Data mining phd thesis

The analyzed web resources contain 1 the actual web site 2 the hyperlinks connecting these sites and 3 the path that online users take on the web to reach a particular site. Web usage mining then refers to the derivation of useful knowledge from these data inputs. Web mining discovers patterns in a less structured data such as Internet. In other words, we can say that Web Mining is Data Mining techniques applied to the.

Data mining phd thesis

However, because predicting orthology is computationally intensive at large scale, and most pipelines relatively inaccessible, less precise homology-based functional transfer is still the default for meta- genome annotation.

Student Theses Related to Data Mining (Since )

We therefore developed eggNOG-mapper, a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed clusters and phylogenies from eggNOG. To validate our method, we benchmarked Gene Ontology predictions against two widely used homology-based approaches: Through strict orthology assignments, eggNOG-mapper further renders more specific annotations than possible from domain similarity only e.

The tool is available standalone or as an online service at http: Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations.

However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations.

We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes and subunits encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link.

In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs.

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We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy.

The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification.

Data mining phd thesis

This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models. This has been driven primarily by comparative genomics approaches, which rely on accurate and consistent characterization of genomic sequences.

It is nevertheless difficult to obtain consistent taxonomic and integrated functional annotations for defined prokaryotic clades. Thus, we developed proGenomes, a resource that provides user-friendly access to currently 25 high-quality genomes whose sequences and consistent annotations can be retrieved individually or by taxonomic clade.

These genomes are assigned to consistent and accurate taxonomic species clusters based on previously established methodology.

Additionally, broad habitat information is provided for many genomes. All genomes and associated information can be downloaded by user-selected clade or multiple habitat-specific sets of representative genomes. We expect that the availability of high-quality genomes with comprehensive functional annotations will promote advances in clinical microbial genomics, functional evolution and other subfields of microbiology.

Jensen, Kristian and Cardoso, Joao G. It provides a common native Python interface to a series of optimization tools, so different solver backends can be used and changed in a transparent way.

Optlang targets scientists who can thus focus on formulating optimization problems based on mathematical equations derived from domain knowledge. Although some core biomass components such as nucleic acids and proteins are evident for most species, the essentiality of the pool of other organic molecules, especially cofactors and prosthetic groups, is yet unclear.

Here we integrate biomass compositions from 71 manually curated genome-scale models, 33 large-scale gene essentiality datasets, enzyme-cofactor association data and a vast array of publications, revealing universally essential cofactors for prokaryotic metabolism and also others that are specific for phylogenetic branches or metabolic modes.

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Our results revise predictions of essential genes in Klebsiella pneumoniae and identify missing biosynthetic pathways in models of Mycobacterium tuberculosis.

This work provides fundamental insights into the essentiality of organic cofactors and has implications for minimal cell studies as well as for modeling genotype-phenotype relations in prokaryotic metabolic networks.

The economic feasibility of producer cells requires robust performance balancing growth and production. However, the inherent competition between these two objectives often leads to instability and reduces productivity.

While algorithms exist to design metabolic network reduction strategies for aligning these objectives, the biochemical basis of the growth-product coupling has remained unresolved. Here, we reveal key reactions in the cellular biochemical repertoire as universal anchor reactions for aligning cell growth and production.

A necessary condition for a reaction to be an anchor is that it splits a substrate into two or more molecules. The here identified anchor reactions mark network nodes for basing growth-coupled metabolic engineering and novel pathway designs. Methods commonly used within the field of systems biology including omics characterization, genome-scale metabolic modeling, and adaptive laboratory evolution can be readily deployed in metabolic engineering projects.

However, high performance strains usually carry tens of genetic modifications and need to operate in challenging environmental conditions. This additional complexity compared to basic science research requires pushing systems biology strategies to their limits and often spurs innovative developments that benefit fields outside metabolic engineering.

Here we survey recent advanced applications of systems biology methods in engineering microbial production strains for biofuels and -chemicals.Search Funded PhD Projects, Programs & Scholarships in Data Mining. Search for PhD funding, scholarships & studentships in the UK, Europe and around the world.

Your PhD Thesis: How to Plan, Draft, Revise & Edit Your Thesis. Postgraduate Study Fair, London We have 65 Data Mining PhD Projects, Programs & · faculty of computer science and automation eng.

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