Sökning: "neural code"
Visar resultat 1 - 5 av 30 avhandlingar innehållade orden neural code.
1. Regulation of morphogen signalling during neural patterning in the Xenopus embryo
Sammanfattning : Morphogens such as Hedghog, Wnt, FGF, and retinoic acid are important signals whose concentrations need to be tightly regulated in the vertebrate embryo to ensure body axis development and formation of the central nervous system. We first show that the intracellular cytoplasmic protein XSufu acts as a dual regulator of Hedgehog (Hh) and Wnt signals during neural induction and patterning in the Xenopus embryo. LÄS MER
2. Input Calibration, Code Validation and Surrogate Model Development for Analysis of Two-phase Circulation Instability and Core Relocation Phenomena
Sammanfattning : Code validation and uncertainty quantification are important tasks in nuclear reactor safety analysis. Code users have to deal with large number of uncertain parameters, complex multi-physics, multi-dimensional and multi-scale phenomena. LÄS MER
3. Transposable Elements in Neural Progenitor Cells
Sammanfattning : More than 90% of DNA does not code for proteins and for a long time these sequences were referred to as “junk DNA” due to their unknown purpose. With the advent of new technologies it is now known, that the non-coding part of the genome is of great importance for regulating gene expression and is therefore indispensable. LÄS MER
4. Natural Language Processing for Low-resourced Code-switched Colloquial Languages – The Case of Algerian Language
Sammanfattning : In this thesis we explore to what extent deep neural networks (DNNs), trained end-to-end, can be used to perform natural language processing tasks for code-switched colloquial languages lacking both large automated data and processing tools, for instance tokenisers, morpho-syntactic and semantic parsers, etc. We opt for an end-to-end learning approach because this kind of data is hard to control due to its high orthographic and linguistic variability. LÄS MER
5. Source Code Representations of Deep Learning for Program Repair
Sammanfattning : Deep learning, leveraging artificial neural networks, has demonstrated significant capabilities in understanding intricate patterns within data. In recent years, its prowess has been extended to the vast domain of source code, where it aids in diverse software engineering tasks such as program repair, code summarization, and vulnerability detection. LÄS MER