Experiment design and multivariate analysis

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; 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/ Subject exam: 60%, (Con04, Con05, Con07, Comp1).
2/ Practices
• Work in practices (student work, practices report, ...): 15%, (Comp4, H/D06, H/D07, H/D08).
• Practical Test: 15%, (Con04, Con05, Con07, Comp1).
3/ Participation in classroom activities: 10%, (Comp4, H/D06, H/D07, H/D08).


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.

...................................................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.