2,931 research outputs found
From genome evolution to genetic interactions and personalized anti-cancer drug targets
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160814.pdf (Publisher’s version ) (Open Access)Radboud University, 21 november 2016Promotor : Huijnen, M.A. Co-promotor : Notebaart, R.A
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No full textHere is a curious book. Its title-page declares "The Artist's Book of Fables" but its pre-title-page has "Fables, Original and Selected, with a Memoir of the Author." After that title-page, it is identical with "Fables, Original and Selected" as in our copy printed by John Murray in 1833. There is again an AI at the front and an index of engravings and engravers at the back. I found that copy twenty years ago. I had found an inferior copy twenty-two years before that. At that time, I noted Aesopic fables here including "Stone Broth" and "The Mouse and the Oyster."This is a hardbound book (hard cover)James Northcote, R.A
Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival
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149260.pdf (Publisher’s version ) (Open Access)Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly. As experimental genome-wide SDL screens are still scarce, here we introduce a network-level computational modeling framework that quantitatively predicts human SDLs in metabolism. For each enzyme pair (A, B) we systematically knock out the flux through A combined with a stepwise flux increase through B and search for pairs that reduce cellular growth more than when either enzyme is perturbed individually. The predictive signal of the emerging network of 12,000 SDLs is demonstrated in five different ways. (i) It can be successfully used to predict gene essentiality in shRNA cancer cell line screens. Moving to clinical tumors, we show that (ii) SDLs are significantly underrepresented in tumors. Furthermore, breast cancer tumors with SDLs active (iii) have smaller sizes and (iv) result in increased patient survival, indicating that activation of SDLs increases cancer vulnerability. Finally, (v) patient survival improves when multiple SDLs are present, pointing to a cumulative effect. This study lays the basis for quantitative identification of cancer SDLs in a model-based mechanistic manner. The approach presented can be used to identify SDLs in species and cell types in which "omics" data necessary for data-driven identification are missing
Integrative bioinformatics of metabolic networks.
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74411.pdf (Publisher’s version ) (Open Access)RU Radboud Universiteit Nijmegen, 06 mei 2009Promotores : Siezen, R.J., Teusink, B.117 p
Predicting human genetic interactions from cancer genome evolution
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148880.pdf (Publisher’s version ) (Open Access
Turbulent entrainment in a shearless mixing layer at the edge of a cloud
No full textThree-dimensional direct numerical simulations which combine the Eulerian description of temperature, vapor content and velocity with a Lagrangian ensemble of cloud water droplets are used to study the turbulent entrainment and subsequent mixing of clear air with a cloudy air filament. The study is conducted in a shearless mixing layer setup which is adjusted to realistic conditions at a cumulus cloud boundary. The magnitude of turbulent velocity fluctuations in- and outside the cloud can be varied independently. We find that the evolution of the cloud water droplet ensemble depends slightly only on the contrast of turbulent velocity fluctuations in- and outside the cloud filament. The buoyancy feedback on the flow via the evaporating droplets causes a transient amplification of all fluctuations before the turbulence eventually decays. We study the evolution of the probability density functions of droplet size as well as of supersaturation, temperature and vorticity at the droplet positions
The role of bacterial microcompartments in Listeria monocytogenes growth, stress adaptation and virulence
No full textListeria monocytogenes is a facultative anaerobe responsible for a severe infection called listeriosis, which primarily affects immunocompromised individuals. This foodborne pathogen can activate adaptive stress responses supporting its survival in a range of stress conditions encountered in food production and host environments. The capacity to utilize alternative substrates for growth is crucial for the survival of L. monocytogenes when other efficient nutrients such as glucose are unavailable. In recent years more and more evidence has been presented that so-called Bacterial Microcompartments (BMCs) play an essential role in the utilization of specific host-derived substrates by enteric pathogens that result from degradation of phospholipids and metabolism of mucus-derived saccharides, including ethanolamine and 1,2-propanediol. Notably, these compounds are also encountered in a wide range of food products, and could therefore also contribute to transmission of pathogens to the host. It has been suggested that BMCs also play a role in L. monocytogenes ecophysiology and pathogenicity, but experimental evidence supporting these claims are very scarce. In this thesis, we studied to understand the role of bacterial microcompartments in Listeria monocytogenes growth, stress adaptation and virulence
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