Prototypic sequences for human repetitive DNA

Summary We report a collection of 53 prototypic sequences representing known families of repetitive elements from the human genome. The prototypic sequences are either consensus sequences or selected examples of repetitive sequences. The collection includes: prototypes for high and medium reiteration frequency interspersed repeats, long terminal repeats of endogenous retroviruses, alphoid repeats, telomere-associated repeats, and some miscellaneous repeats. The collection is annotated and available electronically.[/ap ]Offprint requests to: J. Jurka     

Voice Pathologies Classification and Detection Using EMD-DWT Analysis Based on Higher Order Statistic Features

BackgroundThe voice is a prominent tool allowing people to communicate and to change information in their daily activities. However, any slight alteration in the voice production system may affect the voice quality. Over the last years, researchers in biomedical engineering field worked to develop a robust automatic system that may help clinicians to perform a preventive diagnosis in order to detect the voice pathologies in an early stage.MethodIn this context, pathological voice detection and classification method based on EMD-DWT analysis and Higher Order Statistics (HOS) features, is proposed. Also DWT coefficients features are extracted and tested. To carry out our experiments a wide subset of voice signal from normal subjects and subjects which suffer from the five most frequent pathologies in the Saarbrücken Voice Database (SVD), is selected. In The first step, we applied the Empirical Mode Decomposition (EMD) to the voice signal. Afterwards, among the obtained candidates of Intrinsic Mode Functions (IMFs), we choose the robust one based on temporal energy criterion. In the second step, the selected IMF was decomposed via the Discrete Wavelet Transform (DWT). As a result, two features vector includes six HOSs parameters, and a features vector includes six DWT features were formed from both approximation and detail coefficients. In order to classify the obtained data a support vector machine (SVM) is employed. After having trained the proposed system using the SVD database, the system was evaluated using voice signals of volunteer's subjects from the Neurological department of RABTA Hospital of Tunis.ResultsThe proposed method gives promising results in pathological voices detection. The accuracies reached 99.26% using HOS features and 93.1% using DWT features for SVD database. In the classification, an accuracy of 100% was reached for “Funktionelle Dysphonia vs. Rekrrensparese” based on HOS features. Nevertheless, using DWT features the accuracy achieved was 90.32% for “Hyperfunktionelle Dysphonia vs. Rekurrensparse”. Furthermore, in the validation the accuracies reached were 94.82%, 91.37% for HOS and DWT features, respectively. In the classification the highest accuracies reached were for classifying “Parkinson versus Paralysis” 94.44% and 88.87% based on HOS and DWT features, respectively.ConclusionHOS features show promising results in the automatic voice pathology detection and classification compared to DWT features. Thus, it can reliably be used as noninvasive tool to assist clinical evaluation for pathological voices identification.     

Open access to tree genomes: the path to a better forest

An open-access culture and a well-developed comparative-genomics infrastructure must be developed in forest trees to derive the full potential of genome sequencing in this diverse group of plants that are the dominant species in much of the earth''s terrestrial ecosystems.     

Evaluation of structural features in fungal cytochromes P450 predicted to rule catalytic diversification

Fungi belong to the large kingdom of lower eukaryotic organisms encompassing yeasts along with filamentous and dimorphic members. Microbial P450 enzymes have contributed to exploration of and adaptation to diverse ecological niches such as conversion of lipophilic compounds to more hydrophilic derivatives or degradation of a vast array of environmental toxicants. To better understand diversification of the catalytic behavior of fungal P450s, detailed insight into the molecular machinery steering oxidative attack on the distinctly structured endogenous and xenobiotic substrates is of preeminent interest. Based on a general, CYP102A1-related template the bulk of predicted substrate/inhibitor-binding determinants were shown to cluster near the distal heme face within the six known substrate recognition sites (SRSs) made up by the α-helical B′/F/G/I tetrad, the B′–C interhelical loop and strands of the β6-sheet, population density being highest in the structurally flexible SRS-1 and SRS-4 domains, showing a low degree of conservation. Reactivity toward ligands favorably coincides with the lipophilicity/hydrophilicity profile and bulkiness of critical amino acids acting as selective filters. Some decisive elements may also serve in maintenance of catalytic competence via their action as gatekeepers directing substrate access/positioning or stabilizers of the heme environment enabling dioxygen activation. Non-SRS residues seem to control spin state equilibria and attract redox partners by electrostatic forces. Of note, the inhibitory potency of azole-type fungicides is likely to arise from perturbation of the complex interplay of the mechanistic principles addressed above. Knowledge-supported exploitation of the topological data will be helpful in the manufacture of commodity/specialty chemicals as well as therapeutic agents. Also, engineered fungal P450s may be used to improve pollutant-specific bioremediation of contaminated soils.     

乳腺肿瘤组织标本库与数据库的建立及信息化管理

目的:随着基础和临床研究的深入开展,拥有完整基因信息的组织标本成为了肿瘤研究工作的基础.建立电子信息化管理的乳腺肿瘤组织标本库和数据库,为临床和科研收集、保存和管理标本资源.方法:标准化收集手术切除的乳腺肿瘤组织、正常腺体组织,以及患者血液标本,预处理后保存于-80℃冰箱中.每3个月从标本库中随机抽取5例标本,提取标本的总RNA,琼脂糖凝胶电泳验证总RNA质量;运用免疫组织化学法(Immunohistochemistry,IHC)检测标本中人表皮生长因子-2(Human epidermal growth factor receptor,HER-2 or c-erbB-2)和Ki67的表达,并与术后免疫组化结果进行比较.同时利用Epidata软件管理乳腺肿瘤组织标本库.结果:收集恶性肿瘤507例,良性肿瘤212例,血液标本9347份,并建立了一套高效的信息化管理系统.总RNA电泳结果显示28 S和18S亚基条带清晰明亮,5S条带很弱,表明标本中的RNA质量较高,无降解.免疫组化结果显示标本中的HER-2和Ki67的表达与术后免疫组化结果情况吻合,存储的标本质量良好.结论:建立的实验标本收集、储存流程是有效可行的,收集的标本质量是可靠的,管理方法是高效实用的,为乳腺肿瘤基础和临床研究提供质量可靠的标本来源,可为乳腺肿瘤研究提供良好的服务平台.     

Microsatellite markers uncover cryptic species of Odontotermes (Termitoidae: Termitidae) from Peninsular Malaysia

Termites from the genus Odontotermes are known to contain numerous species complexes that are difficult to tell apart morphologically or with mitochondrial DNA sequences. We developed markers for one such cryptic species complex, that is, Odontotermes srinakarinensis sp. nov. from Maxwell Hill Forest Reserve (Perak, Malaysia), and characterised them using a sample of 41 termite workers from three voucher samples from the same area. We then genotyped 150 termite individuals from 23 voucher samples/colonies of this species complex from several sites in Peninsular Malaysia. We analysed their population by constructing dendograms from the proportion of shared-alleles between individuals and genetic distances between colonies; additionally, we examined the Bayesian clustering pattern of their genotype data. All methods of analysis indicated that there were two distinct clusters within our data set. After the morphologies of specimens from each cluster were reexamined, we were able to separate the two species morphologically and found that a single diagnostic character found on the mandibles of its soldiers could be used to separate the two species quite accurately. The additional species in the clade was identified as Odontotermes denticulatus after it was matched to type specimens at the NHM London and Cambridge Museum of Zoology.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.