`Tools of the trade'

BOOKS

described in the other chapters intopractical therapies for human disease.

As in most multiauthor

compilations, the quality is variable but mostly very high. Only a fewcontributions are over-focused on thework of the authors. There is significantoverlap between some chapters, but inmany cases, the presentation ofdifferent viewpoints works to the

reader’s advantage. There are

exhaustive reference lists, but not everychapter has clear figures and tables. Ingeneral there is an admirable scope ofcoverage, despite the absence ofchapters on important topics, such asDNA repair in bacteriophage orDrosophila, and structures of DNA-repair proteins. But writing for bookslike this is essentially done as a

community service and we should beespecially grateful to the contributorsand editors.

Richard D. Wood

Imperial Cancer Research Fund, Clare Hall

Laboratories, South Mimms, Herts,

UK EN6 3LD.

project today is a database search orother computational analysis. Thus, it isessential for molecular biologists tohave a good understanding of theavailable biocomputing tools and howthey work. But given the explosion oftools available both on the World WideWeb and as standalone programs, howdoes one keep abreast of new

developments? Books such as Guide toHuman Genome Computing can helpbridge the gap for the investigator.

The Human Genome Project (HGP)is generating many hundreds of

megabytes of information consisting ofsequence, various types of maps andother data. The tools to process andmanage these data are the subject ofGuide to Human Genome Computing.Although it is by no means a

comprehensive guide to biocomputing,the book does cover topics relevant toall of the major goals of the HGP asstated on the National Human GenomeResearch Institute web pages andprovides a sampling of techniques and tools useful for scientists involvedin the HGP.

collection of articles by a dozen or soauthors, was published in 1994. Althoughthere is some overlap in the two books,this new edition does include chapterson many more types of maps and hasupdated information on topics that havechanged. Because of the time lag

between writing manuscripts and theirpublication, books are often hopelesslyout of date before they go to press.Despite some dated information, I waspleasantly surprised to see that therewere many useful chapters included(e.g. comparative mapping, radiationhybrids, human genome sequencing,ESTs, gene prediction, etc.), which at aminimum provide a good starting pointfor further exploration. There are,however, some recently emergingtopics that are not covered in thissecond edition (e.g. functional

genomics, chip informatics). But someof the references in the bibliographiesmay help guide the savvy reader tomore current information.

The style of most chapters is first abrief introduction to the biology relatedto the computational tools being

described and then a description of thetools. One chapter that should appeal toa wide audience provides an excellent,‘illustrated tour of the World Wide Webfrom the genome biologist’s

perspective’. Another chapter, whichmay appeal to a more limited audience,provides a detailed description of howto set up and manage a database ofpedigree and genotyping data completewith the structured query language(SQL) to define a database. Each

chapter in the Guide does provide the‘working scientist’ (the stated intendedaudience) with background informationfor particular computational tools, mostof which are freely available to

academic sites. Tools that are not webbased generally run on Unix machinesrather than on personal computers.

When all is said and done, it wouldbe very difficult to publish a book that is‘everything to everybody’. Nevertheless,this Guide will be a useful reference forbioinformatics old-timers and will behelpful also to introduce someone newto the computational tools relevant tothe HGP. However, for the most currentdetail, readers will have to refer to theonline resources available from the sitesdeveloping the tools.

Fran Lewitterlewitter@wi.mit.edu

Whitehead Institute for Biomedical Research,Nine Cambridge Center, Cambridge,

MA 02142-1479, USA.

Authors’ correction

How many homeobox genes does it take to make a pituitary gland? by Dawn E. Watkins-Chow and Sally A. Camper (Trends Genet. 14, 284–290)

There are two errors in this Review article, which are corrected here:

The correct Ref. 18 is Li, H. et al. (1994) EMBO J. 13, 2876–2885

The text on p. 285 and in Table 2 should refer to Gsh4 (Lhx4) instead of Gsh1.

The effects of Gsh1 on pituitary development are described in Li, H. et al. (1996) EMBO J. 15, 714–724

TIGOCTOBER1998 VOL. 14 NO. 10

Copyright © 1998 Elsevier Science Ltd. All rights reserved. 0168-9525/98/$19.00

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