Database reverse engineering: From requirements to CARE tools

This paper analyzes the requirements that CASE tools should meet for effective database reverse engineering (DBRE), and proposes a general architecture for data-centered applications reverse engineering CASE environments. First, the paper describes a generic DBMS-independent DBRE methodology, then it analyzes the main characteristics of DBRE activities in order to collect a set of desirable requirements. Finally, it describes DB-MAIN, an operational CASE tool developed according to these requirements. The main features of this tool that are described in this paper are its unique generic specification model, its repository, its transformation toolkit, its user interface, the text processors, the assistants, the methodological control and its functional extensibility. Finally, the paper describes five real-world projects in which the methodology and the CASE tool were applied. This is a heavily revised and extended version of “Requirements for Information System Reverse Engineering Support” by J.-L. Hainaut, V. Englebert, J. Henrard, J.-M. Hick, D. Roland, which first appeared in the Proceedings of the Second Working Conference on Reverse Engineering, IEEE Computer Society Press, pp. 136–145, July 1995. This paper presents some results of the DB-MAIN project. This project is partially supported by the Région Wallonne, the European Union, and by a consortium comprising ACEC-OSI (Be), ARIANE-II (Be), Banque UCL (Lux), BBL (Be), Centre de recherche public H. Tudor (Lux), CGER (Be), Cockerill-Sambre (Be), CONCIS (Fr), D'Ieteren (Be), DIGITAL, EDF (Fr), EPFL (CH), Groupe S (Be), IBM, OBLOG Software (Port), ORIGIN (Be), Ville de Namur (Be), Winterthur (Be), 3 Suisses (Be). The DB-Process subproject is supported by the Communauté Fran?aise de Belgique.     

多媒体教育资源库层次索引模型

依据多媒体教育资源各层次特征及其关系,通过定义资源媒体特征空间,构建了教育资源库层次索引模型,各层次特征间的映射规则将资源的高层语义特征映射到低层媒体特征,达到了扩充描述语义的目的,提高了查全率;结合学科本体,规范了资源标注内容和用户查询条件的描述,减少了人为因素对查询项和索引项匹配相似度计算的影响,提高了查准率.     

关系模式关键字的一个求解算法

本文给出了关系数据库模式中求解关键字的一个算法。算法很简洁并且对于[1]定义的一大类问题,执行时间是多项式级的。     

商标数据库存储模式及其检索算法研究

依据商标专家的先验知识和基于内容的图像检索技术，提出了一种新的商标库存储结构，并依据该存储结构设计了以三级检索算法为核心的实用商标登记注册管理系统，对于检索算法，一级检索采用人工确认，二级检索采用傅立叶描述子作为边缘特征向量，三级检索采用hu不变矩组作为矩特征向量，从而达到提高商标申请注册中的检索速度和查准率。     

SciFinder-guided rational design of fluorescent carbon dots for ratiometric monitoring intracellular pH fluctuations under heat shock

Intracellular pH plays a significant role in various biological processes, including cell proliferation, apoptosis, metabolism, enzyme activity and homeostasis. In this work, a novel design strategy for the preparation of pH responsive carbon dots (CDs-pH) for ratiometric intracellular imaging was reported. By using SciFinder database, fluorescent CDs-pH with the required pK_a value of 6.84 were rationally designed, which is vital important for precise sensing of intracellular pH. As a result, the synthesized CDs-pH demonstrated robust ability to test pH fluctuations within the physiological range of 5.4-7.4. The CDs-pH was further utilized for fluorescent ratiometric imaging of pH in living HeLa cells, effectively avoided the influence of autofluorescence from native cellular species. Moreover, real-time monitoring of intracellular pH fluctuation under heat shock was successfully realized. This SciFinder-guided design strategy is simple and flexible, which has a great potential to be used for the development of other types of CDs for various applications.     

Protein family classification and functional annotation

With the accelerated accumulation of genomic sequence data, there is a pressing need to develop computational methods and advanced bioinformatics infrastructure for reliable and large-scale protein annotation and biological knowledge discovery. The Protein Information Resource (PIR) provides an integrated public resource of protein informatics to support genomic and proteomic research. PIR produces the Protein Sequence Database of functionally annotated protein sequences. The annotation problems are addressed by a classification-driven and rule-based method with evidence attribution, coupled with an integrated knowledge base system being developed. The approach allows sensitive identification, consistent and rich annotation, and systematic detection of annotation errors, as well as distinction of experimentally verified and computationally predicted features. The knowledge base consists of two new databases, sequence analysis tools, and graphical interfaces. PIR-NREF, a non-redundant reference database, provides a timely and comprehensive collection of all protein sequences, totaling more than 1,000,000 entries. iProClass, an integrated database of protein family, function, and structure information, provides extensive value-added features for about 830,000 proteins with rich links to over 50 molecular databases. This paper describes our approach to protein functional annotation with case studies and examines common identification errors. It also illustrates that data integration in PIR supports exploration of protein relationships and may reveal protein functional associations beyond sequence homology.     

Computer-assisted structure elucidation of organic compounds III: Automatic fragment generation from13C-NMR spectra

The interpretation of carbon-NMR spectra is mainly based on the comparison with suitable reference data taken from literature. The whole information contents of¹³C-NMR spectra cannot be utilized by manual interpretation. Therefore a network of interactive computer programs has been developed, which simulates the strategy of the spectroscopist in generating structural fragments from the spectral data. The most important knowledge source for this process is a carbon-NMR data base containing some 17,500 spectra. Structural fragments are generated automatically from this data file and assembled by a model builder to complete chemical structures using constraints derived from the spectral data. A comparison of the experimental carbon-NMR spectrum with the estimated ones allows the generation of a sorted hitlist.For part II see: H. Kalchhauser, W. Robien,J. Chem. Inf. Comput. Sci. 1985,25, 103.     

Computer based screening of compound databases: 1. Preselection of benzamidine-based thrombin inhibitors

We present a computational protocol which uses the known three-dimensional structure of a target enzyme to identify possible ligands from databases of compounds with low molecular weight. This is accomplished by first mapping the essential interactions in the binding site with the program GRID. The resulting regions of favorable interaction between target and ligand are translated into a database query, and with UNITY a flexible 3D database search is performed. The feasibility of this approach is calibrated with thrombin as the target. Our results show that the resulting hit lists are enriched with thrombin inhibitors compared to the total database.     

CAST/CNMR: highly accurate C NMR chemical shift prediction system considering stereochemistry

Accurate, practical prediction of ¹³C NMR chemical shifts has been achieved with a new system, CAST/CNMR, taking account of stereochemistry. The CAST/CNMR system has solved the critical problem of the accurate distinction of differences and similarities in stereochemical structures around a specific carbon, which has not yet been achieved by any other database-oriented system for prediction of ¹³C NMR chemical shifts. CAST/CNMR uses a three-dimensional structural database together with a ¹³C NMR spectral database. Absolute/relative configurational and conformational structural information are described by the CAST (CAnonical-representation of STereochemistry) coding method. This paper provides an overview of the CAST/CNMR system, and describes its application to two natural products as examples.