42 resultados para Biology - Glossaries, vocabularies, etc
Resumo:
In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.
Resumo:
Invokaatio: I.N.J.
Resumo:
Arkit: A-B8 C4.
Resumo:
Kaksi tekijän esipuhetta.
Resumo:
Arkit: A-B8 C4.
Resumo:
Cancer affects more than 20 million people each year and this rate is increasing globally. The Ras/MAPK-pathway is one of the best-studied cancer signaling pathways. Ras proteins are mutated in almost 20% of all human cancers and despite numerous efforts, no effective therapy that specifically targets Ras is available to date. It is now well established that Ras proteins laterally segregate on the plasma membrane into transient nanoscale signaling complexes called nanoclusters. These Ras nanoclusters are essential for the high-fidelity signal transmission. Disruption of nanoclustering leads to reduction in Ras activity and signaling, therefore targeting nanoclusters opens up important new therapeutic possibilities in cancer. This work describes three different studies exploring the idea of membrane protein nanoclusters as novel anti-cancer drug targets. It is focused on the design and implementation of a simple, cell-based Förster Resonance Energy Transfer (FRET)-biosensor screening platform to identify compounds that affect Ras membrane organization and nanoclustering. Chemical libraries from different sources were tested and a number of potential hit molecules were validated on full-length oncogenic proteins using a combination of imaging, biochemical and transformation assays. In the first study, a small chemical library was screened using H-ras derived FRET-biosensors. Surprisingly from this screen, commonly used protein synthesis inhibitors (PSIs) were found to specifically increase H-ras nanoclustering and downstream signalling in a H-ras dependent manner. Using a representative PSI, increase in H-ras activity was shown to induce cancer stem cell (CSC)-enriched mammosphere formation and tumor growth of breast cancer cells. Moreover, PSIs do not increase K-ras nanoclustering, making this screening approach suitable for identifying Ras isoform-specific inhibitors. In the second study, a nanoncluster-directed screen using both H- and K-ras derived FRET biosensors identified CSC inhibitor salinomycin to specifically inhibit K-ras nanocluster organization and downstream signaling. A K-ras nanoclusteringassociated gene signature was established that predicts the drug sensitivity of cancer cells to CSC inhibitors. Interestingly, almost 8% of patient tumor samples in the The Cancer Genome Atlas (TCGA) database had the above gene signature and were associated with a significantly higher mortality. From this mechanistic insight, an additional microbial metabolite screen on H- and K-ras biosensors identified ophiobolin A and conglobatin A to specifically affect K-ras nanoclustering and to act as potential breast CSC inhibitors. In the third study, the Ras FRET-biosensor principle was used to investigate membrane anchorage and nanoclustering of myristoylated proteins such as heterotrimeric G-proteins, Yes- and Src-kinases. Furthermore, Yes-biosensor was validated to be a suitable platform for performing chemical and genetic screens to identify myristoylation inhibitors. The results of this thesis demonstrate the potential of the Ras-derived FRETbiosensor platform to differentiate and identify Ras-isoform specfic inhibitors. The results also highlight that most of the inhibitors identified predominantly perturb Ras subcellular distribution and membrane organization through some novel and yet unknown mechanisms. The results give new insights into the role of Ras nanoclusters as promising new molecular targets in cancer and in stem cells.
Resumo:
Arkit: A-B8 C4.
Resumo:
There are more than 7000 languages in the world, and many of these have emerged through linguistic divergence. While questions related to the drivers of linguistic diversity have been studied before, including studies with quantitative methods, there is no consensus as to which factors drive linguistic divergence, and how. In the thesis, I have studied linguistic divergence with a multidisciplinary approach, applying the framework and quantitative methods of evolutionary biology to language data. With quantitative methods, large datasets may be analyzed objectively, while approaches from evolutionary biology make it possible to revisit old questions (related to, for example, the shape of the phylogeny) with new methods, and adopt novel perspectives to pose novel questions. My chief focus was on the effects exerted on the speakers of a language by environmental and cultural factors. My approach was thus an ecological one, in the sense that I was interested in how the local environment affects humans and whether this human-environment connection plays a possible role in the divergence process. I studied this question in relation to the Uralic language family and to the dialects of Finnish, thus covering two different levels of divergence. However, as the Uralic languages have not previously been studied using quantitative phylogenetic methods, nor have population genetic methods been previously applied to any dialect data, I first evaluated the applicability of these biological methods to language data. I found the biological methodology to be applicable to language data, as my results were rather similar to traditional views as to both the shape of the Uralic phylogeny and the division of Finnish dialects. I also found environmental conditions, or changes in them, to be plausible inducers of linguistic divergence: whether in the first steps in the divergence process, i.e. dialect divergence, or on a large scale with the entire language family. My findings concerning Finnish dialects led me to conclude that the functional connection between linguistic divergence and environmental conditions may arise through human cultural adaptation to varying environmental conditions. This is also one possible explanation on the scale of the Uralic language family as a whole. The results of the thesis bring insights on several different issues in both a local and a global context. First, they shed light on the emergence of the Finnish dialects. If the approach used in the thesis is applied to the dialects of other languages, broader generalizations may be drawn as to the inducers of linguistic divergence. This again brings us closer to understanding the global patterns of linguistic diversity. Secondly, the quantitative phylogeny of the Uralic languages, with estimated times of language divergences, yields another hypothesis as to the shape and age of the language family tree. In addition, the Uralic languages can now be added to the growing list of language families studied with quantitative methods. This will allow broader inferences as to global patterns of language evolution, and more language families can be included in constructing the tree of the world’s languages. Studying history through language, however, is only one way to illuminate the human past. Therefore, thirdly, the findings of the thesis, when combined with studies of other language families, and those for example in genetics and archaeology, bring us again closer to an understanding of human history.
Resumo:
Kaksi tekijän esipuhetta.
Resumo:
Janamittakaavat: Milles pas geometriques ; Lieues de Suede ; Lieues d'une Heure de Chemin.
Resumo:
Janamittakaavat: Milles pas geometriques ; Lieues de Suede ; Lieues d'une Heure de Chemin.
Resumo:
0-meridiaani: Ferro: Koordinaattiasteikko: E10°-68°, N72°-53°30'.