Evolution of conserved secondary structures and their function in transcriptional regulation networks

Background: Many conserved secondary structures have been identified within conserved elements in the human genome, but only a small fraction of them are known to be functional RNAs. The evolutionary variations of these conserved secondary structures in h

Supramolecular isomerism in zinc hydroxide coordination polymers with pyridine-2,4-dicarboxylic acid: Two polymorphs with centrosymmetric two-dimensional and acentric three-dimensional coordination networks

Reactions of Zn(BF4)(2) and pyridine-2,4-dicarboxylic acid (2,4-pydcH(2)) in the presence of 1,2-bis( 4-pyridyl) ethylene or 1,3-bis(4-pyridyl) propane under hydro(solvo) thermal conditions yielded two polymorphic metal-organic coordination polymers formulated as Zn-2(OH)(2)(2,4-pydc) (1 and 2). Polymorph 1 features a two-dimensional (2-D) layer-like structure that is constructed by 2,4-pydc ligands bridging between the Zn-OH-Zn double-chain units. Each single Zn-OH-Zn chain is composed of mu(2)-OH groups connecting trigonal bipyramidal and tetrahedral Zn centers. Polymorph 2 is a 3-D coordination polymer containing 2-D Zn-OH-Zn sheets that consist of mu(2)- and mu(3)-OH groups and trigonal bipyramidal Zn centers. The sheets are pillared by 2,4-pydc ligands to form an acentric structural architecture. 1 and 2 are rare examples that the two polymorphs exhibit a centrosymmetric 2-D coordination network and an acentric 3-D coordination network, respectively. The different structures lead to differences in photoluminescent properties and thermal stabilities for 1 and 2.

Classification of valence changes of trivalent rare earth ions in alkaline earth borates using artificial neural networks

The investigations of classification on the valence changes from RE3+ to RE2+ (RE = Eu, Sm, Yb, Tm) in host compounds of alkaline earth berate were performed using artificial neural networks (ANNs). For comparison, the common methods of pattern recognition, such as SIMCA, KNN, Fisher discriminant analysis and stepwise discriminant analysis were adopted. A learning set consisting of 24 host compounds and a test set consisting of 12 host compounds were characterized by eight crystal structure parameters. These parameters were reduced from 8 to 4 by leaps and bounds algorithm. The recognition rates from 87.5 to 95.8% and prediction capabilities from 75.0 to 91.7% were obtained. The results provided by ANN method were better than that achieved by the other four methods. (C) 1999 Elsevier Science B.V. All rights reserved.

QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor