A comparison of diversity estimators applied to a database of host–parasite associations

Understanding the drivers of biodiversity is important for forecasting changes in the distribution of life on earth. However, most studies of biodiversity are limited by uneven sampling effort, with some regions or taxa better sampled than others. Numerous methods have been developed to account for differences in sampling effort, but most methods were developed for systematic surveys in which all study units are sampled using the same design and assemblages are sampled randomly. Databases compiled from multiple sources, such as from the literature, often violate these assumptions because they are composed of studies that vary widely in their goals and methods. Here, we compared the performance of several popular methods for estimating parasite diversity based on a large and widely used parasite database, the Global Mammal Parasite Database (GMPD). We created artificial datasets of host–parasite interactions based on the structure of the GMPD, then used these datasets to evaluate which methods best control for differential sampling effort. We evaluated the precision and bias of seven methods, including species accumulation and nonparametric diversity estimators, compared to analyzing the raw data without controlling for sampling variation. We find that nonparametric estimators, and particularly the Chao2 and second-order jackknife estimators, perform better than other methods. However, these estimators still perform poorly relative to systematic sampling, and effect sizes should be interpreted with caution because they tend to be lower than actual effect sizes. Overall, these estimators are more effective in comparative studies than for producing true estimates of diversity. We make recommendations for future sampling strategies and statistical methods that would improve estimates of global parasite diversity.     

Pathway-based Analysis Tools for Complex Diseases:A Review

Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehen- sive understanding of the molecular mechanisms underlying complex diseases. Extensive studies uti- lizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available path- way-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are dis- cussed. This review will provide a useful guide to dissect complex diseases.     

急性心肌梗死患者冠状动脉病变严重性与脉压和脉压指数的关系

目的:探讨急性心肌梗死(AMI)患者冠状动脉病变严重程度与脉压和脉压指数的关系.方法:对185例AMI患者进行冠状动脉造影术,冠状动脉病变严重程度用冠状动脉病变支数和Gensini积分来表示,并测定收缩压(SBP)和舒张压(DBP)并计算脉压(PP)及脉压指数(PPI).结果:与脉压＜65mmHg的患者相比,脉压≥65mmHg的患者冠状动脉3支血管病变的患病率和Gensini积分显著增高(P＜0.01).与PPI＜0.500的患者相比,PPI≥0.500的患者冠状动脉3支血管病变的患病率和Gensini积分亦显著增高(P＜0.01).结论:PP和PPI与AMI患者冠状动脉病变程度密切相关,在临床上具有指导作用.     

In silico identification of novel lncRNAs with a potential role in diagnosis of gastric cancer

Abstract

Gastric cancer (GC) is the second leading cause of cancer-related deaths in the world. Due to the shortage of adequate symptoms in the early stages, it is diagnosed when the tumor has spread to distant organs. Early recognition of GC enhances the chance of successful treatment. Molecular mechanisms of GC are still poorly understood. LncRNAs are emerging as new players in cancer in both oncogene and tumor suppressor roles. High-throughput technologies such as RNA-Seq, have revealed thousands of lncRNAs which are dysregulated in GC. In this study, we retrieved lncRNAs obtained by High-throughput technologies from OncoLnc database. Consequently, retrieved lncRNAs were compared in literature-based databases including PubMed. As a result, two lists, including experimentally validated lncRNAs and predicted lncRNAs were provided. We found 43 predicted lncRNAs that had not been experimentally validated in GC, so far. Further Bioinformatics analyses were performed to obtain the expression profile of predicted lncRNAs in tumor and normal tissues. Also, the roles and targets of predicted lncRNAs in GC were identified by related databases. Finally, using the GEPIA database was reviewed the significant relationship of predicted lncRNAs with the survival of GC patients. By recognizing the lncRNAs involved in initiation and progression of GC, they may be considered as potential biomarkers in the GC early diagnosis or targeted treatment and lead to novel therapeutic strategies.

Communicated by Ramaswamy H. Sarma     

NMRShiftDB -- compound identification and structure elucidation support through a free community-built web database

Compound identification and support for computer-assisted structure elucidation via a free community-built web database for organic structures and their NMR data is described. The new database NMRShiftDB is available on . As the first NMR database, NMRShiftDB allows not only open access to the database but also open and peer reviewed submission of datasets, enabling the natural products community to build its first free repository of assigned 1H and 13C NMR spectra. In addition to the open access, the underlying database software is built solely from free software and is available under an open source license. This allows collaborating laboratories to fully replicate the database and to create a highly available network of NMRShiftDB mirrors. The database contains about 10,000 structures and assigned spectra, with new datasets constantly added. Its functionality includes (sub-) spectra and (sub-) structure searches as well as shift prediction of 13C spectra based on the current database material.     

EBI databases and services

The EMBL Outstation-European Bioinformatics Institute (EBI) is a center for research and services in bioinformatics. It serves researchers in molecular biology, genetics, medicine, and agriculture from academia, and the agricultural, biotechnology, chemical, and pharmaceutical industries. The Institute manages and makes available databases of biological data including nucleic acid, protein sequences, and macromolecular structures. It provides to this community bioinformatics services relevant to molecular biology free of charge over the Internet. Some of these databases and services are described in this review. For more information, visit the EBI Web server at http://www.ebi.ac.uk/.     

A new archaeobotanical database program

The available quantity of archaeobotanical data derived from the identification of macroremains has expanded considerably over the last few decades. In order to obtain a supraregional or even regional overview for a particular period of time, or of the distribution of a single species, a database is needed. At the Archaeobotanical Department of the Institute of the "Kommission für Arch?ologische Landesforschung in Hessen e.V." (KAL) such a database has been developed in the last few years. It is suitable for the handling of large quantities of archaeobotanical results, including a whole range of background information comprising archaeological, ecological and other related data, and offers various possibilities for the evaluation of these data. Received January 8, 2001 / Accepted April 9, 2002     

Human sequence variation and mutation databases

This paper aims to give an overview of current resources onhuman sequence variations and give an idea about the directionin which these services are moving.      

Characterization of SCAR markers of Eimeria spp. of domestic fowl and construction of a public relational database (The Eimeria SCARdb)

This study reports the development and characterization of 151 sequence characterized amplified region (SCAR) markers for the seven Eimeria species that infect the domestic fowl. From this set, 84 markers are species-specific and 67 present partial specificity. The complete nucleotide sequence was derived for all markers, revealing the presence of micro- and minisatellite repetitive units in 22 SCARs, with up to five distinct repeat units being observed per marker. Only 15 markers showed significant hits in similarity searches against public sequence databases, thus confirming their anonymous and non-coding character. Finally, a relational database of the markers (the Eimeria SCARdb) was developed and made available on the Internet, providing a valuable resource of SCAR markers that can be useful for molecular diagnosis, and also for epizootiological, genetic variability and genome mapping studies.