Peptides and Peptoids - A Systematic Structure Comparison

A systematic analysis of the conformational space of the basic structure unit of peptoids in comparison to the corresponding peptide unit was performed based on ab initio MO theory and complemented by molecular mechanics (MM) and molecular dynamics (MD) calculations both in the gas phase and in aqueous solution.The calculations show three minimum conformations denoted as C_7ß, a_D and a that do not correspond to conformers on the gas phase peptide potential energy hypersurface. The influence of aqueous solvation was estimated by means of continuum models. The MD simulations indicate the a_D form as the preferred conformation in solution both in cis and trans peptide bond orientations.     

有序差异显示:一种基因表达谱系统比较法

系统研究具有同一基因组的各种细胞群之间基因的差异表达谱十分重要。目前,研究基因差异表达的技术大致有ｍＲＮＡ差异显示［１］、ＲＤＡ［３］、ＳＳＨ［４、５］和ｃＤＮＡ阵列［６］等。近几年,还发展了一些研究基因差异表达谱系统的技术,如ＲＬＣＳ（ｒｅｓｔｒｉｃｔｉｏｎｌａｎｄ－ｍａｒｋｃＤＮＡｓｃａｎｎｉｎｇ）［８］、ＧＥＦ（ｇｅｎｅｅｘｐｒｅｓ－ｓｉｏｎｆｉｎｇｅｒｐｒｉｎｔｉｎｇ）［２］和ＲＮＡ指纹法［９］等。然而,这些技术或较为复杂,或灵敏度偏低。本文拟介绍一种有效的基因表达谱系统比较法——有序差…     

A Systematic Comparison of Supervised Classifiers

Pattern recognition has been employed in a myriad of industrial, commercial and academic applications. Many techniques have been devised to tackle such a diversity of applications. Despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, as many techniques as possible should be considered in high accuracy applications. Typical related works either focus on the performance of a given algorithm or compare various classification methods. In many occasions, however, researchers who are not experts in the field of machine learning have to deal with practical classification tasks without an in-depth knowledge about the underlying parameters. Actually, the adequate choice of classifiers and parameters in such practical circumstances constitutes a long-standing problem and is one of the subjects of the current paper. We carried out a performance study of nine well-known classifiers implemented in the Weka framework and compared the influence of the parameter configurations on the accuracy. The default configuration of parameters in Weka was found to provide near optimal performance for most cases, not including methods such as the support vector machine (SVM). In addition, the k-nearest neighbor method frequently allowed the best accuracy. In certain conditions, it was possible to improve the quality of SVM by more than 20% with respect to their default parameter configuration.     

DNA-Microarray Technology: Comparison of Methodological Factors of Recent Technique Towards Gene Expression Profiling

DNA-microarray technology is a powerful tool to explore the potentials of functional genomics. Almost a decade back, it was not so easy to trace the molecular pathway process in the pathogenesis of diseases. Today DNA-microarray technology allows identifying candidate genes that are implicated in the development and progression of diseases. Because this technology is new, it remains a challenge to perform DNA-microarray experiments in the laboratory. All the technical factors associated with DNA-microarray experiments have a strong impact on the results and therefore, all parts/steps of the protocol, in particular sample preparation (i.e., RNA isolation, RNA preamplification, and cDNA labeling), hybridization, washing, and scanning settings need to be checked and optimized to obtain reliable results from DNA-microarray experiments.     

Systematic Profiling of Histone Readers in Arabidopsis thaliana

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Gene Expression Profiling of Seizure Disorders

Seizure disorders affect a significant percentage of the population, and researchers worldwide continue to work toward a better understanding of what initiates, propagates, and results from aberrant and excessive neuronal excitation. During the past two decades, one aspect of this research effort has been to describe the effects of seizure activity upon neuronal gene expression, with hopes of identifying the molecular mechanisms that underlie subsequent changes in cell function and survival. Here we review this body of work from the perspective of how these gene profiling efforts have evolved, starting with one-by-one analyses of specific gene targets to the more recent use of DNA microarrays to survey literally thousands of genes simultaneously. With regard to the latter, we present some of our own work that suggests that molecular mechanisms contributing to normal brain development are reiterated during seizure-induced network reorganization.     

Profiling Gene Expression in Germinating Brassica Roots

Based on previously developed solid-phase gene extraction (SPGE) we examined the mRNA profile in primary roots of Brassica rapa seedlings for highly expressed genes like ACT7 (actin7), TUB (tubulin1), UBQ (ubiquitin), and low expressed GLK (glucokinase) during the first day post-germination. The assessment was based on the mRNA load of the SPGE probe of about 2.1 ng. The number of copies of the investigated genes changed spatially along the length of primary roots. The expression level of all genes differed significantly at each sample position. Among the examined genes ACT7 expression was most even along the root. UBQ was highest at the tip and root–shoot junction (RS). TUB and GLK showed a basipetal gradient. The temporal expression of UBQ was highest in the MZ 9 h after primary root emergence and higher than at any other sample position. Expressions of GLK in EZ and RS increased gradually over time. SPGE extraction is the result of oligo-dT and oligo-dA hybridization and the results illustrate that SPGE can be used for gene expression profiling at high spatial and temporal resolution. SPGE needles can be used within two weeks when stored at 4 °C. Our data indicate that gene expression studies that are based on the entire root miss important differences in gene expression that SPGE is able to resolve for example growth adjustments during gravitropism.