Gene2EST: a BLAST2 server for searching expressed sequence tag (EST) databases with eukaryotic gene-sized queries

Expressed sequence tags (ESTs) are randomly sequenced cDNA clones. Currently, nearly 3 million human and 2 million mouse ESTs provide valuable resources that enable researchers to investigate the products of gene expression. The EST databases have proven to be useful tools for detecting homologous genes, for exon mapping, revealing differential splicing, etc. With the increasing availability of large amounts of poorly characterised eukaryotic (notably human) genomic sequence, ESTs have now become a vital tool for gene identification, sometimes yielding the only unambiguous evidence for the existence of a gene expression product. However, BLAST-based Web servers available to the general user have not kept pace with these developments and do not provide appropriate tools for querying EST databases with large highly spliced genes, often spanning 50 000–100 000 bases or more. Here we describe Gene2EST (http://woody.embl-heidelberg.de/gene2est/), a server that brings together a set of tools enabling efficient retrieval of ESTs matching large DNA queries and their subsequent analysis. RepeatMasker is used to mask dispersed repetitive sequences (such as Alu elements) in the query, BLAST2 for searching EST databases and Artemis for graphical display of the findings. Gene2EST combines these components into a Web resource targeted at the researcher who wishes to study one or a few genes to a high level of detail.

Google - Security Testing Tool

Using Google as a security testing tool, basic and advanced search techniques using advanced google search operators. Examples of obtaining control over security cameras, VoIP systems, web servers and collecting valuable information as: Credit card details, cvv codes – only using Google.

Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Gestengestützte Schema- und Datenexploration

Der Zugang zu Datenbanken über die universelle Abfragesprache SQL stellt für Nicht-Spezialisten eine große Herausforderung dar. Als eine benutzerfreundliche Alternative wurden daher seit den 1970er-Jahren unterschiedliche visuelle Abfragesprachen (Visual Query Languages, kurz VQLs) für klassische PCs erforscht. Ziel der vorliegenden Arbeit ist es, eine generische VQL zu entwickeln und zu erproben, die eine gestenbasierte Exploration von Datenbanken auf Schema- und Instanzdatenebene für mobile Endgeräte, insbesondere Tablets, ermöglicht. Dafür werden verschiedene Darstellungsformen, Abfragestrategien und visuelle Hints für Fremdschlüsselbeziehungen untersucht, die den Benutzer bei der Navigation durch die Daten unterstützen. Im Rahmen einer Anforderungsanalyse erwies sich die Visualisierung der Daten und Beziehungen mittels einer platzsparenden geschachtelten NF2-Darstellung als besonders vorteilhaft. Zur Steuerung der Datenbankexploration wird eine geeignete Gestensprache, bestehend aus Stroke-, Multitouch- und Mid-Air-Gesten, vorgestellt. Das Gesamtkonzept aus Darstellung und Gestensteuerung wurde anhand des im Rahmen dieser Arbeit entwickelten GBXT-Prototyps auf seine reale Umsetzbarkeit hin, als plattformunabhängige Single-Page-Application für verschiedene mobile Endgeräte mittels JavaScript und HTML5/CSS3 untersucht.

Street lighting mesh network protocol

The digital revolution of the 21st century contributed to stem the Internet of Things (IoT). Trillions of embedded devices using the Internet Protocol (IP), also called smart objects, will be an integral part of the Internet. In order to support such an extremely large address space, a new Internet Protocol, called Internet Protocol Version 6 (IPv6) is being adopted. The IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) has accelerated the integration of WSNs into the Internet. At the same time, the Constrained Application Protocol (CoAP) has made it possible to provide resource constrained devices with RESTful Web services functionalities. This work builds upon previous experience in street lighting networks, for which a proprietary protocol, devised by the Lighting Living Lab, was implemented and used for several years. The proprietary protocol runs on a broad range of lighting control boards. In order to support heterogeneous applications with more demanding communication requirements and to improve the application development process, it was decided to port the Contiki OS to the four channel LED driver (4LD) board from Globaltronic. This thesis describes the work done to adapt the Contiki OS to support the Microchip TM PIC24FJ128GA308 microprocessor and presents an IP based solution to integrate sensors and actuators in smart lighting applications. Besides detailing the system’s architecture and implementation, this thesis presents multiple results showing that the performance of CoAP based resource retrievals in constrained nodes is adequate for supporting networking services in street lighting networks.

Machine learning tools for protein annotation: the cases of transmembrane β-barrel and myristoylated proteins

Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

Deep learning and embeddings for problems of computational biology

The development of Next Generation Sequencing promotes Biology in the Big Data era. The ever-increasing gap between proteins with known sequences and those with a complete functional annotation requires computational methods for automatic structure and functional annotation. My research has been focusing on proteins and led so far to the development of three novel tools, DeepREx, E-SNPs&GO and ISPRED-SEQ, based on Machine and Deep Learning approaches. DeepREx computes the solvent exposure of residues in a protein chain. This problem is relevant for the definition of structural constraints regarding the possible folding of the protein. DeepREx exploits Long Short-Term Memory layers to capture residue-level interactions between positions distant in the sequence, achieving state-of-the-art performances. With DeepRex, I conducted a large-scale analysis investigating the relationship between solvent exposure of a residue and its probability to be pathogenic upon mutation. E-SNPs&GO predicts the pathogenicity of a Single Residue Variation. Variations occurring on a protein sequence can have different effects, possibly leading to the onset of diseases. E-SNPs&GO exploits protein embeddings generated by two novel Protein Language Models (PLMs), as well as a new way of representing functional information coming from the Gene Ontology. The method achieves state-of-the-art performances and is extremely time-efficient when compared to traditional approaches. ISPRED-SEQ predicts the presence of Protein-Protein Interaction sites in a protein sequence. Knowing how a protein interacts with other molecules is crucial for accurate functional characterization. ISPRED-SEQ exploits a convolutional layer to parse local context after embedding the protein sequence with two novel PLMs, greatly surpassing the current state-of-the-art. All methods are published in international journals and are available as user-friendly web servers. They have been developed keeping in mind standard guidelines for FAIRness (FAIR: Findable, Accessible, Interoperable, Reusable) and are integrated into the public collection of tools provided by ELIXIR, the European infrastructure for Bioinformatics.

Decision making models embedded into a web-based tool for assessing pest infestation risk

Current practices in agricultural management involve the application of rules and techniques to ensure high quality and environmentally friendly production. Based on their experience, agricultural technicians and farmers make critical decisions affecting crop growth while considering several interwoven agricultural, technological, environmental, legal and economic factors. In this context, decision support systems and the knowledge models that support them, enable the incorporation of valuable experience into software systems providing support to agricultural technicians to make rapid and effective decisions for efficient crop growth. Pest control is an important issue in agricultural management due to crop yield reductions caused by pests and it involves expert knowledge. This paper presents a formalisation of the pest control problem and the workflow followed by agricultural technicians and farmers in integrated pest management, the crop production strategy that combines different practices for growing healthy crops whilst minimising pesticide use. A generic decision schema for estimating infestation risk of a given pest on a given crop is defined and it acts as a metamodel for the maintenance and extension of the knowledge embedded in a pest management decision support system which is also presented. This software tool has been implemented by integrating a rule-based tool into web-based architecture. Evaluation from validity and usability perspectives concluded that both agricultural technicians and farmers considered it a useful tool in pest control, particularly for training new technicians and inexperienced farmers.

Ferramenta de apoio ao projeto, configuração e gestão de instalações domóticas

Esta dissertação apresenta o trabalho realizado no âmbito da unidade curricular de Tese / Dissertação (TEDI) do Mestrado em Engenharia Eletrotécnica e de Computadores – Especialização em Automação e Sistemas em parceria com a empresa Live Simply, uma empresa de domótica que decidiu apostar na inovação e no desenvolvimento de serviços e produtos de valor acrescentado para consolidar a sua posição no mercado. Neste contexto, foram identificadas como mais-valias para a Live Simply a conceção, por um lado, de uma ferramenta de apoio técnico de integração e simplificação das fases de projeto, configuração e gestão de instalações domóticas e, por outro lado, de uma interface com a instalação para o cliente consultar e alterar, em tempo real, o estado dos atuadores. Depois de analisadas as tecnologias disponíveis, selecionaram-se as soluções a adotar (linguagens de programação, servidores de base de dados e ambientes de desenvolvimento), definiu-se a arquitetura do sistema, detalhando-se os módulos de projeto, configuração e gestão de instalações, a estrutura da base de dados assim como o hardware de controlo da instalação. De seguida, procedeu-se ao desenvolvimento dos módulos de software e à configuração e programação do módulo de hardware. Por último, procedeu-se a um conjunto exaustivo de testes aos diferentes módulos que demonstraram o correto funcionamento da ferramenta e a adequação das tecnologias empregues. A ferramenta de apoio técnico realizada integra as fases do projeto, configuração e gestão de instalações domóticas, permitindo melhorar o desempenho dos técnicos e a resposta aos clientes. A interface oferecida ao dono da instalação é uma interface Web de aspeto amigável e fácil utilização que permite consultar e modificar em tempo real o estado da instalação.

The web feature service: transaction standard: an example of prototype implementation

Trabalho de Projecto apresentado como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Adding SOS Core & transactional profiles support to a web thin client

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

Aplicació web de notícies

Aquesta memòria tracta sobre el procediment de creació d’una aplicació web de notícies. Està dividida en 3 zones, una on usuaris amb permisos d’administració poden penjar notícies per ser visualitzades per tothom, una altra que s’hi accedeix si s’és usuari registrat i permet visualitzar noticies d’altres servidors mitjançant el format de dades RSS, i un tercer apartat de gestió administrativa, incorporar noves notícies, modificar-ne de presents o introduir noves pàgines web que continguin notícies. Els usuaris registrats podran seleccionar el diaris dels quals rebran informació, així com especificar quines temàtiques prefereixen en la cerca de notícies.

Estudio sobre la información de texto contenida en imágenes web

La indexació i la recerca de pàgines web es basa en l’anàlisi de text. La tecnologia actual encara no pot processar d’una manera eficient i suficientment ràpida el text contingut a les imatges de les pàgines web. Aquest fet planteja un problema important d’indexació però també d’inaccessibilitat. Per poder quantificar aquest problema hem desenvolupat una aplicació software que ens permet realitzar un estudi sobre aquesta situació. Hem utilitzat aquest software per analitzar un conjunt de pàgines web representatives de la situació actual a Internet. Aquests resultats obtinguts s’han analitzat i comparat amb estudis anteriors.

Desenvolupament d'una plataforma web per a integrar serveis de neuroimatge al PIC (Port d'Informació Científica)

El projecte ha consistit en el disseny i implementació d'una arquitectura/plataforma d'integració dels serveis d'emmagatzemament i postprocessament d'imatge mèdica que oferix el grup així com la visualització, anonimització, transferència d'arxius... basat en una interfície web com a frontend de la plataforma. Els servis que requereixen interacció gràfica han estat implementats mitjançant tècniques d'exportació d'escriptori remotament a la web i altres s'han implementat per tal que funcionin amb el cluster de màquines del que disposa el PIC.