Epfl master thesis databases

The field of Affective Computing AC expects to narrow the communicative gap between the highly emotional human and the emotionally challenged computer by developing computational systems that recognize and respond to the affective states of the user.

Epfl master thesis databases

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.

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 epfl master thesis databases 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.

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. 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.

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

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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.

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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.

Where law meets science. Pharmaceutical companies are developing new transdermal patches that are less invasive and maintain more steady levels of drugs—to treat everything from pain to . The Assembly is the supreme governing body of the ICRC. It oversees all the ICRC's activities. It formulates policy, defines general objectives and strategy, and approves the budget and accounts. It nominates the directors and the head of Internal Audit. Composed of between 17 and 25 co-opted. The Assembly is the supreme governing body of the ICRC. It oversees all the ICRC's activities. It formulates policy, defines general objectives and strategy, and approves the budget and accounts.

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. Ataman, Meric and Gardiol, Daniel F.

epfl master thesis databases

However the complexity of these large metabolic networks often hinders their utility in various practical applications.The Assembly is the supreme governing body of the ICRC.

It oversees all the ICRC's activities. It formulates policy, defines general objectives and strategy, and approves the budget and accounts. It nominates the directors and the head of Internal Audit.

epfl master thesis databases

Composed of between 17 and 25 co-opted. The Assembly is the supreme governing body of the ICRC. It oversees all the ICRC's activities. It formulates policy, defines general objectives and strategy, and approves the budget and accounts.

George TS has done his Master’s in Advanced Manufacturing Engineering from NITK Surathkal and has last worked as a Research Associate working on the development of an Intracranial stent at the Sree Chitra Institute for Medical Sciences and Technology, Thiruvananthapuram.

International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research. David Dao David is a PhD student at DS3Lab, building privacy-preserving and scalable Blockchain + AI systems for sustainability and health.

Before joining ETH Zurich, he was an engineer in Silicon Valley and a graduate student at MIT Broad Institute. Trust in drugs and especially in vaccinations can be lost by counterfeits or by not optimally managed distribution chains.

Directly and indirectly this creates health risks or can facilitate outbreaks. In combination and fully integrated with other methods, blockchain databases offer an additional.

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