DBMODELING - A database applied to the study of protein targets from genome projects

Genome sequencing efforts are providing us with complete genetic blueprints for hundreds of organisms. We are now faced with assigning, understanding, and modifying the functions of proteins encoded by these genomes. DBMODELING is a relational database of annotated comparative protein structure models and their metabolic pathway characterization, when identified. This procedure was applied to complete genomes such as Mycobacteritum tuberculosis and Xylella fastidiosa. The main interest in the study of metabolic pathways is that some of these pathways are not present in humans, which makes them selective targets for drug design, decreasing the impact of drugs in humans. In the database, there are currently 1116 proteins from two genomes. It can be accessed by any researcher at http://www.biocristalografia.df.ibilce.unesp.br/tools/. This project confirms that homology modeling is a useful tool in structural bioinformatics and that it can be very valuable in annotating genome sequence information, contributing to structural and functional genomics, and analyzing protein-ligand docking.

SKPDB: A structural database of shikimate pathway enzymes

Background: The functional and structural characterisation of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design. The main interest in studying shikimate pathway enzymes involves the fact that they are essential for bacteria but do not occur in humans, making them selective targets for design of drugs that do not directly impact humans.Description: The ShiKimate Pathway DataBase (SKPDB) is a relational database applied to the study of shikimate pathway enzymes in microorganisms and plants. The current database is updated regularly with the addition of new data; there are currently 8902 enzymes of the shikimate pathway from different sources. The database contains extensive information on each enzyme, including detailed descriptions about sequence, references, and structural and functional studies. All files (primary sequence, atomic coordinates and quality scores) are available for downloading. The modeled structures can be viewed using the Jmol program.Conclusions: The SKPDB provides a large number of structural models to be used in docking simulations, virtual screening initiatives and drug design. It is freely accessible at http://lsbzix.rc.unesp.br/skpdb/. © 2010 Arcuri et al; licensee BioMed Central Ltd.

Development of a natural products database from the biodiversity of Brazil

We describe herein the design and development of an innovative tool called the NuBBE database (NuBBEDB), a new Web-based database, which incorporates several classes of secondary metabolites and derivatives from the biodiversity of Brazil. This natural product database incorporates botanical, chemical, pharmacological, and toxicological compound information. The NuBBEDB provides specialized information to the worldwide scientific community and can serve as a useful tool for studies on the multidisciplinary interfaces related to chemistry and biology, including virtual screening, dereplication, metabolomics, and medicinal chemistry. The NuBBEDB site is at http://nubbe.iq.unesp.br/nubbeDB.html. © 2013 The American Chemical Society and American Society of Pharmacognosy.

CARIBTRADE, trade statistics database: user manual

Includes bibliography

Nubbe natural products, source of molecular diversity for the design of new anticancer agents

Pós-graduação em Química - IQ

Apoio à gerência de requisitos de software utilizando Design Rationale

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

BtoxDB: a comprehensive database of protein structural data on toxin-antitoxin systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

SNIIC: a plataforma digital de cultura brasileira sob a perspectiva das convergências entre o Design e a Ciência da Informação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The Use of Factor Analysis in the Development of Hand Sizes for Glove Design

Factor analysis was used to develop a more detailed description of the human hand to be used in the creation of glove sizes; currently gloves sizes are small, medium, and large. The created glove sizes provide glove designers with the ability to create a glove design that can provide fit to the majority of hand variations in both the male and female populations. The research used the American National Survey (ANSUR) data that was collected in 1988. This data contains eighty-six length, width, height, and circumference measurements of the human hand for one thousand male subjects and thirteen hundred female subjects. Eliminating redundant measurements reduced the data to forty-six essential measurements. Factor analysis grouped the variables to form three factors. The factors were used to generate hand sizes by using percentiles along each factor axis. Two different sizing systems were created. The first system contains 125 sizes for male and female. The second system contains 7 sizes for males and 14 sizes for females. The sizing systems were compared to another hand sizing system that was created using the ANSUR database indicating that the systems created using factor analysis provide better fit.

SNIIC: a plataforma digital de cultura brasileira sob a perspectiva das convergências entre o Design e a Ciência da Informação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Supporto alla creazione di un ecosistema di aziende: change management e design thinking - il caso Centergross

Il lavoro tratta la progettazione di un intervento tecnologico e organizzativo in grado di guidare la creazione di un ecosistema di imprese per un distretto commerciale: Centergross (Funo d’Argelato, Bologna). Tale lavoro è stato preparato durante un periodo di Stage della durata di cinque mesi effettuato presso Epoca S.r.l (Bologna) a seguito della necessità, riscontrata dalla direzione del distretto, di ripensare il proprio modello di business. L’obiettivo del progetto di intervento di Epoca è quello di supportare il distretto in questa fase di cambiamento, da “condominio” di imprese autonome a ecosistema, grazie all’identificazione e alla realizzazione di strumenti organizzativi e tecnologici che possano costruire opportunità di sinergie, aumentare la completezza dell’offerta e sfruttare economie di scopo. Per questo è stato realizzato un nuovo sistema informatico (social network e applicazione mobile) in grado di supportare la strategia ed evolvere con essa. La tesi si struttura in tre parti. Nella prima parte, attraverso un’indagine della letteratura di riferimento, si sono indagati i principali modelli di cambiamento organizzativo e il ruolo dei sistemi informativi all’interno delle organizzazione. Un approfondimento circa gli approcci, i processi e la gestione del cambiamento in relazione all’introduzione di un nuovo sistema informativo all’interno delle organizzazioni con riferimento alle tematiche del Business Process Reengineering. La seconda parte è dedicata all’evoluzione del Web con la rivoluzione culturale causata dagli strumenti del web partecipativo, semantico e potenziato: social network e applicazione mobile nello specifico; e all’approccio di progettazione: il Design Thinking. Una tecnica che si prefigge di: trovare il miglior fit fra obiettivi, risorse e tecnologie disponibili; favorire lo sviluppo di nuove idee innovative entrando in empatia con il contesto del problema proponendo soluzioni centrate sui bisogni degli utenti. L’ultima parte del lavoro consiste nella descrizione del caso. Vengono presentate la fase di analisi della situazione attuale e i successivi step di progettazione del sistema informatico: la definizione dei prototipi, la popolazione del database, il modello di dominio, le interfacce utente e le esperienze di navigazione all’interno della piattaforma software proposta. L’approccio prevede che il progetto proceda per iterazioni successive e un adattamento continuo alle esigenze del cliente.

Composite materials design, manufacture and evaluation

Fibre-Reinforced-Plastics are composite materials composed by thin fibres with high mechanical properties, made to work together with a cohesive plastic matrix. The huge advantages of fibre reinforced plastics over traditional materials are their high specific mechanical properties i.e. high stiffness and strength to weight ratios. This kind of composite materials is the most disruptive innovation in the structural materials field seen in recent years and the areas of potential application are still many. However, there are few aspects which limit their growth: on the one hand the information available about their properties and long term behaviour is still scarce, especially if compared with traditional materials for which there has been developed an extended database through years of use and research. On the other hand, the technologies of production are still not as developed as the ones available to form plastics, metals and other traditional materials. A third aspect is that the new properties presented by these materials e.g. their anisotropy, difficult the design of components. This thesis will provide several case-studies with advancements regarding the three limitations mentioned. In particular, the long term mechanical properties have been studied through an experimental analysis of the impact of seawater on GFRP. Regarding production methods, the pre-impregnated cured in autoclave process was considered: a rapid tooling method to produce moulds will be presented, and a study about the production of thick components. Also, two liquid composite moulding methods will be presented, with a case-study regarding a large component with sandwich structure that was produced with the Vacuum-Assisted-Resin-Infusion method, and a case-study regarding a thick con-rod beam that was produced with the Resin-Transfer-Moulding process. The final case-study will analyse the loads acting during the use of a particular sportive component, made with FRP layers and a sandwich structure, practical design rules will be provided.