, Sebastián Rodrigo (srnajle@uic.es)

  • Dra. MANCINI, Estefania

  • AIRA, Nicolas (naira@uic.es)

Introduction

Large amounts of biomedical data are generated daily, whether from research laboratories, clinical laboratories, or private companies. It is necessary to improve our ability to understand and analyze this type of data to fully leverage its capacity to generate new scientific advances and improve patient care. For those who are not bioinformaticians, handling large amounts of data remains a daunting task.

This course introduces students to the fundamental concepts and tools of bioinformatics, focusing on its applications to understand and solve biological problems. Students will explore structural bioinformatics, omics, databases, and the role of artificial intelligence in biomedical research.

Sustainable Development Goals (SDGs): The course on Introduction to Bioinformatics contributes to the Sustainable Development Goals (SDGs) of the 2030 Agenda, particularly ODS 3, 9, 10, 12, and 17. It does so by promoting health and well-being, fostering biomedical innovation and infrastructure, supporting social equity through access to scientific data, ensuring responsible consumption of computational resources, and encouraging scientific and social progress through global partnerships in data sharing.

Pre-course requirements

To follow this class, previous knowledge in genetics, biomolecules and molecular biology is needed. 

Additional experience with the use of computers, web browsers and the internet and use of spreadsheets software is highly recommended.

Objectives

  • Explain the principles and applications of bioinformatics in biomedicine. 
  • Foster the development of skills in the use of bioinformatics tools for sequence analysis, protein structure modeling, and database management. 
  • Introduce next-generation sequencing (NGS) and omics techniques in clinical and research settings. 
  • Teach students the integration of artificial intelligence in biomedical data analysis.

Competences/Learning outcomes of the degree programme

  • CP05 - Apply biological foundations in the search for practical solutions to health problems, following ethical standards and scientific rigour and respecting fundamental equal rights between men and women, and the promotion of human rights and the values inherent in a peaceful society of democratic values that includes inclusive, non-discriminatory language without stereotypes.
  • HB08 - Use basic bioinformatics tools to analyse the structure and interaction of the main biomolecules, as well as the bioinformatics resources of the field of biomedical research.

Learning outcomes of the subject

At the end of the course, students should be able to:

  • Describe the transition from early computational tools to modern bioinformatics technologies, as well as identify the equipment and software requirements necessary for this discipline.
  • Apply key tools and techniques for the analysis of biological data in the area of human health and biomedicine through the exploration, management, and interpretation of bioinformatic data and algorithms, and of sequence and protein databases.
  • Analyze and apply sequencing and omics technologies in the clinical and research setting, implementing analysis strategies such as NGS and RNA-Seq.
  • Use structural visualization tools and databases to analyze protein structures and their implications in the design of biomedical therapies.
  • Identify and explain machine learning models, the AI workflow, and their applications in biological data analysis, drug discovery, and innovative tools such as AlphaFold and ChatGPT.

Syllabus

  1. 1. Foundations in Bioinformatics

    • Introduction to Bioinformatics: Definition, Scope, and Relevance.

    • History of Computing in Biology: From Early Tools to Modern Bioinformatics.

    • Equipment and Software Requirements: Understanding the computational infrastructure.

    • Data Mining in Bioinformatics: extracting knowledge from data.

    • Key Algorithms: Sequence Alignment (Global vs. Local), BLAST, and Multiple Sequence Alignment.

    • Sequence Databases: Overview of GenBank, RefSeq, and others.

    • Sequencing Strategies: History and Evolution of Sequencing Technologies.

    2. Structural Bioinformatics

    • Introduction: Why Protein Structure is Important.

    • Sequence-Structure-Function Relationship: From primary sequence to 3D folding.

    • Techniques for Visualizing Protein Structures: PyMOL, Chimera, and web viewers.

    • Structural Databases: PDB (Protein Data Bank) and UniProt.

    • Role in Biomedicine: Structure-based drug design and understanding disease mutations.

    • Future of Structural Bioinformatics: The impact of predictive models on biomedicine.

    3. Omics

    • Next-Generation Sequencing (NGS): Historical description, platforms, and techniques.

    • Clinical Applications: From Gene Panels to Whole-Genome Sequencing in human genetics.

    • RNA-Seq: Fundamentals of Gene Expression and its implications for health.

    • RNA-Seq Workflows: Data processing, normalization, and interpretation.

    • Single-Cell Experiments: Introduction to Single-Cell RNA-Seq.

    • Epigenomics and Multi-Omics: Techniques and applications in biomedical research.

    4. Artificial Intelligence

    • A Friendly Introduction to Artificial Intelligence: Concepts and Definitions.

    • Overview of Machine Learning Models: Supervised vs. Unsupervised learning in biology.

    • The Machine Learning Pipeline: From Data Preparation to Model Evaluation.

    • Applications of AI in Biomedicine:

      • Drug Discovery (e.g., ADMETlab).

      • Protein Structure Prediction (e.g., AlphaFold).

      • Large Language Models in Science (e.g., ChatGPT).

    5. Integration

    • Integrating Data Modalities: Combining Omics, Structural data, and Clinical metadata.

    • Systems Biology Approach: Moving from reductionism to holistic analysis.

    • Applied Problem Solving: Case studies integrating Foundations, Structure, Omics, and AI to solve complex biomedical questions.

      

    Practical Sessions

    Laboratory practical sessions will be held in small groups where students will seek to apply the theoretical concepts learned.

    • Data Navigation: Retrieval and Analysis from essential databases.

    • Sequence Analysis: Running alignments and interpreting evolutionary relationships.

    • Structural Visualization: Hands-on molecular modeling.

    • Omics Analysis: Basic workflows for NGS data interpretation.

    AI Implementation: Simple exercises in data preparation and model interpretation.

Teaching and learning activities

In person



Fully in-person modality in the classroom

1. Lectures - 20 hours: presentation of a theoretical topic by the teaching staff.

2. Case Methods (CM) - 28 hours: presentation of a real or hypothetical situation in small groups. Students work together with the teaching staff to solve practical questions. The teaching staff intervenes actively and, if necessary, provides new knowledge.

3. Practical Classes - 12 hours: experimental demonstration in the laboratory on concepts studied in theoretical classes under the supervision of the teaching staff.

4. Virtual Education (VE): online material that students can consult from any computer, at any time, and that will contribute to the learning of concepts related to the subject.

Evaluation systems and criteria

In person



1) Student in first call:

  • Case method and practical sessions: 20%
  • Midterm exam: 30%
  • Final exam: 40%
The teaching staff reserves an additional 10% of the grade to award based on subjective criteria such as involvement, participation, respect for basic rules, etc.  

Multiple Choice Exam Rules: If the exam consists of multiple-choice questions (test type), according to the degree regulations, for every +1 point for a correct answer, points will be deducted for incorrect answers as follows:

  • -0.33 points if there are 4 response options (with one correct).

  • -0.25 points if there are 5 response options (with one correct).

2) Students in their second or later attempt: The case method grade will be maintained, and the final exam will account for 75% of the total grade.

3) Repeat students who wish to retake the midterm exam in the third or fifth session must notify the teaching staff in advance. 

General points to consider about the evaluation system:
  • A minimum grade of 5 on the final exam is required to calculate the overall grade.
  • In addition, to pass the course, a general average of 5 or higher in all evaluations is necessary.
  • Due to the continuous nature of the assessment, it is not possible to pass the course without attending at least 75% of the scheduled sessions.
  • Inappropriate use of electronic devices (such as recording and sharing student or teaching staff content during sessions, or using devices for non-educational purposes) may result in expulsion from the class.
  • The teaching staff reserves up to 10% of the total grade to be awarded based on subjective criteria, such as commitment, participation, compliance with basic rules, etc.

Bibliography and resources

  1. Applied Bioinformatics, 2nd Edition. Springer (2018). ISBN: 978-3-319-68299-0
  2. Biomedical Informatics, 4th Edition. Springer (2014). ISBN:  978-1-4471-4473-1
  3. Fundations of Programming Languages. 2nd Edition. Springer (2017). ISBN: 978-3-319-70789-1
  4. Bioinformatics with Python cookbook, 2nd Edition ISBN-10: 1789344697
  5. H. Wickham. R packages. O'Reailly, Sebastopol, 2015.

Evaluation period

E: exam date | R: revision date | 1: first session | 2: second session:
  • E1 26/05/2026 A16 18:00h
  • E2 30/06/2026 A16 11:00h
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