Strategies for digital preservation of information

With the advent of the digital era, the digital information produced has grown exponentially. According to Seamus Ross, digital information is a cultural product [1]. The growing dependency on digital information is changing the way our culture is recorded. There is no longer a strict relation between the logical structure of information, the physical storage support and its interpretation. Internet provided the right environment not only for the thriving of new communities but also for the growth of the information produced by them. Software and hardware have also evolved. Along with them came new capabilities of producing more accurate and space demanding information. One good example is multimedia content, audio and video, but there are many more. This new reality rose an awareness for the need to preserve all this information for future generations to come. Unlike their analogue peers, digital formats require a different effort to maintain as they are exposed to such threats as the deterioration of the medium they are stored in or formats obsolescence. A number of actions must be taken to ensure their long-term access. To address this need, digital repositories have evolved, accommodating now sets of features capable of implementing different strategies for the digital preservation of information. This thesis presents an analysis of the current state of the art open source repository software for the digital preservation of information identifying the five most relevant solutions. From those solutions, we picked the most feature rich and broader user community software, RODA, to which we propose and implement further improvements to an existing preservation strategy: federation. These improvements consist in building into the system an interoperability mechanism capable of allowing RODA to interact with other systems. This improvement is made by implementing a prototype composed by a CMIS server inside the repository, which communicates with client applications through the implementation of the CMIS protocol. We name this prototype RODA OpenCMIS Server, or in short, RODA-OCS. The prototype allows RODA to expose contents stored inside it publicly, under a controlled environment, in an authenticated and secure way. This goal is achieved by integrating our prototype with RODA native permissions system. RODA-OCS not only implements a file browser mechanism for content navigation but also a query engine capable of searching and retrieving contents based on their metadata, either technical or descriptive. Finally, we present a demonstration of the functioning of RODA-OCS. Through the use of a dataset conceived to test the functionalitie

Characterizing the transcriptional regulation of crassulacean acid metabolism in Kalanchoe

Due to the agricultural challenges posed by the prospect of a hotter drier climate understanding the molecular basis of plant water-use efficiency is of increasing importance. Species performing crassulacean acid metabolism (CAM) photosynthesis have evolved to be naturally water-use efficient primarily through shifting their carbon uptake to night to minimize water-loss. Relative to C3 and C4 photosynthesis species, CAM plants are enriched for rhythmic circadian clock-dependent regulation of metabolic processes. However, the transcriptional regulation of CAM remains largely uncharacterized. Using Kalanchoe fedtschenkoi, in which CAM develops along a leaf developmental gradient, candidate transcription factors with possible CAM-related functions were identified. The mRNA abundance of these transcription factors increases upon the transition from C3 photosynthesis to CAM and they appear to exhibit a circadian phase-dependent pattern of regulation. To better characterize the transcriptional control circuits underlying CAM, three such of these transcription factors, KfNF-YB3, KfHomeodomain-like, and KfMYB59 were selected for chromatin immunoprecipitation-sequencing (ChIP-seq). However, these experiments failed to identify enriched target genomic loci possibly as a consequence of the unique challenges of adapting experimental protocols designed for model C3 photosynthesis plant species to a succulent plant such as Kalanchoe. Additionally, this work focuses on elucidating the cis-regulatory elements and the trans-acting factors governing the transcriptional control of the phosphoenolpyruvate carboxylase gene (Ppc1) in Kalanchoe. Despite this enzyme’s importance in catalyzing the primary nocturnal fixation of CO2 in CAM species, the complex regulatory mechanisms underlying its expression are not well-studied. We examined the Kalanchoe Ppc1 promoter and identified numerous cis-regulatory elements on the basis of their sequence conservation with known regulatory modules. These individual elements along with two-hundred base pair region segments of the Kalanchoe Ppc1 promoter were used at bait probes in yeast one-hybrid (Y1H) assays. From this analysis, several high-confidence interacting transcriptional regulators were identified including ERF9, ERF106, TCP4, and PIF1. In silico examination of the Ppc1 promoter revealed likely binding sites for these factors based on homology to validated preferred binding sequences in Arabidopsis. The specific transcription factors identified through this work can now serve as the basis for further experiments to confirm interaction with the Ppc1 promoter and elucidate the nature of their regulatory effects. Overall, the work presented in this dissertation attempts to investigate the transcriptional control of crassulacean acid metabolism using the developmental CAM model Kalanchoe

Metabolic Network Alignments and their Applications

The accumulation of high-throughput genomic and proteomic data allows for the reconstruction of the increasingly large and complex metabolic networks. In order to analyze the accumulated data and reconstructed networks, it is critical to identify network patterns and evolutionary relations between metabolic networks. But even finding similar networks becomes computationally challenging. The dissertation addresses these challenges with discrete optimization and the corresponding algorithmic techniques. Based on the property of the gene duplication and function sharing in biological network,we have formulated the network alignment problem which asks the optimal vertex-to-vertex mapping allowing path contraction, vertex deletion, and vertex insertions. We have proposed the first polynomial time algorithm for aligning an acyclic metabolic pattern pathway with an arbitrary metabolic network. We also have proposed a polynomial-time algorithm for patterns with small treewidth and implemented it for series-parallel patterns which are commonly found among metabolic networks. We have developed the metabolic network alignment tool for free public use. We have performed pairwise mapping of all pathways among five organisms and found a set of statistically significant pathway similarities. We also have applied the network alignment to identifying inconsistency, inferring missing enzymes, and finding potential candidates

GEIR: a Full-Fledged Geographically Enhanced Information Retrieval Solution

With the development of search engines (e.g. Google, Bing, Yahoo, etc.), people is ambitiously expecting higher quality and improvements of current technologies. Bringing human intelligence features to these tools, like the ability to find implicit information through semantics, is one of the must prominent research lines in Computer Science. Information semantics is a very wide concept, as wide as the human capability to interpret, in particular, the analysis of geographical semantics gives the possibility to associate information with a place. It is estimated that more than 70\% of all information in the world has some kind of geographic features \cite{Jones04}. In 2012, Ed Parsons, a GeoSpatial Technologist from Google, reported that between 30\% and 40\% of the user queries at Google search engine contain geographic references \cite{Parsons12}. This thesis addresses the field of geographic information extraction and retrieval in unstructured texts. This process includes the identification of spatial features in textual documents, the data indexing, the manipulation of the relevance of the identified geographic entities and the multi-criteria retrieval according to the thematic and geographic information. The main contributions of this work include a custom geographic knowledge base, built from the combination of GeoNames and WordNet; a Natural Language Processing and knowledge based heuristics for Toponym Recognition and Toponym Disambiguation; and a geographic relevance weighting model that supports non-spatial indexing and simple ranking combination approaches. The validity of each one of these components is supported by practical experiments that show their effectiveness in different scenarios and their alignment with state of the art solutions. In addition, it also constitutes a main contribution of this work GEIR, a general purpose GIR framework that includes the implementations of the above described components and brings the possibility of implementing new ones and test their performance within an end to end GIR system

Integrative bioinformatics analyses of genome-wide RNAi screens

In past few years, genome-wide RNAi screens have identified many novel genes involved in diseases for many viruses such as Human Immunodeficiency Virus-1 (HIV-1), Hepatitis C virus (HCV), West Nile Virus (WNV) and Influenza virus (IV). However, due to difference in experimental conditions, usage of different viral strains and inherent biological noise, these screens have shown low number of common or overlapping hits for a virus. Moreover, this overlap gets poorer for similar studies on viruses of different families. Although these overlaps are significant, their lower size restricts a comprehensive insight from a comparative analysis. Thus, a direct comparison of gene hit-lists of RNAi screens may not always give meaningful results. To address this problem we propose an integrative bioinformatics pipeline that allows for network based meta-analysis of viral HT-RNAi screens. Initially, human protein interaction network (PIN) generated by collating data from various public repositories, is subjected to unsupervised clustering to determine functional modules. Those modules that are significantly enriched in host dependency factors (HDFs) and/or host restriction factors (HRFs) are then filtered based on network topology and semantic similarity measures. Modules passing all these criteria are then interpreted for their biological significance from enrichment analyses. With our approach we could predict Tankyrase-1 as a potential novel hit within the functional subnetworks, within the human PIN for Hepatitis C virus (HCV). and Human Immunodeficiency Virus-1 (HIV-1), based on HDFs and HRFs identified in the corresponding genome-wide RNAi screens of these viruses. Thus, our approach allows for a network based meta-analysis of genome-wide screens to develop plausible hypotheses for novel regulatory mechanisms in virus-host interactions based on RNAi screens