Alexander V. Lukashin

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The number of completely sequenced bacterial genomes has been growing fast. There are computer methods available for finding genes but yet there is a need for more accurate algorithms. The GeneMark. hmm algorithm presented here was designed to improve the gene prediction quality in terms of finding exact gene boundaries. The idea was to embed the GeneMark(More)
A major challenge of current neuroscience is to elucidate the brain mechanisms that underlie cognitive function. There is no doubt that cognitive processing in the brain engages large populations of cells. This article explores the logic of investigating these problems by combining psychological studies in human subjects and neurophysiological studies of(More)
MOTIVATION Cluster analysis of genome-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and samples. In the present paper, we focus on several important issues related to clustering algorithms that have not yet been fully studied. RESULTS We describe a(More)
We have developed a model that simulates possible mechanisms by which supraspinal neuronal signals coding forces could converge in the spinal cord and provide an ongoing integrated signal to the motoneuronal pools whose activation results in the exertion of force. The model consists of a three-layered neural network connected to a two-joint-six-muscle model(More)
The distribution of closed unknotted polymer chains over the writhing number is calculated by the Monte-Carlo method. For circular duplex DNA the variance of the distribution equals approximately half the observed variance of equilibrium distribution over the linking number. The balance which arises from fluctuations in DNA twisting makes it possible to(More)
The hypothesis was tested that learned movement trajectories of different shapes can be stored in, and generated by, largely overlapping neural networks. Indeed, it was possible to train a massively interconnected neural network to generate different shapes of internally stored, dynamically evolving movement trajectories using a general-purpose core part,(More)
Understanding the neural computations performed by the motor cortex requires biologically plausible models that account for cell discharge patterns revealed by neurophysiological recordings. In the present study the motor cortical activity underlying movement generation is modeled as the dynamic evolution of a large fully recurrent network of stochastic(More)
As a dynamical model for motor cortical activity during hand movement we consider an artificial neural network that consists of extensively interconnected neuron-like units and performs the neuronal population vector operations. Local geometrical parameters of a desired curve are introduced into the network as an external input. The output of the model is a(More)
  • Peter Salamon, Andrzej K Konopka, G E F Scherer, S Walkinshaw, Arnott, D Schneider +15 others
  • 1995
[38] John C. Wootton and Scott Federhen. Statistics of local complexity in amino acid sequences and sequence databases. [39] J. Ziv and A. Lempel. Compression of individual sequences via variable-rate coding. [24] M. C. O'Neill. Consensus methods for nding and ranking DNA binding sites. A maximum entropy principle for the distribution of local complexity in(More)