Use of self-organizing maps and molecular descriptors to predict the cytotoxic activity of sesquiterpene lactones

Some sesquiterpene lactones (SLs) are the active compounds of a great number of traditionally medicinal plants from the Asteraceae family and possess considerable cytotoxic activity. Several studies in vitro have shown the inhibitory activity against cells derived from human carcinoma of the nasopharynx (KB). Chemical studies showed that the cytotoxic activity is due to the reaction of alpha,beta-unsaturated carbonyl structures of the SLs with thiols, such as cysteine. These studies support the view that SLs inhibit tumour growth by selective alkylation of growth-regulatory biological macromolecules, such as key enzymes, which control cell division, thereby inhibiting a variety of cellular functions, which directs the cells into apoptosis. In this study we investigated a set of 55 different sesquiterpene lactones, represented by 5 skeletons (22 germacranolides, 6 elemanolides, 2 eudesmanolides, 16 guaianolides and nor-derivatives and 9 pseudoguaianolides), in respect to their cytotoxic properties. The experimental results and 3D molecular descriptors were submitted to Kohonen self-organizing map (SOM) to classify (training set) and predict (test set) the cytotoxic activity. From the obtained results, it was concluded that only the geometrical descriptors showed satisfactory values. The Kohonen map obtained after training set using 25 geometrical descriptors shows a very significant match, mainly among the inactive compounds (similar to 84%). Analyzing both groups, the percentage seen is high (83%). The test set shows the highest match, where 89% of the substances had their cytotoxic activity correctly predicted. From these results, important properties for the inhibition potency are discussed for the whole dataset and for subsets of the different structural skeletons. (C) 2008 Elsevier Masson SAS. All rights reserved.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

USGS Topographic Maps over a Hillshaded Digital Elevation Model

http://digitalcommons.colby.edu/atlasofmaine2005/1013/thumbnail.jpg

February 2008: Maps

http://digitalcommons.winthrop.edu/dacusdocsnews/1026/thumbnail.jpg

New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

Self-Organizing Maps as a New Tool for Classification of Plants at Lower Hierarchical Levels

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Extended depth from focus reconstruction using NIH ImageJ plugins: Quality and resolution of elevation maps

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic linkage maps of chicken chromosomes 6, 7, 8, 11 and 13 from a Brazilian resource population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparative RH Maps of the River Buffalo and Bovine Y Chromosomes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Topological signatures in CMB temperature anisotropy maps

We propose an alternative formalism to simulate cosmic microwave background (CMB) temperature maps in Lambda CDM universes with nontrivial spatial topologies. This formalism avoids the need to explicitly compute the eigenmodes of the Laplacian operator in the spatial sections. Instead, the covariance matrix of the coefficients of the spherical harmonic decomposition of the temperature anisotropies is expressed in terms of the elements of the covering group of the space. We obtain a decomposition of the correlation matrix that isolates the topological contribution to the CMB temperature anisotropies out of the simply connected contribution. A further decomposition of the topological signature of the correlation matrix for an arbitrary topology allows us to compute it in terms of correlation matrices corresponding to simpler topologies, for which closed quadrature formulas might be derived. We also use this decomposition to show that CMB temperature maps of (not too large) multiply connected universes must show patterns of alignment, and propose a method to look for these patterns, thus opening the door to the development of new methods for detecting the topology of our Universe even when the injectivity radius of space is slightly larger than the radius of the last scattering surface. We illustrate all these features with the simplest examples, those of flat homogeneous manifolds, i.e., tori, with special attention given to the cylinder, i.e., T-1 topology.