Bioinformatics,
`a new
`interdisciplinary
`science, is
`essential to
`managing,
`understanding,
`and harnessing
`clinical benefit
`from new
`genetic data
`
`Centre for
`Integrated Genomic
`Medical Research,
`University of
`Manchester,
`Manchester
`M13 9PT
`Ardeshir Bayat
`MRC fellow
`
`Correspondence to:
`ardeshir.bayat@
`man.ac.uk
`
`BMJ 2002;324:1018–22
`
`Clinical review
`
`Science, medicine, and the future
`Bioinformatics
`Ardeshir Bayat
`
`An unprecedented wealth of biological data has been
`generated by the human genome project and sequenc(cid:173)
`ing projects in other organisms. The huge demand for
`analysis and interpretation of these data is being man(cid:173)
`aged by the evolving science of bioinformatics.
`Bioinformatics is defined as the application of tools of
`computation and analysis to the capture and interpret(cid:173)
`ation of biological data. It is an interdisciplinary field,
`which harnesses computer science, mathematics, phys(cid:173)
`ics, and biology (fig 1). Bioinformatics is essential for
`management of data in modern biology and medicine.
`This paper describes the main tools of the bioinforma(cid:173)
`tician and discusses how they are being used to
`interpret biological data and to further understanding
`of disease. The potential clinical applications of these
`data in drug discovery and development are also
`discussed.
`
`Methods
`
`This article is based on personal experience in
`bioinformatics and on selected articles in recent issues
`of Nature Genetics, Nature Genetics Reviews, Nature Medi(cid:173)
`cine, and Science. Key terms including bioinformatics,
`comparative and functional genomics, proteomics,
`microarray, disease, and medicine were used to search
`for relevant articles in the peer reviewed scientific
`literature.
`
`Bioinformatics and its impact on
`genomics
`
`Last year it was announced that the entire human
`genome had been mapped as a result of the efforts of
`
`Biology
`
`Medicine
`
`Bioinformatics
`
`Maths/physics
`
`Computer science
`
`An additional figure
`appears on
`bmj.com
`
`1018
`
`Fig 1 Interaction of disciplines that have contributed to the
`formation of bioinformatics
`
`Summary points
`
`Bioinformatics is the application of tools of
`computation and analysis to the capture and
`interpretation of biological data
`
`Bioinformatics is essential for management of
`data in modern biology and medicine
`
`The bioinformatics toolbox includes computer
`software programs such as BLAST and Ensembl,
`which depend on the availability of the internet
`
`Analysis of genome sequence data, particularly
`the analysis of the human genome project, is one
`of the main achievements of bioinformatics to
`date
`
`Prospects in the field of bioinformatics include its
`future contribution to functional understanding
`of the human genome, leading to enhanced
`discovery of drug targets and individualised
`therapy
`
`the worldwide human genome project and a private
`genomic company.1 2 However, in recent years, the sci(cid:173)
`entific world has witnessed the completion of whole
`genome sequences of many other organisms. The
`analysis of the emerging genomic sequence data and
`the human genome project is a landmark achievement
`for bioinformatics.
`A novel strategy for random sequencing of the
`whole genome (the so called “shot gun” technique) was
`used to sequence the genome of Haemophilus influenzae
`in 1995.3 This was the very first complete genome of
`any free living organism to be sequenced. Other bacte(cid:173)
`rial genomes, such as those of Mycoplasma genitalium
`and Mycobacterium tuberculosis, were sequenced soon
`after,4 5 and the sequence of the plague bacterium Yers(cid:173)
`inia pestis was recently completed.6 The sequence and
`annotation of the first eukaryotic genome, that of Sac(cid:173)
`charomyces cerevisiae (a yeast),7 was followed by those of
`other eukaryotic species such as Caenorhabtidis elegans
`(a worm),8 Drosophila melanogaster (fruit fly),9 and Arab(cid:173)
`dopsis thaliana (mustard weed)10 (see fig A on bmj.com).
`Sequencing of
`several other
`species,
`including
`
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`

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`Useful bioinformatic websites (available freely
`on the internet)
`• National Center for Biotechnology Information
`(www.ncbi.nlm.nih.gov)—maintains bioinformatic tools
`and databases
`• National Center for Genome Resources
`(www.ncgr.org/)—links scientists to bioinformatics
`solutions by collaborations, data, and software
`development
`• Genbank (www.ncbi.nlm.nih.gov/Genbank)—stores
`and archives DNA sequences from both large scale
`genome projects and individual laboratories
`• Unigene (www.ncbi.nlm.nih.gov/UniGene)—gene
`sequence collection containing data on map location
`of genes in chromosomes
`• European Bioinformatic Institute
`(www.ebi.ac.uk)—centre for research and services in
`bioinformatics; manages databases of biological data
`• Ensembl (www.ensembl.org)—automatic annotation
`database on genomes
`• BioInform (www.bioinform.com)—global
`bioinformatics news service
`• SWISS(cid:173)PROT (www.expasy.org/sprot/)—important
`protein database with sequence data from all
`organisms, which has a high level of annotation
`(includes function, structure, and variations) and is
`minimally redundant (few duplicate copies)
`• International Society for Computational Biology
`(www.iscb.org/)—aims to advance scientific
`understanding of living systems through computation;
`has useful bioinformatic links
`
`zebrafish, pufferfish, mouse, rat, and non(cid:173)human
`primates, are either under way or nearing completion
`by both private and public sequencing initiatives.11 The
`knowledge obtained from these sequence data will
`have considerable implications for our understanding
`of biology and medicine. As a result of comparative
`genomic and proteomic research, we will soon be able
`to not only locate each human gene but also fully
`understand its function.12
`
`Bioinformatic tools
`
`The main tools of a bioinformatician are computer
`software programs and the internet. A fundamental
`activity is sequence analysis of DNA and proteins using
`various programs and databases available on the world
`wide web. Anyone,
`from clinicians
`to molecular
`biologists, with access to the internet and relevant web(cid:173)
`sites can now freely discover the composition of
`biological molecules such as nucleic acids and proteins
`by using basic bioinformatic tools. This does not imply
`that handling and analysis of raw genomic data can
`easily be carried out by all. Bioinformatics is an evolv(cid:173)
`ing discipline, and expert bioinformaticians now use
`complex software programs for retrieving, sorting out,
`analysing, predicting, and storing DNA and protein
`sequence data.
`Large commercial enterprises such as pharmaceu(cid:173)
`tical companies employ bioinformaticians to perform
`and maintain the large scale and complicated bioinfor(cid:173)
`matic needs of
`these industries. With an ever(cid:173)
`increasing need for constant input from bioinformatic
`experts, most biomedical laboratories may soon have
`their own in(cid:173)house bioinformatician. The individual
`
`BMJ VOLUME 324 27 APRIL 2002 bmj.com
`
`Clinical review
`
`researcher, beyond a basic acquisition and analysis of
`simple data, would certainly need external bioinfor(cid:173)
`matic advice for any complex analysis.
`The growth of bioinformatics has been a global
`venture, creating computer networks that have allowed
`easy access to biological data and enabled the develop(cid:173)
`ment of software programs for effortless analysis.
`Multiple international projects aimed at providing
`gene and protein databases are available freely to the
`whole scientific community via the internet.
`
`Bioinformatic analysis
`
`The escalating amount of data from the genome
`projects has necessitated computer databases that fea(cid:173)
`ture rapid assimilation, usable formats and algorithm
`software programs
`for efficient management of
`biological data.13 Because of the diverse nature of
`emerging data, no single comprehensive database
`exists for accessing all this information. However, a
`growing number of databases that contain helpful
`information for clinicians and researchers are avail(cid:173)
`able. Information provided by most of these databases
`is free of charge to academics, although some sites
`require subscription and industrial users pay a licence
`fee for particular sites. Examples range from sites pro(cid:173)
`viding comprehensive descriptions of clinical disor(cid:173)
`ders,
`listing disease susceptibility genetic mutations
`and polymorphisms, to those enabling a search for dis(cid:173)
`ease genes given a DNA sequence (box).
`These databases include both “public” repositories
`of gene data as well as those developed by private com(cid:173)
`panies. The easiest way to identify databases is by
`
`Fig 2 Ensembl website: a genomic data search facility freely available on the internet.
`Ensembl is a joint project between the European Bioinformatic Institute and the Sanger
`Centre, which is capable of automatically tracking the sequenced pieces of the human
`genome and assembling and analysing them to identify genes and other features of interest
`to biomedical researchers
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`

`

`database links and searchable indexes provided by one
`of
`the major public databases. For example,
`the
`National Center
`for Biotechnology
`Information
`(www.ncbi.nlm.nih.gov) provides the Entrez browser,
`which is an integrated database retrieval system that
`allows integration of DNA and protein sequence data(cid:173)
`bases. The European Bioinformatic Institute archives
`gene and protein data from genome studies of all
`organisms, whereas Ensembl produces and maintains
`automatic annotation on eukaryotic genomes (fig 2).
`The quality and reliability of databases vary; certainly
`some of the better known and more established ones,
`such as those above, are superior to others.
`One of the simplest and better known search tools
`is called BLAST (basic local alignment search tool, at
`www.ncbi.nlm.nih.gov/BLAST/). This algorithm soft(cid:173)
`ware is capable of searching databases for genes with
`similar nucleotide structure (fig 3) and allows compari(cid:173)
`son of an unknown DNA or amino acid sequence with
`hundreds or thousands of sequences from human or
`other organisms until a match is found. Databases of
`known sequences are thus used to identify similar
`sequences, which may be homologues of the query
`sequence. Homology implies that sequences may be
`related by divergence from a common ancestor or
`share common functional aspects. When a database is
`searched with a newly determined sequence (the query
`sequence), local alignment occurs between the query
`sequence and any similar sequence in the database.
`The result of the search is sorted in order of priority on
`the basis of maximum similarity. The sequence with the
`highest score in the database of known genes is the
`homologue. If homologues or related molecules exist
`for a query sequence, then a newly discovered protein
`may be modelled and the gene product may be
`predicted without
`the need for further laboratory
`experiments.
`
`Functional genomics
`
`Since the completion of the first draft of the human
`genome,1 2
`the emphasis has been changing from
`genes themselves to gene products. Functional genom(cid:173)
`ics assigns functional relevance to genomic infor(cid:173)
`mation. It is the study of genes, their resulting proteins,
`and the role played by the proteins.
`Analysis and interpretation of biological data con(cid:173)
`siders information not only at the level of the genome
`but at the level of the proteome and the transcriptome
`(fig 4). Proteomics is the analysis of the total amount of
`proteins (proteome) expressed by a cell, and transcrip(cid:173)
`tomics refers to the analysis of the messenger RNA
`transcripts produced by a cell (transcriptome). DNA
`microarray technology determines the expression level
`of genes and includes genotyping and DNA sequenc(cid:173)
`ing. Gene expression arrays allow simultaneous analy(cid:173)
`sis of
`the messenger RNA expression levels of
`thousands of genes in benign and malignant tumours,
`such as keloid and melanoma. Expression profiles clas(cid:173)
`sify
`tumours and provide potential
`therapeutic
`targets.14
`Bioinformatic protein research draws on annotated
`protein and two dimensional electrophoresis data(cid:173)
`bases. After separation, identification, and characterisa(cid:173)
`tion of a protein, the next challenge in bioinformatics is
`the prediction of its structure. Structural biologists also
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`BMJ VOLUME 324 27 APRIL 2002 bmj.com
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`Clinical review
`
`Fig 3 Web page illustrating freely available BLAST services run by
`the National Center for Biotechnology Information. BLAST (basic local
`alignment search tool) is a set of similarity search programs
`designed to explore all of the available DNA sequence databases
`
`searching for bioinformatic tools and databases in any
`one of the commonly used search engines. Another
`way to identify bioinformatic sources is through
`
`I
`
`...agcttgatattatacgcgcggca
`
`II
`
`III
`
`IV
`
`Genomics
`
`DNA
`
`Makes
`
`Transcriptomics
`
`RNA
`
`Makes
`
`Proteomics
`
`Protein
`
`C o m p l e x i t y
`
`Fig 4 Schematic diagram representing complexity of genomic data processing. Analysis and
`interpretation of biological data considers information at every level from the genome (total
`genetic content) to the proteome (total protein content) and transcriptome (total messenger
`RNA content) of the cell. The images numbered I(cid:173)IV to the right of the diagram represent
`relevant examples of DNA (image I is base pair nucleotides); RNA (image II is a microarray
`showing levels of gene expression); and protein (image III is a structure of a single protein;
`image IV is a two dimensional gel electrophoresis showing separation of all proteins of a
`cell—each spot corresponds to a different protein chain)
`
`1020
`
`

`

`use bioinformatics to handle the vast and complex data
`from x ray crystallography, nuclear magnetic reso(cid:173)
`nance, and electron microscopy investigations to create
`three dimensional models of molecules.15
`
`Other applications of bioinformatics
`
`from analysis of genome sequence data,
`Apart
`bioinformatics is now being used for a vast array of
`other important tasks, including analysis of gene varia(cid:173)
`tion and expression, analysis and prediction of gene
`and protein structure and function, prediction and
`detection of gene regulation networks, simulation envi(cid:173)
`ronments for whole cell modelling, complex modelling
`of gene regulatory dynamics and networks, and
`presentation and analysis of molecular pathways in
`interactions.16
`order
`to understand gene(cid:173)disease
`Although on a smaller scale, simpler bioinformatic
`tasks valuable to the clinical researcher can vary from
`designing primers (short oligonucleotide sequences
`needed for DNA amplification in polymerase chain
`reaction experiments) to predicting the function of
`gene products.
`
`Clinical application of bioinformatics
`
`The clinical applications of bioinformatics can be
`viewed in the immediate, short, and long term. The
`human genome project plans to complete the human
`sequence by 2003, producing a database of all the vari(cid:173)
`ations in sequence that distinguish us all. The project
`could have considerable impact on people living in
`2020—for example, a complete list of human gene
`products may provide new drugs and gene therapy for
`single
`gene
`diseases may
`become
`routine
`(www.ornl.gov/hgmis/medicine/tnty.html).
`Basic bioinformatic tools are already accessed in
`certain clinical situations to aid in diagnosis and treat(cid:173)
`ment plans. For example, PubMed (www.nlm.nih.gov)
`is accessed freely for biomedical
`journals cited in
`Medline, and OMIM (Online Mendelian Inheritance in
`Man at www3.ncbi.nlm.nih.gov/Omim/), a search tool
`for human genes and genetic disorders, is used by cli(cid:173)
`nicians to obtain information on genetic disorders in
`the clinic or hospital setting. An example of the appli(cid:173)
`cation of bioinformatics in new therapeutic advances is
`the development of novel designer targeted drugs such
`as imatinib mesylate (Gleevec), which interferes with
`the abnormal protein made in chronic myeloid
`leukaemia.17
`(Imatinib mesylate was synthesised at
`Novartis Pharmaceuticals by identifying a lead in a
`high throughput screen for tyrosine kinase inhibitors
`and optimising its activity for specific kinases.) The
`ability to identify and target specific genetic markers by
`using bioinformatic tools facilitated the discovery of
`this drug.
`In the short term, as a result of the emerging bioin(cid:173)
`formatic analysis of the human genome project, more
`disease genes will be identified and new drug targets
`will be simultaneously discovered. Bioinformatics will
`serve to identify susceptibility genes and illuminate the
`pathogenic pathways involved in illness, and will there(cid:173)
`fore provide an opportunity for development of
`targeted therapy. Recently, potential targets in cancers
`were identified from gene expression profiles.18
`
`BMJ VOLUME 324 27 APRIL 2002 bmj.com
`
`Clinical review
`
`Additional educational resources
`
`Journals
`• Specific bioinformatic journals exist (for example,
`www.bioinformatics.oupjournals.org), but papers from
`every area of science and medicine involving
`bioinformatic analysis are published in any biomedical
`journal. Examples include:
`• The human genome (special issue). Nature
`2001;409:813(cid:173)933.
`• The human genome (special issue). Science
`2001;5507:1145(cid:173)434.
`• The human genome (special issue). JAMA
`2001;286:2211(cid:173)333.
`• The human genome (special issue). Scientific
`American 2000;283:38(cid:173)57.
`• Luscombe NM, Greenbaum D, Gerstein M. What is
`bioinformatics? Method Inform Med 2001;40:346(cid:173)58.
`• Online Lectures on Bioinformatics
`(www.lectures.molgen.mpg.de/)
`
`Books
`• Mount DW. Bioinformatics: sequence and genome
`analysis. Cold Spring Harbor Laboratory Press, 2001.
`• Baxevanis AD, Ouellette BFF. Bioinformatics: a
`practical guide to the analysis of genes and proteins. 2nd ed.
`John Wiley and Sons, 2001.
`• Lengauer T (Ed). Bioinformatics. Wiley(cid:173)VCH Series,
`2001. (Methods and principles in medicinal chemistry
`series.)
`• Higgins D, Taylor W. Bioinformatics. Oxford
`University Press, 2000. (Practical approach series.)
`• Baldi P, Brunak S. Bioinformatics. 2nd ed. MIT Press,
`2001. (Adaptive computation and machine learning
`series.)
`
`BMJ archive
`• Aitman TJ. DNA microarrays in medical practice.
`BMJ 2001;323:611(cid:173)5.
`• Mathew CG. Postgenomic technologies: hunting the
`genes for common disorders. BMJ 2001;322:1031(cid:173)4.
`• Stewart A, Haites N, Rose P. Online medical genetics
`resources: a UK perspective. BMJ 2001;322:1037(cid:173)9.
`• Savill J. Molecular genetic approaches to
`understanding disease. BMJ 1997;314:126(cid:173)9.
`
`In the longer term, integrative bioinformatic analy(cid:173)
`sis of genomic, pathological, and clinical data in clinical
`trials will reveal potential adverse drug reactions in
`individuals by use of simple genetic tests. Ultimately,
`pharmacogenomics (using genetic information to
`individualise drug treatment) is likely to bring about a
`new age of personalised medicine; patients will carry
`gene cards with their own unique genetic profile for
`certain drugs aimed at individualised therapy and tar(cid:173)
`geted medicine free from side effects.
`
`Future directions
`
`The practice of studying genetic disorders is changing
`from investigation of single genes in isolation to
`discovering cellular networks of genes, understanding
`their complex interactions, and identifying their role in
`disease.19 As a result of this, a whole new age of
`individually tailored medicine will emerge. Bioinfor(cid:173)
`matics will guide and help molecular biologists and
`clinical researchers to capitalise on the advantages
`brought by computational biology.20 The clinical
`
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`

`Clinical review
`
`research teams that will be most successful in the com(cid:173)
`ing decades will be those that can switch effortlessly
`between the laboratory bench, clinical practice, and the
`use of these sophisticated computational tools.
`
`I thank Tessa Richards, Dipak Roy, and Professor Bill Ollier for
`advice on the preparation of this manuscript and Andy Brass for
`providing me with some of the diagrams.
`Funding: Medical Research Council.
`Competing interests: None declared.
`
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`2 Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, et al. The
`sequence of the human genome. Science 2001;291:1304(cid:173)51.
`3 Fleischmann RD, Adams MD, White O, Clayton RA, Kirkness EF, Kerlav(cid:173)
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`4 Fraser CM, Gocayne JD, White O, Adams MD, Clayton RA, Fleischmann
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`Science 1995;270:397(cid:173)403.
`5 Cole ST, Brosch R, Parkhill J, Garnier T, Churcher C, Harris D, et al. Deci(cid:173)
`phering the biology of Mycobacterium tuberculosis from the complete
`genome sequence. Nature 1998;393:537(cid:173)44.
`6 Parkhill J, Wren BW, Thomson NR, Titball RW, Holden MT, Prentice MB,
`et al. Genome sequence of Yersinia pestis, the causative agent of plague.
`Nature 2001;413:523(cid:173)27.
`7 Goffeau A, Barrell BG, Bussey H, Davis RW, Dujon B, Feldmann H, et al.
`Life with 6000 genes. Science 1996;274:546.
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`8 The C. elegans Sequencing Consortium. Genome sequence of the nema(cid:173)
`tode C. elegans: a platform for
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`9 Myers EW, Sutton GG, Delcher AL, Dew IM, Fasulo DP, Flanigan MJ, et al.
`A whole(cid:173)genome assembly of Drosophila. Science 2000;287:2196(cid:173)204.
`10 Arabidopsis Genomics Initiative. Analysis of the genome sequence of the
`flowering plant Arabidopsis thaliana. Nature 2000;408:796(cid:173)815.
`11 Stein L. Genome annotation: from sequence to biology. Nat Rev Genet
`2001;2:493(cid:173)503.
`12 Subramanian G, Adams MD, Venter JC, Broder S. Implications of the
`human genome for understanding human biology and medicine. JAMA
`2001;286:2296(cid:173)306.
`13 Benton D. Bioinformatics—principles and potential of a new multidisci(cid:173)
`plinary tool. Trends Biotech 1996;14:261(cid:173)312.
`14 Maggio ET, Ramnarayan K. Recent developments in computational pro(cid:173)
`teomics. Trends Biotech 2001;19:266(cid:173)72.
`15 Burley SK, Almo SC, Bonanno JB, Capel M, Chance MR, Gaasterland T,
`et al. Structural genomics: beyond the human genome project. Nat Genet
`1999;23:151(cid:173)7.
`16 Tsoka S, Ouzounis CA. Recent developments and future directions in
`computational genomics. FEBS Lett 2000;480:42(cid:173)8.
`17 Druker BJ, Sawyers CL, Kantarjian H, Resta DJ, Reese SF, Ford JM, et al.
`Activity of a specific inhibitor of the BCR(cid:173)ABL tyrosine kinase in the blast
`crisis of chronic myeloid leukemia and acute lymphoblastic leukemia
`with the Philadelphia chromosome. N Engl J Med 2001;344:1038(cid:173)42.
`18 Graeber TG, Eisenberg D. Bioinformatic identification of potential auto(cid:173)
`crine signaling loops in cancers from gene expression profiles. Nat Genet
`2001;29:295(cid:173)300.
`19 Debouk C, Metcalf B. The impact of genomics on drug discovery. Annu
`Rev Pharmacol Toxicol 2000;40:193(cid:173)208.
`20 Butler D. Are you ready for the revolution? Nature 2001;409:758(cid:173)60.
`
`When I use a word
`Meta(cid:173)
`
`Mr John Gleave, a neurosurgeon, has written to ask me
`the origin of the meta(cid:173) in meta(cid:173)analysis. The answer
`comes from Aristotle.
`The Greek preposition ♯♦♸♡´ (meta) had several
`meanings, depending on whether it governed the
`accusative, genitive, or dative case. With the accusative
`it could mean coming into or among, in pursuit of, or
`coming after in place or time; with the genitive it could
`mean in the midst of, between, or in common with;
`and with the dative it could mean in the company of or
`over and above. It was also used as a prefix to express
`such notions as sharing, being in the midst of,
`succession, pursuit, reversal, and (most commonly)
`change. Examples of the last include metabolism,
`metamorphosis, and metaplasia.
`In scientific English words its uses include
`“consequent upon” (as in the obsolete terms
`meta(cid:173)arthritic, metapneumonic), “behind” or “beyond”
`in an anatomical sense (metabranchial, metacarpal,
`metaphysis), “coming later” (metaphase, which comes
`after prophase), or “changing” (metachromasia, a
`property of materials that stain a different colour from
`the stain used). In geology meta(cid:173) is used to distinguish
`various types of metamorphic processes. And chemists
`use meta(cid:173) to differentiate certain metameric chemical
`compounds (such as metacresol, paracresol,
`orthocresol).
`And so to Aristotle. Some 250 years after his death,
`Aristotle’s manuscripts came into the hands of
`Andronicus of Rhodes, who edited them. Andronicus
`called one set of papers The Physics (♸♡` *♲♹♶♬♭♡´), dealing
`as they did with natural science. Then he published a
`set of papers that he called The Metaphysics (♸♡` ♯♦♸♡` ♸♡`
`*♲♹♶♬♭♡´), simply because it came after The Physics.
`However, because The Metaphysics dealt with what
`Aristotle called “primary philosophy,” or ontology,
`metaphysics came to be misunderstood as “the science
`of that which transcends the physical.”
`As a result, the prefix meta(cid:173) was then used to
`designate any higher science (actual or hypothetical)
`that dealt with more fundamental problems than the
`original science itself. This use first appeared in the
`
`1022
`
`early 17th century (John Donne, for example, writes
`about metatheology) but did not become really
`popular until the middle of the 19th century. Examples
`include metaethics (the study of the foundations of
`ethics, especially the nature of ethical statements) and
`metahistory (an inquiry into the principles that govern
`historical events).
`Then, from about 1940, it became commonplace to
`prefix meta(cid:173) to designate concern with basic principles.
`A metacriterion is a criterion that defines criteria. A
`metatheorem is a theorem about theorems. A
`metalanguage is a language that supplies terms for
`analysing a language; a metametalanguage does the
`same for a metalanguage. And Jean Tinguely described
`his machine(cid:173)like sculptures as “metamechanical.” (But
`a metaphysician is not a doctor’s doctor.)
`In these poststructuralist times we recognise many
`metaforms. Mantissa, a medical novel by John Fowles, is
`metafiction; Francois Truffaut’s film La Nuit Amercaine
`is metacinema; several paintings by Magritte, notably
`La Condition Humaine, are meta(cid:173)art; and John Cage’s
`piano piece 4’33’’ is metamusic.
`So meta(cid:173)analysis is an analysis of analyses, in which
`sets of previously published (or unpublished) data are
`themselves subjected as a whole to further analysis. In
`this statistical sense it was first used in the 1970s by GV
`Glass (Educ Res 1976;3(Nov):2). As he wrote, “The term
`is a bit grand, but it is precise and apt.” Incidentally,
`meta(cid:173)analysis should not be confused with metanalysis,
`which is the process whereby, for example, “a nadder”
`becomes “an adder” (see BMJ 1999;318:1758 and
`2000;321:953).
`I trust that this cures Mr Gleave’s metagrobolism.
`
`Jeff Aronson clinical pharmacologist, Oxford
`
`We welcome articles up to 600 words on topics such as
`A memorable patient, A paper that changed my practice, My
`most unfortunate mistake, or any other piece conveying
`instruction, pathos, or humour. If possible the article
`should be supplied on a disk. Permission is needed
`from the patient or a relative if an identifiable patient is
`referred to.
`
`Petitioner Microsoft Corporation - Ex. 1029, p. 1022
`
`BMJ VOLUME 324 27 APRIL 2002 bmj.com
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`