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C O M M E N TA R Y
Systems biology has spurred interest inthousands of researchers, some just startingtheir careers, others well established butinterested in learning more about it. What isthe best plan for scientists and studentsinterested in a career in systems biology?
Why the excitement?The use of systematic genomic, proteomicand metabolomic technologies to constructmodels of complex biological systems anddiseases is becoming increasingly common-place. These endeavors, collectively knownas systems biology1,2, establish an approachby which to interrogate and iterativelyrefine our knowledge of the cell. In sodoing, systems biology integrates knowl-edge from diverse biological componentsand data into models of the system as awhole.
Although the notion of systems sciencehas existed for some time3, these approacheshave recently become far more powerfulbecause of a host of new experimental tech-nologies that are high-throughput, quanti-tative and large-scale4. As evidence of theimpact ‘systems’ thinking has had on biol-ogy, consider the explosive growth of newresearch institutes, companies, conferencesand academic departments that have thewords ‘systems biology’ in the title or mis-sion statement. Several journals are noweither entirely devoted to reporting systemsbiology research or are sponsoring regularsections devoted to current issues in systemsor computational biology, such as this inau-gural section in Nature Biotechnology. Andunder the leadership of Elias Zerhouni, theNational Institutes of Health (Bethesda,MD, USA) has released a new ‘roadmap’ thatincludes interdisciplinary science and inte-grative systems biology as core focus areas5;the UK’s Biotechnology and BiologicalSciences Research Council has also targetedpredictive and integrated biology as a strate-gic aim over the next five years6.
Where to startBecause of the need to couple computationalanalysis techniques with systematic biologi-cal experimentation, more and more univer-sities are offering PhD programs thatintegrate both computational and biologicalsubject matter (Table 1). Several of theseprograms, such as those recently initiated bythe Massachusetts Institute of Technology(MIT, Cambridge, MA, USA) and HarvardUniversity (Cambridge, MA, USA), include‘systems biology’ directly in the name.Others offer courses of study from withinphysics, engineering or biology departments(e.g., the systems biology syllabus within thebioengineering department at the Universityof California, San Diego, CA, USA).
Apart from PhD programs with courseofferings in systems biology, a number ofinstitutions offer intensive short courses(Table 2). These include the Institute forSystems Biology (Seattle, WA, USA), OxfordUniversity (Oxford, UK) and BiocentrumAmsterdam (Holland). There are also sev-eral other emerging initiatives and educa-tional programs around the globe (Table 3).
Given the pace of the field, it is probablytoo early to endorse one particular syllabusas the correct or best option. However,clearly all programs must provide a rigorousunderstanding of both biology and quanti-tative modeling. Thus, many require that allstudents, regardless of background, performhands-on research in both computer pro-gramming and in the wet laboratory.Required course work in biology typicallyincludes genetics, biochemistry, molecularand cell biology, with laboratory work asso-ciated with each of these. Course work inquantitative modeling might include proba-bility, statistics, information theory, numer-ical optimization, artificial intelligence andmachine learning, graph and network the-ory, and nonlinear dynamics. Of the biolog-ical course work, genetics is particularlyimportant, because the logic of genetics is,to a large degree, the logic of systems biol-ogy. Of the course work in quantitativemodeling, graph theory and machine learn-ing techniques are of particular interest,because systems approaches often reducecellular function to a search on a network of
biological components and interactions7,8.A course of study integrating life and quan-titative sciences helps students to appreciatethe practical constraints imposed by experi-mental biology and to effectively tailorresearch to the needs of the laboratory biol-ogist. At the same time, knowledge of themajor algorithmic techniques for analysis ofbiological systems will be crucial for makingsense of the data.
Other pathsAn alternative to pursuing a cross-discipli-nary program is to tackle one field initiallyand then learn another in graduate school.Examples would include choosing anundergraduate major in engineering andthen obtaining a PhD in molecular biology,or starting within biochemistry then pursu-ing course work in computer programming.This leads to a common question: whencontemplating a transition, is it better toswitch from quantitative sciences to biologyor vice versa?
Although some feel that it is easier tomove from engineering into biology, thehonest answer is that either trajectory canwork. Some practical advice is that if com-ing from biology, start by becoming familiarwith Unix, Perl and Java before diving intomore complex computational method-ologies. If coming from the quantitative sciences, jump into a wet laboratory as soonas possible—when shaky hands becomesteady, you’re well on your way.
The job marketWhat jobs are new systems biologists likelyto find? With the formation of myriad newacademic departments and centers, the aca-demic job market is booming. On the otherhand, biotech firms and ‘big pharma’ havebeen more cautious about getting involved9.However, most agree that in the long-term,systems approaches promise to influencedrug development in several areas: first, tar-get identification, in which drugs are devel-oped to target a specific molecule ormolecular interaction within a pathway;second, prediction of drug mechanism-of-action (MOA), in which a compound hasknown therapeutic effects but the molecular
NATURE BIOTECHNOLOGY VOLUME 22 NUMBER 4 APRIL 2004 473
Systems biology 101—what you needto knowTrey Ideker
Trey Ideker is at the Department ofBioengineering, University of California, SanDiego, La Jolla, CA 92093-0412, USA.e-mail: [email protected]
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mechanisms by which it achieves theseeffects are unclear; and third, prediction ofdrug toxicity and properties related toabsorption, distribution, metabolism andexcretion. In all of these cases, the key con-tribution of systems biology would be acomprehensive understanding blueprint ofcellular pathways used for identifying pro-teins at key pathway control points, or pro-teins for which the predicted perturbationphenotypes most closely resemble thoseobserved experimentally with a pharmaco-logic or toxic agent.
It is revealing that outside of biology andbiotech, many sectors of manufacturingalready depend heavily on computer simula-tion and modeling for product development.Using computer-aided design tools, digitalcircuit manufacturers explore the wiring oftransistors and other components on the sil-icon wafer, just as automotive engineers esti-mate how many miles per gallon to expectfrom the next-generation sedan long beforeit is built on the assembly line. Biology willundoubtedly also benefit from these ‘classi-cal’ engineering approaches. Given that
more than six out of every seven drugs thatundergo human testing ultimately fail due tounanticipated side effects, software simula-tions may act as a much needed filterbetween high-throughput screening for drugcandidates and the time-consuming andcostly follow-up of human trials.
Thus, the key question may not bewhether systems biology will be important
for the biotech industry, but how quickly itwill take hold9. To effect real changes, whatsystems biology needs most is a major ‘suc-cess story’ within industry—a well-publi-cized example of how systems biologyprinciples, experimentation and/or integra-tive modeling have led directly to selectionof a lead compound or in pushing a drug tomarket.
474 VOLUME 22 NUMBER 4 APRIL 2004 NATURE BIOTECHNOLOGY
Table 1 Selected programs offering systems biology courses
Institution URL
Asia
A*Star Bioinformatics Institute, Singapore http://www.bii.a-star.edu.sg/
University of Tokyo, Japan, Graduate School of Information Science and Technology http://www.i.u-tokyo.ac.jp/index-e.htm
Europe
Flanders and Ghent University, Belgium, Department of Plant Systems Biology http://www.psb.ugent.be/
Max Planck Institute of Molecular Genetics, Berlin, Germany http://lectures.molgen.mpg.de/
Max Planck Institute of Dynamics of Complex Systems, Madgeburg, Germany http://www.mpi-magdeburg.mpg.de/
University of Rostock, Germany, Systems Biology & Bioinformatics http://www.sbi.uni-rostock.de/
University of Stuttgart, Germany, Systems Biology Group http://www.sysbio.de/
North America
Cornell, Memorial Sloan-Kettering Hospital, and Rockefeller Universities, New York, http://www.cs.cornell.edu/grad/cbm/
Physiology,Biophysics & Systems Biology, Program in Computational Biology and Medicine
Harvard University, Cambridge, MA, Department of Systems Biology http:sysbio.med.harvard.edu/
Massachusetts Institute of Technology, Cambridge, MA, http://csbi.mit.edu/
Computational and Systems Biology Initiative
Princeton University, Princeton, NJ, Lewis-Sigler Institute for Integrative Genomics http://www.genomics.princeton.edu
Stanford University, Stanford, CA, Medical Informatics (SMI) and BioX http://smi-web.stanford.edu/
University of California, Berkeley, CA, Graduate Group in Computational & Genomic Biology http://cb.berkeley.edu/
University of California, San Diego, CA, Department of Bioengineering http://www-bioeng.ucsd.edu/
University of Toronto, Canada, Program in Proteomics and Bioinformatics http://www.utoronto.ca/medicalgenetics/
University of Washington, Seattle, WA, Department of Genome Sciences http://www.gs.washington.edu/
Virginia Polytechnic Institute and State University, Blacksburg, VA, http://www.grads.vt.edu/gbcb/phd_gbcb.htm
Program in Genetics,Bioinformatics and Computational Biology
Washington University, St. Louis, MO, Computational Biology Program http://www.ccb.wustl.edu/
Table 2 Selected short courses in systems biology
Institute/Program URL
Berlin Graduate Program, Dynamics & Evolution of http://www.biologie.hu-berlin.de/
Cellular and Macromolecular Processes
Biocentrum Amsterdam, http://www.science.uva.nl/biocentrum/
Molecular Systems Biology Course
Cold Spring Harbor Laboratory, http://meetings.cshl.org/
Course in Computational Genomics
Institute of Systems Biology, Introduction to http://www.systemsbiology.org/
Systems Biology
University of Oxford, UK, Biology & Proteomics http://www.conted.ox.ac.uk/cpd/biosciences/
Informatics courses; Genomics, Proteomics & Beyond courses/short_courses/Genome_Analysis.asp
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Already, numerous biotechnology start-ups such as Genstruct, Genomatica, BeyondGenomics, Ingenuity, Gene NetworkSciences, Entelos, Bioseek and GeneGO arehard at work on developing just such ‘proof-of-principles.’ As for big pharma, systemsconcepts are influencing many companiesto evolve their drug development process,but it is unclear whether what evolves will atall resemble what is currently called ‘systemsbiology’.
A cautionary noteThe field of systems biology still includesmany challenges and holds much promise,especially for new cross-disciplinary scien-tists entering the field. Of course, althoughany number of educational options canplace researchers in a potentially powerfuland sought-after position in the field, stu-dents should beware of the universal curseof systems biology: as you quickly attain abreadth of knowledge in biology and math-ematics, you risk losing, or fail to attain,
depth in either. Jack of all trades, or masterof one? The choice is yours.
ACKNOWLEDGMENTSThe author would like to thank Eric Neumann,Adam Feist, Benno Schwikowski, Bernhard Palssonand Kristyn Ideker for valuable discussions andmaterial for this commentary. Funding wasgenerously provided by National Institutes of Healthgrant 1-P41RR018627-01.
1. Ideker, T., Galitski, T. & Hood, L. A new approach todecoding life: Systems Biology. Annu. Rev. GenomicsHum. Genet. 2, 343–372 (2001).
2. Kitano, H. Computational systems biology. Nature 420,206–210 (2002).
3. Bertalanffy, L.v. General systems theory: foundations,development, applications. (George Braziller, New York,1969).
4. Zhu, H. & Snyder, M. “Omic” approaches for unravelingsignaling networks. Curr. Opin. Cell Biol. 14, 173–179(2002).
5. Zerhouni, E. Medicine. The NIH Roadmap. Science 302,63–72 (2003).
6. UK Biotechnology and Biological Sciences ResearchCouncil. World Class Science. Strategic Plan2003–2008. (BBSRC, Swindon, UK, 2003).
7. Ideker, T. & Lauffenburger, D.A. Building with a scaffold:emerging strategies for high- to low-level cellular model-ing. Trends in Biotechnol. 21, 255–262 (2003).
8. Friedman, N. Inferring cellular networks using probabilis-tic graphical models. Science 303, 799–805 (2004).
9. Cohen, H. Systems biology: a pale beacon for biotechs.The Scientist 17, 52 (2003).
NATURE BIOTECHNOLOGY VOLUME 22 NUMBER 4 APRIL 2004 475
Table 3 Some emerging initiatives and educational programs in systems biology
German Systems Biology Research Program http://www.systembiologie.de/
Manchester Interdisciplinary Biocenter, http://www.mib.umist.ac.uk/
Manchester, UK
University of Texas Southwestern, Dallas, TX, http://www.utsouthwestern.edu/utsw/home/
Program in Molecular, Computational & Systems education/integrativebiology/
Biology, Integrative Biology Graduate Program
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