A combination of modified particle swarm optimization algorithm and support vector machine for gene selection and tumor classification

In the analysis of gene expression profiles, the number of tissue samples with genes expression levels available is usually small compared with the number of genes. This can lead either to possible overfitting or even to a complete failure in analysis of microarray data. The selection of genes that are really indicative of the tissue classification concerned is becoming one of the key steps in microarray studies. In the present paper, we have combined the modified discrete particle swarm optimization (PSO) and support vector machines (SVM) for tumor classification. The modified discrete PSO is applied to select genes, while SVM is used as the classifier or the evaluator. The proposed approach is used to the microarray data of 22 normal and 40 colon tumor tissues and showed good prediction performance. It has been demonstrated that the modified PSO is a useful tool for gene selection and mining high dimension data.     

基于Gene Ontology的表达谱与基因功能相似性的相关性研究

聚类是芯片数据分析中被广泛使用的方法。未知基因的功能通常通过其与已知基因在不同生物状态下具有表达相似性来进行预测。然而，还未有人就这种通过表达相似性来进行功能注释的方法的可靠性进行评估。本文利用Gene Ontology对表达相似性和基因功能相似性的相关关系进行了全面的研究。研究表明，尽管表达谱的相似性和基因功能相似性之间有一定的依赖关系，但相关性较弱。在Gene Ontology的三大类中，相对生物过程和分子功能，基因表达谱的相似性更有助于细胞组分的注释。本文的研究结果对于基因功能的预测有一定的指导意义。     

Conductance of potassium lodide in mixed solvents

The conductance of potassium iodide has been measured in the solvents ethylene carbonate, water, methyl ethyl ketone, and pairwise mixtures of these solvents at 40°C; and ethylene carbonate-water, tetramethylene sulfone-water, dimethyl sulfoxide-water, tetrahydrofuran-water, ethylene carbonate-tetramethylene sulfone-water, ethylene carbonate-tetramethylene sulfone, and tetrahydrofuran-dimethyl sulfoxide at 25°C. For dielectric constants greater than about 60, the pairing constants K_A are in the range 0.3–2.0; no correlation between K_A and solvent properties could be established. For lower dielectric constants, K_A increases exponentially with decreasing dielectric constant. Addition of a proton, acceptor to water initially decreases K_A regardless of whether the dielectric constant of the mixture is higher or lower than that of water, suggesting that ion pairs in water may be stabilized by cage structures. The Walden product A_o is also decreased by the addition of proton acceptors.     

Synthesis and photochemistry of side-chain liquid crystal polymers based on cinnamate esters

The syntheses of three methacrylate monomers with cinnamate ester side-chains and of a further monomer with a corresponding cinnamide side-chain are described. Two of the monomers, with isomeric structures, were thermotropic liquid crystals. Although the clearing points were very similar the crystal melting points differed by 8°C. One compound also exhibited a monotropic smectic phase, behavior not shown by its isomer. The other two monomers were not liquid crystalline. The monomers were polymerized by free radical polymerization, both as homopolymers and as copolymers with methyl methacrylate. In the case of one of the mesogenic ester monomers, copolymers with a cyanophenyl benzoate monomer were also prepared. Three of the four monomers formed thermotropic liquid crystalline homopolymers and the copolymers with the benzoate monomer were also liquid crystalline. The monomers were considered as photoactive components of polymeric liquid crystals. As a preliminary investigation of their photochemistry, copolymers with methyl methacrylate were prepared and irradiated in solution with a broad-band source. Under these conditions two of the materials show a facile photo-Fries rearrangement of the aryl cinnamate ester group. © 1992 John Wiley & Sons, Inc.     

离散小波变换-遗传算法-交互检验法用于近红外光谱数据的高倍压缩与变量筛选

用遗传算法(GA)与交互检验(CV)相结合建立了一种用于对近红外光谱(NIR)数据及其离散小波变换(DWT)系数进行变量筛选的方法，并应用于烟草样品中总挥发碱和总氮的同时测定。结果表明：NIR数据经DWT压缩为原始大小的3．3％时基本没有光谱信息的丢失；有效的变量筛选可以极大地减少模型中的变量个数，降低模型的复杂程度，改善预测的准确度。     

Chromatographic study of the thermodynamics of solutions of hydrocarbons in liquid crystal solvents. Evidence for order disturbance by the solutes

Gas-chromatographic experiments were carried out in various phases of the solvents 4-acetoxy-N-[4-methoxy-benzylidene]-aniline, dibutoxyazoxybenzene, lithium stearate, dihexoxyazoxybenzene, and diheptoxyazoxybenzene. The solutes were linear, branched and cyclic alkanes, and substituted benzenes. Excess enthalpies, entropies, and free entropies were calculated from net retention volumes. In the nematic liquid crystalline phases the effect of order disturbance was significant in and but it was, by enthalpy-entropy compensation, not demonstrable in . Differences in flexibility and degree of expansion of the solutes did not result in significantly different values of the excess quantities.     

Comparison of the retention behaviour of phenol derivatives on porous graphitized and octadecylsilica columns

Summary The retention of 22 ring-substituted phenol derivatives on porous graphitized carbon (PGC) (eluents: acetonitrile — water and methanol — water mixtures) and on octadecylsilica (ODS) (eluents: methanol — 0.025 M KH₂PO₄ mixtures) was determined, and the relationship between retention and physicochemical parameters were evaluated by principal component analysis followed by two-dimensional nonlinear mapping and by cluster analysis as well as by canonical correlation analysis. Calculations proved that marked differences can be detected between the retention characteristics of PGC and ODS columns, and the electronic parameters of phenol derivatives have the highest impact on their retention. The comparison of various multivariate mathematical-statistical methods indicated that principal component analysis followed by two dimensional non-linear mapping is the most appropriate method for the evaluation of large data matrices in RP-HPLC.     

Fuzzy theory in analytical chemistry

The concept of fuzzy theory is described in order to provide the analyst with the means for dealing with vague statements, uncertain observations or the fuzziness of human perception and interpretation, in general. In a theoretical part, basic notions of fuzzy theory are given, such as types of membership functions, operations with fuzzy sets, definitions of fuzzy numbers, points, functions, and relations, and the use of linguistic variables. The difference between fuzziness and probability is outlined. The applications section demonstrates advantages of fuzzy theory methods compared to common mathematical methods with respect to data handling for calibration of analytical methods, to classification of Chromatographie and spectroscopic patterns, to component identification and multicomponent analysis, and to designing fuzzy expert systems for selection of analytical procedures.     

Applications of maximum likelihood principal component analysis: incomplete data sets and calibration transfer

The application of a new method to the multivariate analysis of incomplete data sets is described. The new method, called maximum likelihood principal component analysis (MLPCA), is analogous to conventional principal component analysis (PCA), but incorporates measurement error variance information in the decomposition of multivariate data. Missing measurements can be handled in a reliable and simple manner by assigning large measurement uncertainties to them. The problem of missing data is pervasive in chemistry, and MLPCA is applied to three sets of experimental data to illustrate its utility. For exploratory data analysis, a data set from the analysis of archeological artifacts is used to show that the principal components extracted by MLPCA retain much of the original information even when a significant number of measurements are missing. Maximum likelihood projections of censored data can often preserve original clusters among the samples and can, through the propagation of error, indicate which samples are likely to be projected erroneously. To demonstrate its utility in modeling applications, MLPCA is also applied in the development of a model for chromatographic retention based on a data set which is only 80% complete. MLPCA can predict missing values and assign error estimates to these points. Finally, the problem of calibration transfer between instruments can be regarded as a missing data problem in which entire spectra are missing on the ‘slave’ instrument. Using NIR spectra obtained from two instruments, it is shown that spectra on the slave instrument can be predicted from a small subset of calibration transfer samples even if a different wavelength range is employed. Concentration prediction errors obtained by this approach were comparable to cross-validation errors obtained for the slave instrument when all spectra were available.