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Topic: Self-organizing

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Microtubule - Wikipedia, the free encyclopedia Microtubules are nucleated and organised by the microtubule organizing centers (MTOCs), such as centrosomes and basal bodies. Microtubules are also part of the cilia and flagella of eukaryotic cells (prokaryote flagella are entirely different). Microtubules serve as structural components within cells and are involved in many cellular processes including mitosis, cytokinesis, and vesicular transport. en.wikipedia.org /wiki/Microtubule   (1058 words)

Microtubule organizing center - Wikipedia, the free encyclopedia MTOC or microtubule-organizing center is a structure found in all plant and animal cells from which microtubules radiate. Microtubules are anchored with their "minus" ends in the centrosome, and because microtubules dissociate preferentially at this end, this anchoring has a stabalizing effect, and MTOC associated microtubules can grow very quickly. This directionality is also important for membrane bound transport, as the motor proteins kinesin and dynein typically move preferentially in either the "plus" or "minus" direction along a microtubule, allowing vesicles to be directed to or from the endoplasmic reticulum and Golgi apparatus. en.wikipedia.org /wiki/Microtubule_organizing_center   (240 words)

Microtubules Microtubules, the third principal component of the cytoskeleton, are rigid hollow rods approximately 25 nm in diameter. The microtubule array present in interphase cells disassembles and the free tubulin subunits are reassembled to form the mitotic spindle, which is responsible for the separation of daughter chromosomes (Figure 11.42). The microtubules that emanate from the centrosome terminate in the pericentriolar material, not the centrioles, and it is the pericentriolar material that initiates microtubule assembly. www.ncbi.nlm.nih.gov /books/bv.fcgi?db=Books&rid=cooper.section.1820   (1805 words)

Self-organizing map - Wikipedia, the free encyclopedia The self-organizing map (SOM) is a method for unsupervised learning, based on a grid of artificial neurons whose weights are adapted to match input vectors in a training set. SOM is one of the most popular neural computation methods in use, and several thousand scientific articles have been written about it. Output maps can also be made in different dimensions: 1-dimensional, 2-dimensional, etc., but most popular are 2D and 3D maps, for SOMs are mainly used for dimensionality reduction rather than expansion. en.wikipedia.org /wiki/Self_organizing_map   (722 words)

Kohonen's Self-Organizing Map (SOM) Kohonen's SOM is called a topology-preserving map because there is a topological structure imposed on the nodes in the network. A topological map is simply a mapping that preserves neighborhood relations. Kohonon's SOMs are a type of unsupervised learning. www.willamette.edu /~gorr/classes/cs449/Unsupervised/SOM.html   (440 words)

Freedom Road Socialist Organization - Wikipedia, the free encyclopedia Freedom Road's predecessor groups supported self-determination, up to and including independence, for blacks and Chicanos in the US. The organization was founded in 1985 from three groups of the Maoist tradition: the Proletarian Unity League, the Revolutionary Workers Headquarters and the Organization for Revolutionary Unity. Freedom Road Socialist Organization (Freedom Road) criticizes the term 'Marxism-Leninism' as being too orthodox and has adopted a plan called left refoundation with a goal of uniting previously divided sections of the left, including some Trotskyist and social-democratic organizations. en.wikipedia.org /wiki/Freedom_Road_Socialist_Organization   (440 words)

New Socialist Magazine, What Kind Of Socialist Organization?, Articles In our view revolutionary organizations that do not reproduce forms of hierarchy, bureaucracy and power over others and that can bring to struggles and movements a sense of the history and memories of socialist/anarchist organizing are the best vehicles for facilitating and developing forms of self-organization and the building of people's revolutionary capacities. Forms of socialist organizing that hinder people from democratically organizing themselves, keep people dependent on union officials, politicians or radical activists, or make it harder for people to develop deeper understandings of society through their own experiences are not building capacities for truly radical change. The ways socialists organize ourselves today to work toward socialist transformation should be guided by how we understand three things: the struggle for socialism, what the priorities of socialists in today's political conditions should be, and what ways of organizing are most effective in helping us to work on these priorities. www.newsocialist.org /magazine/47/article9.html   (440 words)

Self-Organizing Maps Applet This is a demonstration of how Self-Organizing Maps work. Below this is the option of viewing the actual colored SOM and the SOM displaying the similarities and differences in the map as described determining the quality of the map. Assuming SOMs work, the final picture produced should have similar colors close to each and when the “Similarity SOM” option is toggled, there should be black lines separating colors which are not similar to each other. davis.wpi.edu /%7Ematt/courses/soms/applet.html   (188 words)

Self-Organizing Map Training Visualization A self-organizing map is trained with a method that is called competition learning: When an input pattern is presented to the network, that neuron in the competition layer is determined, the reference vector of which is closest to the input pattern. These three-dimensional pattern regions may be somewhat better suited to demonstrate the idea of self-organizing maps, because people tend to be confused by the fact that for the other three example the input space and the map have the same number of dimensions. That is, a self-organizing map basically represents a set of vectors in the input space: one vector for each neuron in the competition layer. fuzzy.cs.uni-magdeburg.de /~borgelt/doc/somd   (1952 words)

Landuse Mapping Using Self Organizing Map Self Organizing Map (SOM) is a process of unsupervised learning whereby the significant patterns or features in the input are discovered [3,4]. In the neural area, it is said Self organized because the process of adaptive modify weights as a learning process is done by Maps itself according to the condition input which is applied. SOM uses the Euclidean distance of each input data and weight neuron to refine weight neuron (cluster center) while ISODATA calculate the mean and standard deviation. www.ess.co.at /GAIA/CASES/TAI/taipaper.html   (2740 words)

Automatic Labeling of Self-Organizing Maps:Making a Treasure-Map Reveal its Secrets Without any additional knowledge on the underlying documents, the resulting mapping of the SOM given in Figure 2 is hard to interpret, although the names of the authors may give some hints towards the cluster structure of the map (at least if you know the authors and have some knowledge concerning their research areas). The resulting labeled map allows the user to better understand the structure and the information available in the map and the reason for a specific map organization, especially when only little prior information on the data set and its characteristics is available. The naming convention for the abstracts is such as to give the name of the first author of a paper as the first three characters, followed by the short form label of the respective conference. www.ifs.tuwien.ac.at /ifs/research/pub_html/rau_pakdd99/rau_pakdd99.html   (3710 words)

Self-Organizing Map (SOM) The Self-Organizing Map is based on unsupervised learning, which means that no human intervention is needed during the learning and that little needs to be known about the characteristics of the input data. The Self-Organizing Map was developed by professor Kohonen [20]. Map units, or neurons, usually form a two-dimensional lattice and thus the mapping is a mapping from high dimensional space onto a plane. www.cis.hut.fi /~jhollmen/dippa/node9.html   (520 words)

The Self Organizing Map: Unsupervised Competitive Learning The Self Organizing Map is called a competitive algorithm because units compete to represent the input pattern. Self organizing networks like the SOM have been used as models of how sensory maps form within human and animal brains. Another way to look at the Self Organizing Map is to plot the weight vector associated with each of the map units in the input space. lsa.colorado.edu /~simon/cmc/chapters/SOM/index2.html   (1539 words)

Introduction to Self-Organizing Map Neighborhood relation: The neurons of the map are connected to adjacent neurons by a neighborhood relation dictating the structure of the map. In the SOM similar vectors in the input space are projected onto nearby neurons on the map. In this respect the SOM is a multidimensional scaling methods which project data from input space to a lower-dimensional output space. www.csc.fi /cschelp/sovellukset/math/matlab/cedar/somalg.html   (1045 words)

Microtubule Structures For example, during mitosis, the cytosolic microtubule network characteristic of interphase cells disappears, and the tubulin from it is used to form the spindle-shaped apparatus that partitions chromosomes equally to the daughter cells (Figure 19-4a). In a microtubule, lateral and longitudinal interactions between the tubulin subunits are responsible for maintaining the tubular form. A microtubule is a polymer of globular tubulin subunits, which are arranged in a cylindrical tube measuring 24 nm in diameter www.ncbi.nlm.nih.gov /books/bv.fcgi?rid=mcb.section.5406   (1668 words)

Microtubule- and Dynein-Mediated Movement of Orientia tsutsugamushi to the Microtubule Organizing Center -- Kim et al. 69 (1): 494 -- Infection and Immunity Microtubule- and Dynein-Mediated Movement of Orientia tsutsugamushi to the Microtubule Organizing Center -- Kim et al. Microtubule- and Dynein-Mediated Movement of Orientia tsutsugamushi to the Microtubule Organizing Center The host cell microfilaments and microtubules (MTs) are known to play a critical role in the life cycles of several pathogenic iai.asm.org /cgi/content/abstract/69/1/494   (321 words)

Tim Stearns - Faculty & Researcher Profiles - Stanford School of Medicine We have shown that duplication of the centrosome, the microtubule organizing center of animal cells, is dependent on the cell cycle kinase Cdk2, and on cell cycle-specific proteolysis. Microtubules are polymers assembled from alpha-tubulin and beta-tubulin subunits, and are an essential element of the cytoskeleton. We study the organization and regulation of the microtubule cytoskeleton, and the relationship between the cell cycle and the cytoskeleton. www-med.stanford.edu /profiles/frdActionServlet?choiceId=printerprofile&fid=6244   (1507 words)

2001 Senior Experience Database Lastly, I was involved in a research project that measured the distances between the mitochondrial organizing center of the cell and the distance between the center of the nucleus, in respect to the center of the cell. In addition to this, the laboratory attempts to determine the pathways by which these molecules affect the microtubules and either allow or prevent the polymerization and or orientation of the microtubule-organizing center. Microtubules, which are composed of tubulin proteins, comprise one portion of the cytoskeleton. www.bergen.org /cgi-bin/senexp/2001list.pl?action=More&idnum=84   (223 words)

BioSci 191 November 18, 2005 The unit of microtubule assembly is a dimer of alpha- and beta-tubulin. Microtubule growth is mediated by the addition of GTP-containing tubulin dimers to the plus end. Microtubules (and actin filaments) have a polarity: the two ends are different. biosci191.bsd.uchicago.edu /L23/L23.htm   (639 words)

CELL BIOLOGY: ON MOLECULAR MOTORS The microtubule "plus ends" spread outwards from the organizing center, and this leads to a radial organization of the microtubule network in some interphase cells, such as fibroblast cells [5], pigment cells, and certain mammalian cells. Microtubule organization is cell-type specific and in some cases, such as neurons and epithelial cells, differs significantly from the usual radial organization. Microtubules are part of the cytoskeleton of biological cells, the quasi-rigid matrix that among other things determines cell shape. scienceweek.com /2005/sa050128-1.htm   (1924 words)

Microtubule Structure In the cell itself, microtubules are formed in an area near the nucleus called the "aster". Microtubules are polar with a plus end (fast growing) and a minus end (slow growing). Microtubule growth would be promoted in a dividing or moving cell. www.cytochemistry.net /Cell-biology/microtubule_structure.htm   (1153 words)

Plasma membrane functions MTOC microtubule organizing center, can be considered a starting point or foundation that microtubules grow out from. Most of microtubule function (movement of chromosomes, transport of vesicles and organelles, movement of cilia and flagella) is mediated by microtubular motors. Two sets of microtubules from each triplet in basal body are extended into the cilia or flagella and form the basis of the axoneme. www.indiana.edu /~a560/lect25.html   (639 words)

Interactive Fly, Drosophila The outer diameter of the complex is similar to the outer diameter of a microtubule. MTOCs effect microtubule organization by initiating microtubule assembly and anchoring microtubules at their slowly growing minus ends, thus ensuring that in each microtubule array it is the rapidly growing plus ends that extend distally. During interphase, the minus (or slow-growing) ends of microtubules are embedded in the PCM and the plus (or fast-growing) ends project outwards into the cytoplasm (or during mitosis, into the spindle apparatus). www.sdbonline.org /fly/cytoskel/tubgm1.htm   (878 words)

presentation.htm The organization of the golgi apparatus and the lysosomes in the normal cells were compared to the organization in the cells treated with nocodazole. Microtubules are a key factor in the organization of eukaryotic cells. Microtubules also form a cytoskeleton that maintains the positions of organelles, such as lysosomes and Golgi apparatuses, in the cell and plays a part in intracellular transport. www.haverford.edu /biology/Courses/bio300/BioGallery00/presentation.bwsj/presentation.htm   (2030 words)

Unity Statement of FRSO SON emerged initially out of the dissolution of the League of Revolutionary Struggle (LRS), which itself was formed by the unity of the August 29th Movement, I Wor Kuen, and the Revolutionary Communist League. FRSO merged with the Socialist Organizing Network, (SON) in 1993. SON’s roots are primarily in the liberation movements of oppressed nationalities and national minorities (Chicano/Latino, Asian American, and African-American), and the labor movement. www.frso.org /about/unitystatement2001.htm   (2030 words)

Self Organizing Map (SOM) in Excel SOM is an extensively researched area and it has been applied sucessfully on problems from various fields. You want to buy a commercial SOM software eventually but for now you want to have a feel of it and see what kind of features would be useful or nice to have. On the map, ideally one should represent all the data points of a cluster by a single point - the neuron that captured all those points. www.geocities.com /adotsaha/NN/SOMinExcel.html   (1418 words)

Self-Organizing Maps Self-organizing maps (SOMs) are a data visualization technique invented by Professor Teuvo Kohonen which reduce the dimensions of data through the use of self-organizing neural networks. SOMs organize sample data so that in the final product, the samples are usually surrounded by simliar samples, however similar samples are not always near each other. The way SOMs go about reducing dimensions is by producing a map of usually 1 or 2 dimensions which plot the similarities of the data by grouping similar data items together. davis.wpi.edu /~matt/courses/soms   (2776 words)

Self-Organizing Feature Map for Multi-Spectral Spot Land Cove Classification In this article, a window mask is used to extract texture pattern features, and a self-organizing feature maps (SOFM) is proposed to learn the pattern similarity in the feature space, then a Learning Vector Quantization (LVQ) network with the trained SOFM as its hidden layer is used to classified the test images. In a topology-preserving map, neurons located physically next to each other will respond to input vectors of classes that are likewise next to each other. SOFM based on competitive learning is a topology-preserving map (Kohonen, 1982, 84), and can be adjusted to approach the probability distribution of the inputs (Zheng, 1996). www.gisdevelopment.net /aars/acrs/2000/ts9/imgp0024pf.htm   (1263 words)

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