Assessing the Reproducibility of Clustering of Molecular Dynamics Conformations on Self-Organizing Maps

The goal of most clustering algorithms is to find the optimal number of clusters (i.e. fewest number of clusters). However, analysis of molecular conformations of biological macromolecules obtained from computer simulations may benefit from a larger array of clusters. The Self-Organizing Map (SOM) clustering method has the advantage of generating large numbers of clusters, but often gives ambiguous results. In this work, SOMs have been shown to be reproducible when the same conformational dataset is independently clustered multiple times (~100), with the help of the Cramérs V-index (C_v). The ability of C_v to determine which SOMs are reproduced is generalizable across different SOM source codes. The conformational ensembles produced from MD (molecular dynamics) and REMD (replica exchange molecular dynamics) simulations of the penta peptide Met-enkephalin (MET) and the 34 amino acid protein human Parathyroid Hormone (hPTH) were used to evaluate SOM reproducibility. The training length for the SOM has a huge impact on the reproducibility. Analysis of MET conformational data definitively determined that toroidal SOMs cluster data better than bordered maps due to the fact that toroidal maps do not have an edge effect. For the source code from MATLAB, it was determined that the learning rate function should be LINEAR with an initial learning rate factor of 0.05 and the SOM should be trained by a sequential algorithm. The trained SOMs can be used as a supervised classification for another dataset. The toroidal 10×10 hexagonal SOMs produced from the MATLAB program for hPTH conformational data produced three sets of reproducible clusters (27%, 15%, and 13% of 100 independent runs) which find similar partitionings to those of smaller 6×6 SOMs. The χ^2 values produced as part of the C_v calculation were used to locate clusters with identical conformational memberships on independently trained SOMs, even those with different dimensions. The χ^2 values could relate the different SOM partitionings to each other.

Social Movement Casework and the Law and Organizing Ideal : Toward a modified law and organizing model

En Amérique du Nord, les militants et les juristes ont longtemps cru que les avocats progressistes pourraient offrir des avantages tactiques importants aux mouvements sociaux. Cette perspective optimiste a cédé la place pendant les années 1970 à une attitude critique à l'égard des avocats et des litiges. Les chercheurs se sont interrogés sur l’efficacité d’assimiler les revendications politiques à des atteintes aux droits individuels, pour être ensuite présentées devant les tribunaux. Le litige était perçu comme source d’une influence négative qui favorise l’isolement et l’individualisme. De plus, les chercheurs ont remarqué qu’il y avait le potentiel pour les avocats militants – bien qu’ils soient bien intentionnés – d’exercer leur profession d’une manière qui pourrait donner un sentiment d’impuissance aux autres participants du mouvement social. Les premières versions de cette critique vont souvent assimiler la « stratégie juridique » avec le litige présenté devant les tribunaux judiciaires et géré par les avocats. Une réponse inspirante à cette critique a développée au début des années 2000, avec l'émergence d’un modèle de pratique que les chercheurs aux États-Unis ont nommé « law and organizing ». Des études normatives sur ce modèle offrent des arguments nuancés en faveur d’une pratique militante interdisciplinaire, partagée entre les avocats et les organisateurs. Ces études continuent à attribuer les risques d’individualisation et d’impuissance aux avocats et aux litiges. Selon ce modèle, au lieu de diriger la stratégie, les avocats travaillent en collaboration avec les travailleurs sociaux, les organisateurs et les citoyens pour planifier la stratégie du mouvement social, tout en favorisant l'autonomisation et la mobilisation de la collectivité. La présente thèse offre un examen critique de ce modèle, à travers l'une de ses tactiques bien connues: le traitement des problèmes juridiques individuels par les organisations militantes. La thèse examine les hypothèses fondatrices du modèle « law and organizing », en réinterprétant les problèmes d’individualisation et d’impuissance comme étant des enjeux reconnus dans de multiples disciplines, partout où les acteurs font de l’intervention sur une base individuelle afin de provoquer un changement systémique. La thèse soutient qu’un modèle de la pratique engagée du droit qui associe l'individualisation et l'impuissance exclusivement à la profession d'avocat risque de répondre de façon inadéquate aux deux problèmes. La recherche propose un modèle modifié qui met l'accent sur les options juridiques accessibles aux militants, tout en reconnaissant que la mobilisation et l'autonomisation sont des priorités qui sont partagées entre plusieurs disciplines, même si elles peuvent être traitées de façon particulière à l’intérieur de la profession juridique.

Fast training of self organizing maps for the visual exploration of molecular compounds

Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.

Low-molecular-weight gelators: Elucidating the principles of gelation based on gelator solubility and a cooperative self-assembly model

This paper highlights the key role played by solubility in influencing gelation and demonstrates that many facets of the gelation process depend on this vital parameter. In particular, we relate thermal stability (T-gel) and minimum gelation concentration (MGC) values of small-molecule gelation in terms of the solubility and cooperative self-assembly of gelator building blocks. By employing a van't Hoff analysis of solubility data, determined from simple NMR measurements, we are able to generate T-calc values that reflect the calculated temperature for complete solubilization of the networked gelator. The concentration dependence of T-calc allows the previously difficult to rationalize "plateau-region" thermal stability values to be elucidated in terms of gelator molecular design. This is demonstrated for a family of four gelators with lysine units attached to each end of an aliphatic diamine, with different peripheral groups (Z or Bee) in different locations on the periphery of the molecule. By tuning the peripheral protecting groups of the gelators, the solubility of the system is modified, which in turn controls the saturation point of the system and hence controls the concentration at which network formation takes place. We report that the critical concentration (C-crit) of gelator incorporated into the solid-phase sample-spanning network within the gel is invariant of gelator structural design. However, because some systems have higher solubilities, they are less effective gelators and require the application of higher total concentrations to achieve gelation, hence shedding light on the role of the MGC parameter in gelation. Furthermore, gelator structural design also modulates the level of cooperative self-assembly through solubility effects, as determined by applying a cooperative binding model to NMR data. Finally, the effect of gelator chemical design on the spatial organization of the networked gelator was probed by small-angle neutron and X-ray scattering (SANS/SAXS) on the native gel, and a tentative self-assembly model was proposed.

Reduction of invasive tests in chagasic patients with a modified self-organizing map

The applicability of AI methods to the Chagas' disease diagnosis is carried out by the use of Kohonen's self-organizing feature maps. Electrodiagnosis indicators calculated from ECG records are used as features in input vectors to train the network. Cross-validation results are used to modify the maps, providing an outstanding improvement to the interpretation of the resulting output. As a result, the map might be used to reduce the need for invasive explorations in chronic Chagas' disease.

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.

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)

A new spin-2 self-dual model in D=2+1

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Meaningful Fractal Fuzzy Dimension Applied to the Design of Self Organizing Maps

This paper presents the principal results of a detailed study about the use of the Meaningful Fractal Fuzzy Dimension measure in the problem in determining adequately the topological dimension of output space of a Self-Organizing Map. This fractal measure is conceived by combining the Fractals Theory and Fuzzy Approximate Reasoning. In this work this measure was applied on the dataset in order to obtain a priori knowledge, which is used to support the decision making about the SOM output space design. Several maps were designed with this approach and their evaluations are discussed here.

Polyacids self-dissociation model

This work deals with a model to interpret pH measurements of solutions of weak rodlike polyacids, in the absence of added salts or titrating base. The polyacid is modeled as a series of point charges discretely distributod in a straight line with a distance of closest approach for the protons and an average distance between dissociable monomers, projected in the polymer chain axis. Aside from these two geometrical parameters, the dissociation constant for the isolated monomer that describes the proton dissociated monomer interaction forms the basis of the model. The assumption of cylindrical symmetry and the adoption of the cell model lead to a form written in terms of elementary functions for the mean electrostatic potential. Values of pH (related to the proton concentration in a region beyond the influence of the polyacid) as a function of polymer concentration are displayed graphically for some values of the geometrical parameters and of the dissociation, constant. Theoretical predictions of pH values as a function of polymeric concentration are compared with measured values for poly-L-glutamic and polygalacturonic acids, and a good agreement is found. Theoretical values for the dissociation degree in terms of polymeric concentration are shown for the two experimentally investigated systems. These values are in a range appreciably smaller than what is usually studied as a result of titration.