IC091 Optimization of Experiments using Experimental Design and Artificial Neural Networks in Science

Přírodovědecká fakulta
podzim 2013
Rozsah
1/0/0. 1 kr. (plus ukončení). Ukončení: z.
Vyučující
Prof. E.M. Pena-Mendez (přednášející), prof. RNDr. Josef Havel, DrSc. (zástupce)
Garance
prof. RNDr. Josef Havel, DrSc.
Ústav chemie – Chemická sekce – Přírodovědecká fakulta
Dodavatelské pracoviště: Ústav chemie – Chemická sekce – Přírodovědecká fakulta
Předpoklady
Course INNOLEC will be given in English
Omezení zápisu do předmětu
Předmět je otevřen studentům libovolného oboru.
Cíle předmětu
Na konci tohoto kurzu bude student schopen: porozumět a vysvětlit co jsou neuronové sítě ANN; použít informace o ANN ke své práci ke zpracování dat; vytvořit vstupní data a spočítat je ANN; předkládat odůvodněná (argumentačně promyšlená, racionální) rozhodnutí použití ANN v přírodních vědách... ; na základě nabytých znalostí odvodit i postupz pro nová data a jejich zpracování... ; interpretovat litearární data o umělých neuronových sítích a jejích aplikacích ;
Osnova
  • Artificial Neural Networks in Science Prof. Dr. E. M. Pena-Mendez, PhD La Laguna University, La Laguna, Tenerife, Spain Abstract The goal of “Artificial Neural Networks in Science” is to introduce neural networks computing to the students from different branches. Basic theory and mathematical background as well as strategy of use and individual phases: training, verification and prediction will be given but the main aim is via analysing examples from different fields in real life to give the participants also basic practice of ANN use. Therefore, the lectures are combined with practical computing laboratory sessions (informatic room) to gain basic practical experience of ANNs use. Real life applications are related to chemistry, physics, biology and forensic sciences but general ANNs applicability is stressed. The course gives also space to the students to solve their own data and/or problems. Possible participants: students of faculty of science but even those from social sciences. Theory (5 - 6 hrs) 1.- Introduction to neuronal networks computing. History and overview of Artificial Neural Networks (ANN) applications. 2.- ANN basic theory, notation, neuron mode, single-input neuron, transfer functions, multiple-input neuron, network architectures, single and multilayers architectures, ,recurrent networks. 2. SELF ORGANIZING FEATURE MAPS. 3. Classical Statistical analysis vs Neural Networks. 4. OPTIMIZATION in CHEMICAL (BIOLOGICAL) SYSTEMS 4. Application of neural networks for modeling in different fields (Chemistry, Biology, Physics). Computer Practices (15 hours) Lab 1: Supervised Learning 1 Lab 2: Supervised Learning 2 Lab 3: Supervised Learning 3 Lab 4: Unsupervised Learning 1 Consultations Time for personal consulatation and solving participants own data will be assured. Bibliography *Zupan, J., Gasteiger, J., Neural Networks in Chemistry and Drug Design, Wiley VCH, 1999. * J. Havel, E. M. Peña-Méndez, A.Rojas-Hernandez, J-P. Doucet and A. Panaye. Neural Networks for Optimization of high-performance capillary zone electrophoresis methods. A new method using a combination of experimental design and artificial neural networks (ANN). J. Chromatogr. A, 793, 1998, 317-329. * Novotná, H., Vaňhara, J., Tóthová, A., Muráriková, N., Bejdák, P. & Rozkošný, R. Identification and taxonomy of the West Palaearctic species of Tachina Meigen (Tachinidae, Diptera) based on male terminalia and molecular analyses. Entomologica Fennica, 20, 2009, 139-169. * D. Brougham, G. Ivanova, M. Gottschalk, D. M. Collins, A. Eustace, R. O'Connor and J. Havel, Artificial neural networks in metabolomic studies of human lung carcinoma cell lines by in vitro 1H nuclear magnetic resonance of whole cells, J. Biomed. Biotechnol., 2011, ID 158094, 8 pages, doi:10.1155/2011/158094. *Josef Havel; Eladia María Peña Méndez; Alberto Rojas Hernández. ARTIFICIAL NEURAL NETWORKS IN ELECTROPHORESIS. Capillary Electrophoresis and Microchip Capillary Electrophoresis: Principles, Applications and Limitations. Eds. García, C.D. and Carrilho, E.; John Wiley Sons, Inc., Hoboken, NJ, USA. ISBN-10:0470572175, ISBN-13: 978-0470572177 , 2012. *ANN applications in Science. Eladia María Peña Méndez, Marcos Báez Fumero, Josef Havel, Jaromír Vaňhara. Ed. Marcos Báez Fumero and Eladia María Peña Méndez. Depósito Legal, TF 850/2012. GRAFIEXPRESS, S.L., S/C de Tenerife, Spain.
Výukové metody
Přednášky kombinované s praktickým cvičením na počítači
Metody hodnocení
test,kontrola práce na počítači, group discussion
Vyučovací jazyk
Angličtina
Informace učitele
Recommended literature Bibliography *Zupan, J., Gasteiger, J., Neural Networks in Chemistry and Drug Design, Wiley VCH, 1999. * J. Havel, E. M. Peña-Méndez, A.Rojas-Hernandez, J-P. Doucet and A. Panaye. Neural Networks for Optimization of high-performance capillary zone electrophoresis methods. A new method using a combination of experimental design and artificial neural networks (ANN). J. Chromatogr. A, 793, 1998, 317-329. * Novotná, H., Vaňhara, J., Tóthová, A., Muráriková, N., Bejdák, P. & Rozkošný, R. Identification and taxonomy of the West Palaearctic species of Tachina Meigen (Tachinidae, Diptera) based on male terminalia and molecular analyses. Entomologica Fennica, 20, 2009, 139-169. * D. Brougham, G. Ivanova, M. Gottschalk, D. M. Collins, A. Eustace, R. O'Connor and J. Havel, Artificial neural networks in metabolomic studies of human lung carcinoma cell lines by in vitro 1H nuclear magnetic resonance of whole cells, J. Biomed. Biotechnol., 2011, ID 158094, 8 pages, doi:10.1155/2011/158094. *Josef Havel; Eladia María Peña Méndez; Alberto Rojas Hernández. ARTIFICIAL NEURAL NETWORKS IN ELECTROPHORESIS. Capillary Electrophoresis and Microchip Capillary Electrophoresis: Principles, Applications and Limitations. Eds. García, C.D. and Carrilho, E.; John Wiley Sons, Inc., Hoboken, NJ, USA. ISBN-10:0470572175, ISBN-13: 978-0470572177 , 2012. *ANN applications in Science. Eladia María Peña Méndez, Marcos Báez Fumero, Josef Havel, Jaromír Vaňhara. Ed. Marcos Báez Fumero and Eladia María Peña Méndez. Depósito Legal, TF 850/2012. GRAFIEXPRESS, S.L., S/C de Tenerife, Spain.
Další komentáře
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