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  1. SUMOylation of nuclear receptor Nor1/NR4A3 coordinates microtubule cytoskeletal dynamics and stability in neuronal cells

    Background

    Nor1/NR4A3 is a member of the NR4A subfamily of nuclear receptors that play essential roles in regulating gene expression related to...

    Jonathan Gagnon, Véronique Caron, André Tremblay in Cell & Bioscience
    Article Open access 13 July 2024
  2. Effects of warm oceanographic anomalies on the foraging variability of northern elephant seals

    Evaluation of stable carbon (δ 13 C) and nitrogen (δ 15 N) isotopes in marine organisms over time addresses how environmental variability (e.g., El...

    Eunice D. Rodríguez-Rafael, Fernando R. Elorriaga-Verplancken, ... Felipe Galván-Magaña in Marine Biology
    Article 13 July 2024
  3. Psychological and ethical issues raised by genomic in paediatric care pathway, a qualitative analysis with parents and childhood cancer patients

    In paediatric oncology, genomics raises new ethical, legal and psychological issues, as somatic and constitutional situations intersect throughout...

    Marion Droin-Mollard, Sandrine de Montgolfier, ... Khadija Lahlou-Laforêt in European Journal of Human Genetics
    Article Open access 13 July 2024
  4. Identification of volatile metabolites produced from levodopa metabolism by different bacteria strains of the gut microbiome

    Interspecies pathways in the gut microbiome have been shown to metabolize levodopa, the primary treatment for Parkinson’s disease, and reduce its...

    Taylor Pennington, Jarrett Eshima, Barbara S. Smith in BMC Microbiology
    Article Open access 13 July 2024
  5. The Kernel Memory Concept – A Paradigm Shift from Conventional Connectionism

    In this chapter, the general concept of kernel memory (KM) is described, which is given as the basis for not only representing the general notion of...
    Chapter
  6. Modelling Abstract Notions Relevant to the Mind and the Associated Modules

    This chapter is devoted to the remaining four modules within the AMS, i.e. 1) attention, 2) emotion, 3) intention, and 4) intuition module, and their...
    Chapter
  7. Bioinformatics with Evolutionary Computation

    This chapter makes the presumption that it is more important to understand the domain of the problem of interest and to pursue the best achievable...
    Chapter
  8. Introduction

    Genetic algorithms (GAs) are powerful search techniques based on principles of evolution. They are now widely applied to solve problems in many...
    Chapter
  9. Linkage Learning Genetic Algorithm

    In order to handle linkage evolution and to tackle the ordering problem, Harik [47] took Holland’s call [53] for the evolution of tight linkage quite...
    Chapter
  10. Preliminaries: Assumptions and the Test Problem

    After introducing the background and motivation of the linkage learning genetic algorithm, we will start to improve and understand the linkage...
    Chapter
  11. Rough Set Theory with Applications to Data Mining

    This paper is an introduction to rough set theory with an emphasis on applications to data mining. First, consistent data are discussed, including...
    Chapter
  12. From Classical Connectionist Models to Probabilistic/Generalised Regression Neural Networks (PNNs/GRNNs)

    This chapter begins by briefly summarising some of the well-known classical connectionist/artificial neural network models such as multi-layered...
    Chapter
  13. Language and Thinking Modules

    In this chapter, we focus upon the two modules which are closely tied to the concept of “action planning”, i.e. the 1) language and 2) thinking...
    Chapter
  14. Sensation and Perception Modules

    In any kind of creature, both the mechanisms of sensation and perception are indispensable for continuous living, e.g. to find edible plants/fruits...
    Chapter
  15. Reinforcement Learning: A Brief Overview

    Learning techniques can be usefully grouped by the type of feedback that is available to the learner. A commonly drawn distinction is that between...
    Chapter
  16. An Analysis of Continuous-Valued Representations for Learning Classifier Systems

    Learning Classifier Systems [11] typically use a ternary representation to encode the environmental condition that a classifier matches. However,...
    Christopher Stone, Larry Bull in Foundations of Learning Classifier Systems
    Chapter
  17. Data Driven Fuzzy Modelling with Neural Networks

    Extraction of models for complex systems from numerical data of behavior is studied. In particular, systems representable as sets of fuzzy if-then...
    Chapter
  18. Content Based Image Compression in Biomedical High-Throughput Screening Using Artificial Neural Networks

    Biomedical High-Throughput Screening (HTS) requires specific properties of image compression. Particularly especially when archiving a huge number of...
    Chapter
  19. Discriminative Clustering of Yeast Stress Response

    When a yeast cell is challenged by a rapid change in the conditions, be it temperature, osmolarity, pH, nutrient or other, it starts a genome stress...
    Samuel Kaski, Janne Nikkilä, ... Christophe Roos in Bioinformatics Using Computational Intelligence Paradigms
    Chapter
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