ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Hours of tutorials: 2 Expository Class: 24 Interactive Classroom: 22 Total: 48
Use languages Spanish, Galician
Type: Ordinary subject Master’s Degree RD 1393/2007 - 822/2021
Departments: Analytical Chemistry, Nutrition and Bromatology, Statistics, Mathematical Analysis and Optimisation
Areas: Analytical Chemistry, Statistics and Operations Research
Center Faculty of Sciences
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
General
OG1. Provide students with advanced, specialized and multidisciplinary training in areas related to Biochemistry and Biotechnology in sectors as diverse as: food, biosanitary, cosmetic, pharmaceutical, environmental and chemical.
OG2. Train students in carrying out work and studies in areas linked to scientific and research activities or aimed at other professional activities such as joining technological companies, working in R&D&i laboratories, in the pharmaceutical industry, agri-food industry , etc.
OG 3. Train future professionals trained to create companies of a technological, innovative or high added value nature.
OG 4. Constitute a complementary master's degree offer to the degrees and masters already existing on the Terra campus and Vida campus, particularly the degree in Biochemistry and the degree in Biotechnology.
GO 5. Take advantage of the material resources and existing infrastructure on both USC campuses. In particular, the recent provision of infrastructure and teaching equipment in the last 2 years, coming from the “Convenio Autonómico para Accións de I+D. 2022 (Acción novos graos)”.
GO 6. Enable the retention of talent so that the human capital captured can be used in the development and dynamism of the Galicia University System research groups and the establishment of solid lines of research.
Specific
OE1. In this course, the student is introduced to the knowledge of the fundamental techniques of experimental design and chemometrics and especially those of greatest significance and application in the laboratory and biochemical work.
OE2. The aim is that the student to be able to plan experiments efficiently, as well as handle biochemical data and extract useful information from them through the use of different statistical software packages.
Theory
Block I. Experimental design.
• Introduction to experimental design: basic principles and models.
• Full factorial designs at 2 levels.
• Fractional factorial designs at 2 levels.
• Other designs.
Block II. Multivariate analysis of biochemical data.
• Chemometrics and multivariate analysis. Introduction and historical development.
• Multivariate visualization techniques. Principal component analysis (PCA) and cluster analysis (HCA).
• Supervised model recognition techniques. Discriminant analysis (LDA and QDA), K nearest neighbors (KNN), Soft independent modeling of class analogy (SIMCA), and artificial neural networks (ANN).
• Multivariate calibration. Partial least squares regression (PLSR) and artificial neural networks (ANN).
Practices
Practice 1.- Design and randomization. Analysis of basic experimental design models.
Practice 2.- Generation of complete and fractional designs at 2 levels. Analysis of the results.
Practice 3.- Other experimental design techniques.
Practice 4.- Visualization methods: space exploration of variables.
Practice 5.- Multivariable analysis. Supervised model recognition techniques: classification.
Practice 6.- Multivariate calibration. Applications.
Basic
Gutiérrez Pulido, H.; De la Vara Salazar (2012). Análisis y diseño de experimentos, 3ª edición. McGraw-Hill Interamericana.
Lawson, J. (2015). Design and Analysis of Experiments with R. CRC Press.
Massart, D.L.; Vandeginste, B.G.M.; Buydens, L.M.C.; De Jong, S.; Lewi, P.J.; Smeyers-Verbeke, J. (1998). Handbook of Chemometrics and Qualimetrics, Parts A and B. Elsevier.
Montgomery, D. (2019). Design and Analysis of Experiments, 10th edition. Wiley.
Complementary
Branco, M.; Cerdá, V. -editors- (2007). Temas avanzados de quimiometría. Colección Materiales Didácticos, nº 125. Universitat de les Illes Balears.
Kuehl, R.O. (2001). Diseño de experimentos: principios estadísticos de diseño y análisis de investigación. Thomson Learning.
Lazic, Z. R. (2004). Design of Experiments in Chemical Engineering: A Practical Guide. Wiley-VCH.
Ramis Ramos, G.; García Álvarez-Coque, M.C (2001). Quimiometría. Ed. Síntesis.
Skills/Abilities
H/D06: Interpret experimental results and identify consistent and inconsistent elements.
H/D07: Apply engineering principles to the design and construction of new biological components or metabolic or signaling pathways.
H/D08: Apply the knowledge acquired in the planning and implementation of research projects.
Competencies
Comp01: Develop the ability to properly organize and plan work, based on a synthesis and analysis that allows decision-making.
Comp04: That students know how to apply theoretical-practical knowledge in a professional manner and are competent in formulating/solving problems in both academic and professional contexts related to Molecular Biosciences.
Knowledge
Con04: Determine the most appropriate analytical or molecular technique (workflow) for a given situation or research objective, in the field of biochemistry and biotechnology.
Con05: Know the quality management procedures in a biochemical laboratory and modern chemometric techniques for multivariate data analysis.
Con07: Know the map of relationships between molecules that are part of the interactome and learn to characterize them.
For the correct acquisition of the skills, the following general set of methodologies has been adopted for the mandatory and optional subjects of the degree:
1) Expository teaching. Including master class, and where appropriate, problems.
2) Interactive teaching. Including practices in a computer classroom, which will be compulsory attendance; numerical problem solving classes and/or practical cases; visits to companies; seminars; tutorials in small groups; and use of the Virtual Campus.
3) Student works. Individual or group work (with or without exposition).
4) Individual tutorials.
The evaluation procedure will take into account the following aspects with the indicated weights (assessed competencies).
1/ Exam on the theoretical contents of the subject: 60%, (Con04, Con05, Con07, Comp1).
2/ Practical exam in computer room 30%, (Comp4, H/D06, H/D07, H/D08)
3/ Attendance and participation in classroom activities: 10%, (Comp4, H/D06, H/D07, H/D08).
The final grade will be obtained as the average of the grades obtained in each of the parts (experimental design and multivariate analysis), understanding that for said average to be made, the grade of each of said parts must be greater than or equal to 4. In case the minimum grade of four is not achieved in one of the parts, the final grade will be the lower value between 4.5 and the average of both blocks.
For cases of fraudulent completion of exercises or tests, the “Regulations for the evaluation of student academic performance and the review of qualifications” will apply or be established.
In relation to the exemption from class attendance, and given the experimental nature of the studies, the granting of an exemption is not contemplated except in absolutely exceptional cases and may only be granted in the absence of other viable alternatives. In the exceptional cases in which the exemption from class attendance is granted by the Degree Committee in accordance with the provisions of the Class Attendance Regulations, students must take into account that in order to pass the subject, it will be necessary to complete the practicals, submit all the continuous assessment activities and pass the corresponding exams.
...................................................HOURS.......PRESENTIALITY (%)
Theoretical teaching..........................24..................100
Interactive teaching seminar................2..................100
Interactive teaching laboratory/
Computer rooma..............................20..................100
Tutorials in small groups.....................2..................100
Personal work of students................102.....................0
It is recommended to keep the subject up to date, attend all the classes and solve the proposed exercises.
The teaching of the subject will be taught in the official languages of Galicia: Spanish and Galician.
Regarding the exemption from class attendance, given the experimental nature of the studies, it will be exceptional, and may only be granted in the absence of other viable alternatives. In the exceptional cases that are granted, students who receive the exemption will be required to do the practicals of the subject, the works that are valued for the continuous assessment, as well as the final exam.
Jose Manuel Colmenero Alvarez
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- josemanuel.colmenero [at] usc.es
- Category
- Professor: LOSU (Organic Law Of University System) Associate University Professor
Luis Alberto Ramil Novo
- Department
- Statistics, Mathematical Analysis and Optimisation
- Area
- Statistics and Operations Research
- l.ramil [at] usc.es
- Category
- Professor: University Lecturer
Carlos Herrero Latorre
Coordinador/a- Department
- Analytical Chemistry, Nutrition and Bromatology
- Area
- Analytical Chemistry
- carlos.herrero [at] usc.es
- Category
- Professor: University Professor
| Tuesday | |||
|---|---|---|---|
| 16:00-17:00 | Grupo /TI-ECTS01 | Spanish | 1P CLASSROOM 1 FIRST FLOOR |
| 17:00-19:00 | Grupo /CLE_01 | Spanish | 1P CLASSROOM 1 FIRST FLOOR |
| Wednesday | |||
| 16:00-18:00 | Grupo /CLE_01 | Spanish | 1P CLASSROOM 1 FIRST FLOOR |
| 01.16.2026 10:00-13:00 | Grupo /CLE_01 | 1P CLASSROOM 5 FIRST FLOOR |
| 01.16.2026 10:00-13:00 | Grupo /CLE_01 | COMPUTER CLASSROOM 4 |
| 06.17.2026 10:00-13:00 | Grupo /CLE_01 | 2P CLASSROOM 4 SECOND FLOOR |
| 06.17.2026 10:00-13:00 | Grupo /CLE_01 | COMPUTER CLASSROOM 1 |