Bioinformatics—An Introduction for Computer ScientistsJACQUES COHENBrandeis UniversityAbstract. The article aims to introduce computer scientists to the new field ofbioinformatics. This area has arisen from the needs of biologists to utilize and helpinterpret the vast amounts of data that are constantly being gathered in genomicresearch—and its more recent counterparts, proteomics and functional genomics. Theultimate goal of bioinformatics is to develop in silico models that will complement invitro and in vivo biological experiments. The article provides a bird’s eye view of thebasic concepts in molecular cell biology, outlines the nature of the existing data, anddescribes the kind of computer algorithms and techniques that are necessary tounderstand cell behavior. The underlying motivation for many of the bioinformaticsapproaches is the evolution of organisms and the complexity of working with incompleteand noisy data. The topics covered include: descriptions of the current softwareespecially developed for biologists, computer and mathematical cell models, and areas ofcomputer science that play an important role in bioinformatics.Categories and Subject Descriptors: A.1 [Introductory and Survey]; F.1.1[Computation by Abstract Devices]: Models of Computation—Automata (e.g., finite,push-down, resource-bounded);F.4.2 [Mathematical Logic and Formal Languages]:Grammars and Other Rewriting Systems; G.2.0 [Discrete Mathematics]: General;G.3 [Probability and Statistics]; H.3.0 [Information Storage and Retrieval]:General; I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, andSearch; I.5.3 [Pattern Recongnition]: Clustering; I.5.4 [Pattern Recongnition]:Applications—Text processing; I.6.8 [Simulation and Modeling]: Types ofSimulation—Continuous; discrete event; I.7.0 [Document and Text Processing]:General; J.3 [Life and Medical Sciences]: Biology and geneticsGeneral Terms: Algorithms, Languages, TheoryAdditional Key Words and Phrases: Molecular cell biology, computer, DNA, alignments,dynamic programming, parsing biological sequences, hidden-Markov-models,phylogenetic trees, RNA and protein structure, cell simulation and modeling,microarray1. INTRODUCTIONIt is undeniable that, among the sciences,biology played a key role in the twentiethcentury. That role is likely to acquire fur-ther importance in the years to come. Inthe wake of the work of Watson and Crick,Author’s address: Department of Computer Science, Brandeis University, Waltham, MA 02454; email: [email protected] to make digital/hard copy of part or all of this work for personal or classroom use is grantedwithout fee provided that the copies are not made or distributed for profit or commercial advantage, thecopyright notice, the title of the publication, and its date appear, and notice is given that copying is bypermission of ACM, Inc. To copy otherwise, to republish, to post on servers, or to redistribute to lists requiresprior specific permission and/or a fee.c2004 ACM 0360-0300/04/0600-0122 $5.00[2003] and the sequencing of the humangenome, far-reaching discoveries are con-stantly being made.One of the central factors promoting theimportance of biology is its relationshipwith medicine. Fundamental progress inmedicine depends on elucidating some ofACM Computing Surveys, Vol. 36, No. 2, June 2004, pp. 122–158.Bioinformatics—An Introduction for Computer Scientists 123the mysteries that occur in the biologicalsciencesBiology depended on chemistry to makemajor strides, and this led to the de-velopment of biochemistry. Similarly, theneed to explain biological phenomena atthe atomic level led to biophysics. Theenormous amount of data gathered bybiologists—and the need to interpret it—requires tools that are in the realm of com-puter science. Thus, bioinformatics.Both chemistry and physics have bene-fited from the symbiotic work done withbiologists. The collaborative work func-tions as a source of inspiration for novelpursuits in the original science. It seemscertain that the same benefit will ac-crue to computer science—work with bi-ologists will inspire computer scientists tomake discoveries that improve their owndiscipline.A common problem with the matu-ration of an interdisciplinary subject isthat, inevitably, the forerunner disciplinescall for differing perspectives. I see thesedifferences in working with my biolo-gist colleagues. Nevertheless, we are sointerested in the success of our dia-logue, that we make special efforts tounderstand each other’s point of view.That willingness is critical for jointwork, and this is particularly true inbioinformatics.An area called computational biologypreceded what is now called bioinformat-ics. Computational biologists also gath-ered their inspiration from biology and de-veloped some very important algorithmsthat are now used by biologists. Computa-tional biologists take justified pride in theformal aspects of their work. Those ofteninvolve proofs of algorithmic correctness,complexity estimates, and other themesthat are central to theoretical computerscience.Nevertheless, the biologists’ needs areso pressing and broad that many other as-pects related to computer science have tobe explored. For example, biologists needsoftware that is reliable and can deal withhuge amounts of data, as well as inter-faces that facilitate the human-machineinteractions.I believe it is futile to argue the differ-ences and scope of computational biologyas compared to bioinformatics. Presently,the latter is more widely used among biol-ogists than the former, even though thereis no agreed definition for the two terms.A distinctive aspect of bioinformatics isits widespread use of the Web. It couldnot be otherwise. The immense databasescontaining DNA sequences and 3D pro-tein structures are available to almostany researcher. Furthermore, the commu-nity interested in bioinformatics has de-veloped a myriad of application programsaccessible through the Internet. Some ofthese programs (e.g., BLAST) have takenyears of development and have been finelytuned. The vast numbers of daily visitsto some of the NIH sites containing ge-nomic databases are comparable to thoseof widely used search engines or activesoftware downloading sites. This explainsthe great interest that bioinformaticianshave in script languages such as Perl andPython that allow the automatic exami-nation and gathering of information fromwebsites.With the above preface, we can put for-ward the
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