628 J. Chem. Inf. Comput. Sci., Vol. 37, No. 3, 1997 chemist’s bookshelf and close to their computers. Transferring the listed programs to the computer would be the most exciting step one would take to enter the world of programming. I cannot wait to do exactly that!
Narinder Singh UniVersity of Kansas Medical Center CI970383T S0095-2338(97)00383-1
Online Searching: A Scientists’s Perspective. A Guide for the Chemical and Life Sciences. Damon D. Ridley. John Wiley & Sons: Chichester. 1996. 344 + xx pages. List Price $79.95 (hdbk). ISBN 0-471-96520-0 hdbk, 0-471-96521-9 pbk. After attempting to cultivate the market for end-user access to information, publishers and vendors have recently made great progress in providing end-user-friendly information access systems. For example, STN recently announced STN Easy, a Web based product analogous to KR ScienceBase. These programs require of the enduser even less prior knowledge about information resources and access than SciFinder, the product for end-users that appeared in 1995. Educators, especially in University Departments of Chemistry, are clamoring for inexpensive access to such products, because many say they cannot provide the training for information access for research. The latter point is debatable, because many educators do provide such training. Many in the information industry insist that end-user products like those listed above are great but that end-users would use them even more effectively if they had education and training in the fundamentals of chemical and technical information. This book by Damon Ridley can help provide this proficiency in both the fundamentals and pragmatics of technical information. Ridley aims the book at end-users, stressing the particulars of searching online databases in general, especially databases of scientific information, but primarily on searching chemical databases online on the STN network. This pragmatic approach to searching is especially valuable for those endusers who do not have access to end-user search aids. Since Ridley’s book is primarily aimed at end-users not in a classroom setting, it falls somewhere in between prior books for endusers like Online Information Hunting (N. Goldmann, McGraw-Hill, 1992) and course textbooks like Chemical Information Sources (G. Wiggins, McGraw-Hill, 1991). Ridley is far less confrontational vis´a-vis´ information specialists than Goldmann and is, in my opinion, more upbeat and informative. The writing is apparently patterned after oral presentations, and exclamation marks are used liberally, hopefully not a turn-off for readers. The emphasis is definitely on searching, but knowledge of the construction and maintenance of databases is provided so that the enduser may search better. The first two chapters cover the general topics of online searching and basic commands and tools. Chapters 3-7 cover bibliographic database searching, followed by chapters on full text files, patents, and special topics. Chapters 11-17 cover searching for substances, concluding with chapters on property data and chemical reactions. Structure searching methods include names and nomenclature, molecular formulas, and construction of structure/substructures, including the trade-offs encountered with the various methods. The examples are all based on the STN Messenger system and STN files and emphasize chemical topics. However, the methods are translatable to other search systems and subject disciplines, and command comparison charts for STN, KR DIALOG, and ORBIT are provided in Appendix 1. Ridley develops some rather interesting concepts, including quotes like, “Online searching requires a meeting of three minds: the author, the indexer, and the searcher...”; “It is just as important to search the literature properly as it is to conduct proper research...”; “A conservative estimate is that online costs are only 25% of the real costs of searching and maintaining the hard copy library”; and “Indeed online searching is best conducted through a close association between the information specialist and the scientist, and each has special roles.” The reviewer believes strongly that search aids like SciFinder, STN Easy, and KR ScienceBase promote the acquisition of more information
BOOK REVIEWS by end-users than they would acquire without use of these products. However, I believe just as strongly that knowledge of information and database fundamentals can help end-users acquire even better information more efficiently, with or without the use of information professionals or search aid programs. The preferable method for students would be classroom instruction with texts like Wiggins. However, if the training and education of an end-user has been deficient in this area, use of Ridley’s book can help the end-user to be a more effective user of information and a better contributor to the user’s organization. Students and educators may question the price, but just as information is not free, neither is training for information.
Robert E. Buntrock Buntrock Associates, Inc. CI9703819 S0095-2338(97)00381-8
Neural Networks in QSAR and Drug Design. Edited by J. Devillers. Vol. 2 in the Series: Principles of QSAR and Drug Design. Academic Press: San Diego, 1996, 284 pp. ISBN 0-12-213815-5. The list price of this book is 65.00 pounds sterling. The 11 chapters of this hard-cover book are written by authors who are active research workers in the fields of neural networks (NNs) and/ or quantitative structure-activity relationships (QSARs) or quantitative structure-property relationships (QSPRs). The editor is at the same time the author of the first chapter (Strengths and Weaknesses of the Backpropagation Neural Network in QSAR and QSPR Studies), and one of the co-authors of five other chapters among which we cite AUTOLOG Versus Neural Network Estimation of n-Octanol/Water Partition Coefficients; Use of a Backpropagation Neural Network and Autocorrelation Descriptors for Predicting the Biodegradation of Organic Chemicals; and A Neural Structure-Odor Threshold Model for Chemicals of EnVironmental and Industrial Concern. A total of more than 10 000 bibliographical references for all chapters is made available to the readers, and the chapters are presented in an easily accessible and very readable style. In the first chapter, an extensive review is presented on the standard backpropagation neural network (BNN) algorithm and its variations, with practical recipes for selecting the number of neurons in the various layers, the learning rate, and the momentum. A selected list of addresses on the Internet is appended for obtaining information on artificial neural networks such as software availability, conferences, etc. The great advantages of BNNs are their ability to find nonlinear or multilinear relationships, learning from examples, and making successful interpolations (less so for extrapolations), even starting from a set of noisy, incomplete, and sometimes faulty data. In order to counter some of the drawbacks of BNNs, one has to devise validation tests which are reviewed critically. Other paradigms are also presented in the book. Thus, Kohonen mapping and ReNDeR (reversible nonlinear dimension reduction) are introduced by Livingstone in a chapter entitled MultiVariate Data Display Using Neural Networks and illustrated by Manallack and co-workers in a chapter dealing with nicotinic agonists. The adaptive resonance theory (ART) neural networks are discussed in the chapter AdaptiVe Resonance Theory Based Neural Networks Explored for Pattern Recognition Analysis of QSAR Data by Wienke and co-workers, and an original hybrid mapping called nonlinear neural mapping (N2M) is clearly presented in the chapter entitled A New Nonlinear Neural Mapping Technique for Visual Exploration of QSAR Data by Domine and co-workers. A chapter by Gasteiger and his co-workers is entitled EValuation of Molecular Surface Properties Using a Kohonen Neural Network; it is illustrated with color plates and deals with data sets of ryanodines, cardiac glycosides, and steroids. Maggiora and co-workers provided a chapter entitled Combining Fuzzy Clustering and Neural Networks to Predict Protein Structural Classes, illustrating thereby a hybrid system. This chapter is accompanied by a color plate with stereo drawings showing how one can group together structural classes of proteins, namely all-R helices,
