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Many cellular components are transported using a combination of the actin- and microtubule-based transport systems. However, how these two systems work together to allow well-regulated transport is not clearly understood. We investigate this question in the Xenopus melanophore model system, where three motors, kinesin II, cytoplasmic dynein, and myosin V,(More)
Melanophores move pigment organelles (melanosomes) from the cell center to the periphery and vice-versa. These bidirectional movements require cytoplasmic microtubules and microfilaments and depend on the function of microtubule motors and a myosin. Earlier we found that melanosomes purified from Xenopus melanophores contain the plus end microtubule motor(More)
We present an overview of the research on intracellular transport in pigment cells, with emphasis on the most recent discoveries. Pigment cells of lower vertebrates have been traditionally used as a model for studies of intracellular transport mechanisms, because these cells transport pigment organelles to the center or to the periphery of the cell in a(More)
Motor proteins in the kinesin, dynein, and myosin superfamilies are tightly regulated to perform multiple functions in the cell requiring force generation. Although motor proteins within families are diverse in sequence and structure, there are general mechanisms by which they are regulated. We first discuss the regulation of the subset of kinesin family(More)
— The ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for catching and interception tasks, and for timed action sequences. In dynamic environments, where trajectories are evolving on-line, this is not a trivial task. The dynamical(More)
Kernel-based algorithms such as support vector machines (SVMs) are state-of-the-art in machine learning for pattern recognition. This chapter introduces SVMs and describes a specific application to hydroacoustic signal classification. Long-range, passive-acoustic monitoring in the oceans is facilitated by propagation properties for underwater sound. In(More)
—Large-scale geophysical monitoring systems raise the need for real-time feature extraction and signal classification. We study support vector machine (SVM) classification of hydroacoustic signals recorded by the Comprehensive Nuclear-Test-Ban Treaty's verification network. Due to constraints in the early signal processing most samples have incomplete(More)
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