Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

A Relational Model of Workplace Victimization: Social Roles and Patterns of Victimization in Dyadic Relationships.

This article proposes a model of the ways in which dyadic interactions between employees who occupy 1 of 4 archetypal social roles in organizations can lead to either episodic or institutionalized patterns of victimization. The model shows how the occurrence of victimization involving these 4 role types is influenced by organizational variables such as power differences, culture, and access to social capital. The model integrates behavioral and social structural antecedents of victimization to develop a relational perspective on the dynamics of harmful behavior in the workplace. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The aditi deductive database system

Deductive databases generalize relational databases by providing support for recursive views and non-atomic data. Aditi is a deductive system based on the client-server model; it is inherently multi-user and capable of exploiting parallelism on shared-memory multiprocessors. The back-end uses relational technology for efficiency in the management of disk-based data and uses optimization algorithms especially developed for the bottom-up evaluation of logical queries involving recursion. The front-end interacts with the user in a logical language that has more expressive power than relational query languages. We present the structure of Aditi, discuss its components in some detail, and present performance figures.     

Contextualizing is not nullifying: Reply to Mills (2005).

In omitting crucial words and sentencees, neglecting relevant citations, and overlooking important distinctions, Jon Mills' (see record 2005-04819-001) critique of relational psychoanalysis significantly misrepresents the authors' viewpoint. This viewpoint seeks to contextualize, but not to nullify, individual worlds of experience and their limiting horizons. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

HiSQL: A Front-end Query System for Historical Relational Databases

The paper describes a prototype system called HiSQL (Historical SQL) which extends the functionality of SQL in manipulating historical data, by providing functions for spatial and temporal processing. Conceptually the paper is divided into three parts: the first part deals with the design and architecture of the system; the second part introduces a case study (the defters); and the third part describes specific functions for spatial and temporal processing of serial documents. The paper concludes with a comparison between HiSQL and SQL and suggestions for further work. This revised version was published online in August 2006 with corrections to the Cover Date.     

SQL语言中量词和空值的使用技术

在ＳＱＬ语言中可以引入全称量词符号ＦＯＲＡＬＬ，使ＳＱＬ语言使用更为自然，方便。本文讨论全称量词，存在量词和ＡＬＬ三种谓词之间的转换，联系和区别，以及空值存在时ＳＱＬ的使用技术。     

A frame-based knowledge representation model and its mapping to nested relations

The first part of this paper introduces the basic constructs of a frame representation model and gives a formal definition for them. Subsequently the nested relational model (NF²) is described as an extension of the classical relational model to support relation-valued attributes. In the second part of this paper both models are compared with each other and a mapping of frame representation structures to NF² structures is specified. The structural similarities between frames and NF² relations are made clear and it is shown that their main difference is due to the type polymorphism introduced by the concept hierarchy of the frame model. This causes type collisions to occur in the strictly typed NF² model when frames are directly mapped to NF² structures. Two solutions to this problem are suggested and compared. The paper concludes with a reformulation of query operations of the frame model in terms of NF² algebra operations.     

Object-oriented query language access to relational databases: A semantic framework for query translation

This research investigates and approach to query processing in a multidatabase system that uses an objectoriented model to capture the semantics of other data models. The object-oriented model is used to construct a global schema, defining an integrated view of the different schemas in the environment. The model is also used as a self-describing model to build a meta-database for storing information about the global schema. A unique aspect of this work is that the object-oriented model is used to describe the different data models of the multidatabase environment, thereby extending the meta database with semantic information about the local schemas. With the global and local schemas all represented in an object-oriented form, structural mappings between the global schema and each local schema are then easily supported. An object algebra then provides a query language for expressing global queries, using the structural mappings to translate object algebra queries into SQL queries over local relational schema. The advantage of using an object algebra is that the object-oriented database can be viewed as a blackboard for temporary storage of local data and for establishing relationships between different databases. The object algebra can be used to directly retrieve temporarily-stored data from the object-oriented database or to transparently retrieve data from local sources using the translation process described in this paper.     

CAD^2B—一个计算机辅助数据库设计系统

本文介绍了一个用Ｔｕｒｂｏ Ｃ语言在ＡＳＴ－２８６机器上实现的计算机辅助数据库设计系统ＣＡＤ＾２Ｂ。该系统提供了人机交互的环境，供设计者进行概念模型设计，并自动完成从概念模型逻辑模型的映射，创建满足规范化要求的关系表。该系统采用的概念模型是引入了事件和时间的扩展了的实体关系模型。该模型既能充分反映应用环境的静态和动态语义，又是向关系模式转化的基础。