分子生物学杂志文献搜索引擎开发研究

为了方便从事分子生物学研究人员快捷、准确地查阅相关杂志文献,开发和利用NCBI的Medline数据库的杂志文献资源。我们从Medline(PubMed)中检索并列出184种有关分子生物学的杂志名录,制作了每种杂志的超级链接及部分杂志年份相应的超级链接,组成一个有关分子生物学杂志文献的搜索引擎。此搜索引擎能快捷、准确、动态地检索184种分子生物学杂志全部文献题录及部分杂志各年的文献题录,并可在PubMed中进一步检索出文献的摘要和部分全文。     

Medline(PubMed)生物化学杂志文献搜索引擎开发研究

为了方便生物化学工作快捷、准确地查阅生物化学杂志献,开发和利用NCBI的Medline数据库的生物化学杂志献资源。从Medline(PubMed)中检索并列出175种有关生物化学的杂志名录,制作了每种杂志及部分杂志年份相应的超级链接,组成一个有关生物化学杂志献的搜索引擎。此搜索引擎能快捷、准确、动态地检索175种生物化学杂志全部献题录及部分杂志各年的献题录,并可在PubMed中进一步检索出献的要和部分全。     

计算机辅助教学及多媒体在遗传学教学中的应用

本文首先回顾了我国遗传学传统的教学方式,分析了目前多媒体组合在遗传学教学中的应用特点,指出计算机辅助教学及多媒体在遗传学教学中具有的独特优势,对我国高校建立和应用遗传学CAI课件提出了若干可行建议。 Abstract:The article firstly reviewed traditional teaching method of genetics in China,the characteristics of combination of media mix at present was analyzed in teaching genetics,the unique superiority of computer assisted instruction and multimedia was pointed out in teaching genetics,some suggestions to establish and utilize CAI class document of genetics was proposed in Chinese universities.     

遗传学实验显微图像采集与演示系统设计

利用 Microsoft® Visual Basic 6.0 设计开发了“遗传学实验显微图像采集与演示系统”,该系统主要包括图像采集和编辑、文本输入和编辑,实验指导和图像演示、图像检索和数据库管理、系统维护及帮助等功能,各部分都以窗口形式设计,既可采用视频图像采集卡实时捕获图像,又可通过扫描仪、数码相机、剪贴板或文件输入已有的图像,并经压缩技术处理后与文字说明、实验指导一同存入数据库,方便、快捷、灵活地实现了对图像的输入和编辑、查询和演示,无论是对教师的遗传学实验教学,还是对学生的遗传学实验的自学,都起到了良好的辅助作用。Abstract: A system for capturing and showing micrographs of genetics was designed with Microsoft® Visual Basic 6.0. The system includes many functions such as capturing and editing images, typing and editing text, teaching experiments, showing images, image retrieval, database management, system maintenance and help, all of them were developed with the form of windows. The system could collect images not only from image-grabber card in real-time but also from scanner, digital camera, clipboard and files. After utilizing the image compression technology, the images will be saved in database along with experiment instruction. With all the features referred above, the system can used as a wonderful assistant both for the teaching of genetics experiment and for the students’ learning by themselves.     

遗传学试题库的研制

利用FoxPro 2.5b设计了遗传学试题库。系统主要分为试题输入、试题查找与编辑、试卷生成、试卷管理、编辑打印、试卷分析、学生成绩管理等部分。系统将窗口设计和菜单式设计相结合,集多种功能于一个窗口之中,窗口之间可以相互调用,具有题型多,速度快,直观性强,操作灵活方便等特点。该题库现已输入1500多道试题,生成标准试卷16份。 Abstract:A computer system of genetics test question pool was designed with FoxPro 2.5b.This system includes mainly as follows:input,search,and edit of test questions,generation,management,edit,print and analysis of examination paper and student scored management,etc.The design mthod of window and menu style were used in this system.It collects multi-function in a window,and has some specialties such as calling each other among windows,many question styles,high speed,visualization and easy operation,etc.So far 1 500 test questions have been input into this system and 16 standard examination papers have been generated.     

DCCP and DICP： Construction and Analyses of Databases for Copper- and Iron-Chelating Proteins

Copper and iron play important roles in a variety of biological processes, especially when being chelated with proteins. The proteins involved in the metal binding, transporting and metabolism have aroused much interest. To facilitate the study on this topic, we constructed two databases （DCCP and DICP） containing the known copper- and iron-chelating proteins~ which are freely available from the website http：//sdbi.sdut.edu.cn/en. Users can conveniently search and browse all of the entries in the databases. Based on the two databases, bioinformatic analyses were performed, which provided some novel insights into metalloproteins.     

哮喘的分子遗传学研究进展

哮喘病和易感症的遣传学病因是复杂的,现可通过候选基因和易感位点筛选技术来进行研究。本文综述了哮喘易感基因的研究进展,同时讨论了哮喘遗传学研究对哮喘临床的应用前景。 Abstract:The genetics of asthma and atopy is complex,but can be approached by studies of both candidate genes and mapping of susceptibility loci.The progress in susceptibility genes for asthma and atopy is reviewed.New therapeutic approaches to asthma which are based on the study on asthma genetics for future are summarized.     

表遗传学推动新一轮遗传学的发展

科学的发展孕育着突破,表遗传学研究推动着新一轮的遗传学的发展。表遗传学是研究没有DNA序列变化的、可遗传的表达改变。表遗传学不仅对医学和农业有重要的实践意义,而且还提供了理解遗传和进化的新观点。研究表明,人类基因组含有两类遗传信息,遗传学信息提供了合成生命所必需蛋白质的模板,而表遗传学信息提供了何时、何地和怎样地应用遗传学信息的指令;遗传学和表遗传学的关系有如“阴阳”,它们既相区别又协同参与调节生命活动。同时还讨论了基因的概念、进化和epigenetics的中文译名等问题。表遗传学研究应引起国内学术界的关注。Abstract: Scientific development is pregnant with a breakthrough, epigenetic studies are pushing the genetics forward. Epigenetics is the study of heritable changes in gene expression that occurs without a change in DNA sequence. Epigenetics not only has practical significance for medicine and agriculture, but also provides new views on understanding heredity and evolution. Human genome contains information in two forms: the genetic information provides the blueprint for the manufacture of all the proteins necessary to create a living thing while the epigenetic information provides instructions on how, where, and when the genetic information should be used. The interrelationship of genetics and epigenetics is like a yin-yan, they are different from each other, and cooperatively take part in regulation of a variety of living activities. In this paper concept of gene and problems of evolution has been also discussed according to epigenetic viewpoints.     

遗传学试题库的研制

利用FoxPro 2.5b设计了遗传学试题库。系统主要分为试题输入、试题查找与编辑、试卷生成、试卷管理、编辑打印、试卷分析、学生成绩管理等部分。系统将窗口设计和菜单式设计相结合,集多种功能于一个窗口之中,窗口之间可以相互调用,具有题型多,速度快,直观性强,操作灵活方便等特点。该题库现已输入1500多道试题,生成标准试卷16份。 Abstract:A computer system of genetics test question pool was designed with FoxPro 2.5b.This system includes mainly as follows:input,search,and edit of test questions,generation,management,edit,print and analysis of examination paper and student scored management,etc.The design mthod of window and menu style were used in this system.It collects multi-function in a window,and has some specialties such as calling each other among windows,many question styles,high speed,visualization and easy operation,etc.So far 1 500 test questions have been input into this system and 16 standard examination papers have been generated.     

Design and update of a classification system: the UCSD map of science

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier's Scopus (about 15,000 source titles, 2001-2005) and Thomson Reuters' Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001-2004)-about 16,000 unique source titles. The updated map and classification adds six years (2005-2010) of WoS data and three years (2006-2008) from Scopus to the existing category structure-increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others.     

Developing a register of randomised controlled trials in primary care.

OBJECTIVE--To determine the number, nature, site of publication, and feasibility of identifying randomised controlled trials relevant to primary care. DESIGN--Review of literature using three strategies: approaching journal editors, Medline search, and manual search of individual journals. SETTING--Journals containing publications of studies based in primary care. MAIN OUTCOME MEASURES--The number, site of publication, and subject of trials identified. RESULTS--No journal had a system which enabled identification of all the randomised controlled trials it published. 266 trials relevant to primary care were identified from 110 different journals during 1987-91 by Medline. Of these, only 62 trials were published in primary care journals. Hand searching of seven major primary care research journals showed that between 13% and 38% of the trials had been missed by the Medline search. Of the trials identified, 47 (18%) were concerned with mental disease (including neuroses, tobacco misuse and alcohol misuse) and 43 (16%) were concerned with hypertension. CONCLUSION--Given the diversity of publication sources and topics, this supports the need for a centrally based register of randomised controlled trials that may be relevant to primary care overviews in the future.     

Identifying relevant studies for systematic reviews.

OBJECTIVE--To examine the sensitivity and precision of Medline searching for randomised clinical trials. DESIGN--Comparison of results of Medline searches to a "gold standard" of known randomised clinical trials in ophthalmology published in 1988; systematic review (meta-analysis) of results of similar, but separate, studies from many fields of medicine. POPULATIONS--Randomised clinical trials published in 1988 in journals indexed in Medline, and those not indexed in Medline and identified by hand search, comprised the gold standard. Gold standards for the other studies combined in the meta-analysis were based on: randomised clinical trials published in any journal, whether indexed in Medline or not; those published in any journal indexed in Medline; or those published in a selected group of journals indexed in Medline. MAIN OUTCOME MEASURE--Sensitivity (proportion of the total number of known randomised clinical trials identified by the search) and precision (proportion of publications retrieved by Medline that were actually randomised clinical trials) were calculated for each study and combined to obtain weighted means. Searches producing the "best" sensitivity were used for sensitivity and precision estimates when multiple searches were performed. RESULTS--The sensitivity of searching for ophthalmology randomised clinical trials published in 1988 was 82%, when the gold standard was for any journal, 87% for any journal indexed in Medline, and 88% for selected journals indexed in Medline. Weighted means for sensitivity across all studies were 51%, 77%, and 63%, respectively. The weighted mean for precision was 8% (median 32.5%). Most searchers seemed not to use freetext subject terms and truncation of those terms. CONCLUSION--Although the indexing terms available for searching Medline for randomised clinical trials have improved, sensitivity still remains unsatisfactory. A mechanism is needed to "''register" known trials, preferably by retrospective tagging of Medline entries, and incorporating trials published before 1966 and in journals not indexed by Medline into the system.     

A Method for the Automated,Reliable Retrieval of Publication-Citation Records

Background

Publication records and citation indices often are used to evaluate academic performance. For this reason, obtaining or computing them accurately is important. This can be difficult, largely due to a lack of complete knowledge of an individual''s publication list and/or lack of time available to manually obtain or construct the publication-citation record. While online publication search engines have somewhat addressed these problems, using raw search results can yield inaccurate estimates of publication-citation records and citation indices.

Methodology

In this paper, we present a new, automated method that produces estimates of an individual''s publication-citation record from an individual''s name and a set of domain-specific vocabulary that may occur in the individual''s publication titles. Because this vocabulary can be harvested directly from a research web page or online (partial) publication list, our method delivers an easy way to obtain estimates of a publication-citation record and the relevant citation indices. Our method works by applying a series of stringent name and content filters to the raw publication search results returned by an online publication search engine. In this paper, our method is run using Google Scholar, but the underlying filters can be easily applied to any existing publication search engine. When compared against a manually constructed data set of individuals and their publication-citation records, our method provides significant improvements over raw search results. The estimated publication-citation records returned by our method have an average sensitivity of and specificity of (in contrast to raw search result specificity of less than 10%). When citation indices are computed using these records, the estimated indices are within of the true value, compared to raw search results which have overestimates of, on average, .

Conclusions

These results confirm that our method provides significantly improved estimates over raw search results, and these can either be used directly for large-scale (departmental or university) analysis or further refined manually to quickly give accurate publication-citation records.     

Évaluation de BabelMeSH en français

BabelMeSH is a multilingual search tool for Medline/PubMed. It is intended for users whose primary language is not English. The languages currently supported are: Arabic, Chinese, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish and Swedish. The goal of this work is to evaluate the usability and effectiveness of the French version. This study consisted of two parts: (1) evaluation of translation of French keywords by BabelMeSH, (2) user feedback. We used two sets of keywords: a list of authors’ keywords in medical journals published in French and a list of terms derived from Web server logs submitted by French-speaking users to search BabelMeSH. English translations by the authors were compared with those translated by BabelMeSH. The accuracy of translation of user submitted terms was evaluated. An online questionnaire using the 5-point Likert scale was used to evaluate user opinion on the usefulness of BabelMeSH. One hundred and seventy-four author keywords and 179 user keywords in French were randomly selected to search Medline/PubMed via BabelMeSH. With the author-generated keywords, BabelMeSH exactly matched (word-for-word) the authors’ translations for 69 terms; translations were accurate (similar concept) for 69 keywords; multiple suggestions were given for 19, one of which was the same as the authors’ translation or considered accurate. Partial matches (compound words) were found for 22 keywords. BabelMeSH translations were incorrect for 21 terms. For user search terms, 135 translations and suggestions were considered accurate, 15 partially accurate, 21 were incorrect. Of the eight with multiple suggestions, only one was accurate. Six responses were received from the online questionnaire. The average ratings (5: agree, 1: disagree) for the following statements were: (1) that BabelMeSH was useful: 4.3; (2) the overall quality of citations retrieved was excellent: 4.3; and (3) that they would continue to use BabelMeSH: 4.6. All declared that they had previously searched Medline in English and all, except one, stated that they would recommend it to others. BabelMeSH is an alternative resource for researchers whose native language is other than English. Limited user feedback and the results of an objective evaluation seem to indicate that it could be a useful addition to multilanguage search tools for Medline/PubMed. However, at the time we conducted this study, the development of BabelMeSH was not finished. Therefore, it might be necessary to evaluate BabelMeSH French version in future.     

Conservative surgical and drug therapies for adenomyosis Medicine

Adenomyosis is a benign invasion/infiltration of endometrial glands and stroma in the uterine myometrium. The optimal choice of adenomyosis treatment remains a subject of discussion. For patients with adenomyosis without fertility requirements, hysterectomy can be performed by laparotomy or laparoscopic surgery to eliminate symptoms. However, this is an inadequate option for women who want to preserve fertility or avoid more extensive surgery. To summarize the medicine and conservative surgery treatment for adenomyosis. An extensive literature search was performed using PubMed, Web of Science, Embase, Ovid Medline, Cochrane Central Register of Controlled Trials, Google Scholar and China National Knowledge Infrastructure (CNKI) without language restriction. The search terms were as follows: adenomyomas, adenomyosis, conservative therapy; combined therapy; medicine; surgery. The search included all titles and abstracts assessing conservative treatment for adenomyosis including medical and surgical therapy. All published papers were analyzed if considered relevant. Increasing current conservative treatments will not only improve the quality of life of the patients but also preserve fertility. Therefore, conservative treatment is extremely important for patients with fertility requirements or a strong desire to retain the uterus. Conservative treatment for adenomyosis may become a future trend in the field of gynecology.     

Search filters for finding prognostic and diagnostic prediction studies in Medline to enhance systematic reviews

Background

The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter.

Methodology/Principal Findings

Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next – using word frequency methods – we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85.

Conclusions/Significance

Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studies.     

An Unsupervised, Model-Free, Machine-Learning Combiner for Peptide Identifications from Tandem Mass Spectra

As the speed of mass spectrometers, sophistication of sample fractionation, and complexity of experimental designs increase, the volume of tandem mass spectra requiring reliable automated analysis continues to grow. Software tools that quickly, effectively, and robustly determine the peptide associated with each spectrum with high confidence are sorely needed. Currently available tools that postprocess the output of sequence-database search engines use three techniques to distinguish the correct peptide identifications from the incorrect: statistical significance re-estimation, supervised machine learning scoring and prediction, and combining or merging of search engine results. We present a unifying framework that encompasses each of these techniques in a single model-free machine-learning framework that can be trained in an unsupervised manner. The predictor is trained on the fly for each new set of search results without user intervention, making it robust for different instruments, search engines, and search engine parameters. We demonstrate the performance of the technique using mixtures of known proteins and by using shuffled databases to estimate false discovery rates, from data acquired on three different instruments with two different ionization technologies. We show that this approach outperforms machine-learning techniques applied to a single search engine’s output, and demonstrate that combining search engine results provides additional benefit. We show that the performance of the commercial Mascot tool can be bested by the machine-learning combination of two open-source tools X!Tandem and OMSSA, but that the use of all three search engines boosts performance further still. The Peptide identification Arbiter by Machine Learning (PepArML) unsupervised, model-free, combining framework can be easily extended to support an arbitrary number of additional searches, search engines, or specialized peptide–spectrum match metrics for each spectrum data set. PepArML is open-source and is available from . Electronic supplementary material The online version of this article (doi: ) contains supplementary material, which is available to authorized users.     

Probabilistic consensus scoring improves tandem mass spectrometry peptide identification

Database search is a standard technique for identifying peptides from their tandem mass spectra. To increase the number of correctly identified peptides, we suggest a probabilistic framework that allows the combination of scores from different search engines into a joint consensus score. Central to the approach is a novel method to estimate scores for peptides not found by an individual search engine. This approach allows the estimation of p-values for each candidate peptide and their combination across all search engines. The consensus approach works better than any single search engine across all different instrument types considered in this study. Improvements vary strongly from platform to platform and from search engine to search engine. Compared to the industry standard MASCOT, our approach can identify up to 60% more peptides. The software for consensus predictions is implemented in C++ as part of OpenMS, a software framework for mass spectrometry. The source code is available in the current development version of OpenMS and can easily be used as a command line application or via a graphical pipeline designer TOPPAS.