Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Learning with tangible interfaces

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Definição do conceito de blended learning. Proposta metodológica no quadro da terminologia de base conceptual

Sustentado numa abordagem conceptual da Terminologia, o trabalho de investigação que a seguir se desenvolve visa propor um cenário de resposta à questão: como se define o blended learning no contexto educativo de Ensino Superior Pós-Bolonha? A necessidade de compreender, delimitar e harmonizar o conceito de blended learning no panorama actual do Ensino Superior, resulta do pressuposto de que muito embora proliferem descrições de práticas e modelos para a sua operacionalização de reconhecida qualidade - tal como sucede com outros conceitos sob alçada da educação a distância - a reflexão teórica é ainda insuficiente. Com efeito, para responder à questão supra-colocada, propõe-se o desenho de uma metodologia para construção de uma definição intensional do conceito de blended learning que herde, subsuma e melhore o conhecimento existente, identificado através da análise de texto para fins onomasiológicos e de um processo de elicitação de conhecimento tácito e de negociação discursiva junto de sujeitos especializados. A proposta de desenho metodológico que neste trabalho de esboça escora-se globalmente em três etapas: (1) etapa exploratória do domínio-objecto de estudo; (2) etapa de análise onamasiológica de evidência textual e discursiva; (3) etapa de modelização e de validação de resultados. Pretende-se, em primeiro lugar, através do estudo do espaço conceptual das modalidades de educação que se situam no continuum presença-distância sistematizar e ordenar as visões analisadas, propondo representações de educação presencial, educação a distância, e-learning, educação online, aprendizagem enriquecida por tecnologias e ainda de outras modalidades emergentes. As representações assumem o carácter de proposta aberta e decorrem da necessidade de uma primeira ordenação no sentido de topografrar, delineando - a um nível macro - o possível lugar do conceito de blended learning naquele cenário. Num segundo momento, aprofunda-se e circunscreve-se a análise, depurando a evidência observada, agora reduzida a um conjunto de contextos ricos em informação conceptual – um corpus escrito e oral de definições e descrições de blended learning – identificando candidatas a características essenciais e candidatas a características acidentais. Num terceiro momento, procede-se à modelização do conhecimento, encapsulando-a numa proposta de definição sujeita a um processo iterativo e reflexivo, constituído por um conjunto de ciclos de investigação-acção, os quais reflectem a sequência de interacções entre o terminólogo e sujeitos especializados. Defender-se-á que a experimentação deste desenho revela a produtividade de uma sequência cíclica entre a análise textual e discursiva para fins onomasiológicos, a interacção colaborativa e a introspecção. Por outras palavras, embora a natureza do estudo realizado não permita a generalização, para além da relação diádica de mediação que o terminológo estabelece com o especialista, defende-se a produtividade de um procedimento de acção-reflexão autónomo, solitário e introspectivo, no âmbito da qual o terminólogo se afirma como sujeito conceptualizador, decisor e interventor. Resultam deste percurso uma proposta de definição e de descrição de blended learning em língua portuguesa que acreditamos poder servir diferentes actores da comunidade académica envolvida neste domínio de especialidade.

Cognitive models for the concept of angle

Tese de doutoramento em Filosofia

Modellus: Learning Physics with Mathematical Modelling

Tese de doutoramento em Ciências da Educação, área de Teoria Curricular e Ensino das Ciências

Blended Learning project with Applied Optics. Case study

To show with the case of Applied Optics (AO), the adequacy of blended learning to the teaching/learning process in experimental Science and technology (S&T).

Moodle e ensino-misto (b-learning)

Dissertação de mestrado em Geologia para o ensino

Democratic dialogue and collective learning in the context of self-managed teams

This paper provides a longitudinal, empirical view of the multifaceted and reciprocal processes of organizational learning in a context of self-managed teams. Organizational learning is seen as a social construction between people and actions in a work setting. The notion of learning as situated (Brown & Duguid 1989, Lave& Wenger 1991, Gherardi & al. 1998, Easterby-Smith & Araujo 1999, Abma 2003) opens up the possibility for placing the focus of research on learning in the community rather than in individual learning processes. Further, in studying processes in their social context, we cannot avoid taking power relations into consideration (Contu & Willmott 2003). The study is based on an action research with a methodology close to the ‘democratic dialogue’ presented by Gustavsen (2001). This gives a ground for research into how the learning discourse developed in the case study organization over a period of 5 years, during which time the company abandoned a middle management level of hierarchy and the teams had to figure out how to work as self-managed units. This paper discusses the (re)construction of power relations and its role in organizational learning. Power relations are discussed both in vertical and horizontal work relations. A special emphasis is placed on the dialectic between managerial aims and the space for reflection on the side of employees. I argue that learning is crucial in the search for the limits for empowerment and that these limits are negotiated both in actions and speech. This study unfolds a purpose-oriented learning process, constructing an open dialogue, and describes a favourable context for creative, knowledge building communities.

Concept of Customer Relationship Management as an example of innovation in banking sector

Banks that has introduced CRM system, had to make some difficult changes in their organization in order to become more customer oriented. Beside the pure CRM banks try to adopt other innovative tools related with the core CRM. Some of these solutions are constructed in such a way so that ensured could be also access to the information beside to bank’s organization.

Mobile and web tools for participative learning

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, para a obtenção do grau de Mestre em Engenharia Informática

Competência intercultural: conteúdos culturais na aquisição da língua estrangeira e sua integração didáctica no ensino do alemão

Dissertação apresentada à Faculdade de Ciências Sociais e Humanas da Universidade Nova de Lisboa para obtenção do grau de Doutor em Cultura Alemã.

Adaption of the Creative Commons approach and the roaming concept to spatial data infrastructures (SDI)

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Designing market-based instruments for biodiversity conservation: learning with the Australian experience and evaluating Portugal's potential

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão de Sistemas Ambientais

Aprendizagem autónoma (self-directed learning): relatório de um atelier pedagógico

Educação Médica. 1994, 5(3):178-181.