Essay

Bioinformatics and the Undergraduate CurriculumMark Maloney,* Jeffrey Parker,† Mark LeBlanc,‡ Craig T. Woodard,§

Mary Glackin,� and Michael Hanrahan**

*Department of Biology, Spelman College, Atlanta, GA 30314-4399; †Department of Computer Science,Merrimack College, North Andover, MA 01845; ‡Department of Computer Science, Wheaton College, Norton,MA 02766; §Department of Biological Sciences, Mount Holyoke College, South Hadley, MA 01075; ¶Library,Information & Technology Services, Mount Holyoke College, South Hadley, MA 01075; �Information andLibrary Services, Bates College, Lewiston, ME 04240

Submitted March 16, 2010; Revised June 17, 2010; Accepted June 20, 2010Monitoring Editor: John Jungck

Recent advances involving high-throughput techniques for data generation and analysishave made familiarity with basic bioinformatics concepts and programs a necessity in thebiological sciences. Undergraduate students increasingly need training in methods related tofinding and retrieving information stored in vast databases. The rapid rise of bioinformaticsas a new discipline has challenged many colleges and universities to keep current withtheir curricula, often in the face of static or dwindling resources. On the plus side, manybioinformatics modules and related databases and software programs are free and accessibleonline, and interdisciplinary partnerships between existing faculty members and their sup-port staff have proved advantageous in such efforts. We present examples of strategies andmethods that have been successfully used to incorporate bioinformatics content into under-graduate curricula.

INTRODUCTION

In recent years, great progress has been made in our abilityto sequence entire genomes of a variety of organisms andunderstand how cells access and use the information storedin DNA. Mathematics and the languages of computer sci-ence can be used to describe changes in the DNA-relatedcodes of biology. Scientists can use the many programsdeveloped with applied computer science and mathematicsto access DNA, RNA, and protein sequence data as well asother biologically relevant information generated by biolo-gists and stored in databases.

Operations to compare genes or gene products by matchingnucleotide or related sequences use a variety of bioinformatics

algorithms and computer software. Clearly, a working under-standing of bioinformatics requires a synthesis of principlesfrom biology and computer science as well as applied mathe-matics and chemistry. Due to recent technological advances,data accumulation is currently far outpacing analysis. Thereare many sequences and even complete genomes beingentered into databases that require annotation. These canbe used as sources of data for research as well as for classprojects. In addition to their usefulness as teaching tools,some important research will undoubtedly emerge fromsuch projects. Students need a robust introduction tobioinformatics tools and a solid understanding of relatedprinciples and technologies. Circumstances are favorablefor computer scientists to participate in and supportbioinformatics programs (LeBlanc and Dyer, 2004), andmany interdisciplinary programs have been established atthe undergraduate and graduate levels (Goode and Traj-kovski, 2007; Hemminger et al., 2005). For now, the fruit isstill low because the possibilities for interdisciplinary col-laboration are far from exhausted, the ever-increasingstore of information is largely held in databases withpublic access, and many software programs are freelyavailable that can be used to access and analyze the data.Valuable research can be performed on a computer (in

DOI: 10.1187/cbe.10–03–0038Address correspondence to: Mark Maloney (mmaloney@spelman.edu).

© 2010 M. Maloney et al. CBE—Life Sciences Education © 2010 TheAmerican Society for Cell Biology. This article is distributed byThe American Society for Cell Biology under license from theauthor(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative CommonsLicense (http://creativecommons.org/licenses/by-nc-sa/3.0).

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http://www.lifescied.org/content/suppl/2010/08/17/9.3.172.DC1.htmlSupplemental Material can be found at:

silico) with no further investment in equipment or labo-ratory supplies.

BRINGING BIOINFORMATICS INTO THECLASSROOM

No science curriculum can remain current without a bioin-formatics component. Projects such as the sequencing of thehuman genome have changed the nature of instruction. Amodern biology course must address new techniques ingene mapping. Students need to understand what bioinfor-matics-related computer software programs do and howthey do it. How do programs align nucleic acid sequences orgenerate structural models? To evaluate the results obtainedusing standard bioinformatics tools such as Basic LocalAlignment Search Tool (BLAST), students must understandthe strengths and limitations of the programs and data. Thisis basic knowledge for today’s biologist.

At the undergraduate level, a solid introduction to a com-puter programming language is very important. Althoughmany of the bioinformatics exercises available use the com-puter language Perl, many computer scientists have prefer-ences for other languages. Computer science enrollment isdeclining just as bioinformatics has made the need for com-puter programming experience in biology undeniable. Thesetrends give computer science faculty a strong incentive toinvest in learning relevant biological concepts and collabo-rate with biology faculty. Computer science graduates witha basic knowledge of biological principles will be especiallyin demand, as will biologists with a computer science back-ground.

In addition to the necessary participation of biologists andcomputer scientists, faculty from other disciplines also playa vital role in bioinformatics instruction. Mathematiciansprovide instruction in applied statistics and algorithm de-velopment, and biochemists and chemists provide instruc-tion in molecular modeling, proteomics, and metabolomics.

Biologists will continue to use so-called wet labs to givestudents a chance to experience experimental techniquesinvolving organisms, tissues, and cellular components firsthand. But in silico dry labs involving bioinformatics tech-niques and virtual lab exercises can be very effective, espe-cially in genetics, cell biology, and molecular biology. Re-lease time for existing faculty to gain workshop or shortcourse experience may be necessary for related curriculumdevelopment purposes. Many excellent workshops andshort courses are available from various institutions andorganizations. In addition to the National Institute for Tech-nology in Liberal Education-funded workshops, these in-clude the National Science Foundation (NSF) funded Bio-quest/BEDROCK project, the Teagle-funded Teaching BigScience at Small Colleges: a Genomics Collaboration, theNSF- and Howard Hughes Medical Institute-funded projectThe Genome Consortium for Active Teaching, and the work-shops offered by the National Center for Biotechnology In-formation (NCBI).

Mount Holyoke College (MHC) and Bates College ob-tained a National Institute for Technology in Liberal Educa-tion grant (www.nitle.org) to support collaboration for cur-ricular planning among small liberal arts colleges. Thesebioinformatics retreats convened 46 participants in teams of

biologists, mathematicians, and computer scientists as wellas faculty from related disciplines, instructional technolo-gists, and librarians from 18 colleges. Topics included novelways to initiate and foster interdisciplinary dialogue be-tween Science, Technology, Engineering, and Mathematicsdepartments; to use advances in bioinformatics to enhancecurricular and research opportunities for faculty and under-graduate students; and to engage technical support staff andadministrators in these endeavors. Participants discussedways to use bioinformatics to excite millennial generationstudents who are very comfortable with the use of comput-ers but whose learning styles often are not well suited toa traditional lecture-based format. We concluded thathands-on computer exercises using software freely availableon the Web would engage students in using bioinformaticstools. See sample exercises developed and tested by partic-ipants in the Supplemental Material. These workshops haveinspired innovative interdisciplinary instructional and re-search-oriented projects. Some examples follow.

At MHC, faculty from biology, biochemistry, computerscience, and mathematics and staff from information tech-nology (IT) explored strategies for bringing bioinformaticsinto the curriculum. The group decided to start by integrat-ing bioinformatics and cheminformatics tools throughoutthe existing curriculum, from introductory-level biologythrough advanced courses. They plan to add Bioinformaticsand Proteomics courses as appropriate. MHC hosted anNCBI training workshop on searching tools and participatedin 2 yr of summer workshops to share curricula and strate-gies. MHC faculty have introduced NCBI tools, includingBLAST and Cn3D, into their Introductory Genetics and Mo-lecular Biology courses. They use the Protein Data Bank andvisualization tools in Genetics, Molecular Biology, and CellBiology courses and have developed a new ComputationalChemistry course.

The Department of Biology at Spelman College has under-taken a major revision of its undergraduate curriculum(Maloney et al., 2007). The first Bioinformatics course was of-fered as an elective in 2004 with assistance from guest lecturersfunded through a science seminar series. Basic bioinformaticscontent is now incorporated into the required four-course in-troductory biology sequence with curriculum developmentsupport from the Advancing Spelman’s Participation in Infor-matics Research and Education (www.spelman.edu/academics/research/aspire/index.shtml) program funded by HistoricallyBlack Colleges and Universities Undergraduate Program.Modules currently in use or under development use softwareavailable online at the NCBI or the San Diego Super ComputerCenter’s Biology Workbench sites and include protein model-ing using Cn3D, sequence similarity searches using variousBLAST programs, ORF Finder, CLUSTALW for multiple se-quence comparisons, and Phylip for researching evolutionaryrelationships and generating dendrograms.

Advanced genomics, proteomics, and related bioinformat-ics topics are now offered in upper-level electives enhancedby recent collaborative efforts and new hires in biology andcomputer science. The faculty has experimented with teach-ing computing skills to Spelman students by using the open-source R-language for statistical computing. In addition, arevised version of the Introductory Computer Science courseis being developed that will involve enhanced training witha programming language and various examples of compu-

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tational software applications that form the basis of infor-matics in the new millennium.

Since 1998, Wheaton College (Norton, MA) has activelyengaged with various modes of interdisciplinary teaching.In fact, collaborative pedagogy in the new curriculum iscentered on connections, or pairs of linked courses thatconnect significantly different disciplines (LeBlanc et al.,2010). In short, the faculty voted to teach together in variouscombinations. This provides an exciting way to explore dif-ferent areas of knowledge and different approaches to prob-lems. With NSF funding, Wheaton faculty have developed,tested, and disseminated course materials for linkingcourses in biology and computer science, such as biology’sGenetics with Computer Science’s Algorithm course. Othercurricula changes include a new bioinformatics major and ateam-taught course called DNA, an elective for both thebiology and computer science majors in which studentslearn to program and design experiments to data mine entiregenomes. Bioinformatics courses in biology and computerscience also may be connected with Philosophy’s Ethicscourse. In both the ethics and computing courses, particularattention is paid to the increasing use and challenges ofsequenced genomes as applied to personalized medicine.

WORKSHOP RECOMMENDATIONS

Multiple teaching models are available for bioinformatics-related courses and diversity is encouraged. No one modelfits all curriculum and personnel situations. We see threedistinct models in the spectrum of teaching opportunities:

1. Infusion of bioinformatics content into existing courses2. Linking of Biology and Computer Science courses (or

Bio-Math, Chem-CS, etc.) by sharing lab exercises or in-terdisciplinary final projects

3. Team-teaching of Bioinformatics involving instructorsfrom multiple departments

Also see Supplemental Material and http://genomics.wheatoncollege.edu for examples of course materials.

Alternatively, targeting candidates with bioinformaticsexperience when hiring new faculty may be possible inbiology, computer science, chemistry, mathematics, or re-lated searches. Such coordination of hiring above the depart-ment level in order to assemble appropriate interdiscipli-nary teams is not typical practice and may require noveladministrative initiatives.

Institutions may not need to implement new majors orminors in bioinformatics. The majority of schools can be wellserved by introducing the concepts and technologies intoexisting majors. However, teaching across disciplines is of-ten difficult to coordinate and administer, and innovationsin team teaching must be properly valued and evaluated.Faculty members need administrative encouragement andsupport to experiment with such courses. Junior facultyinvolved in interdisciplinary efforts are often concerned thattheir efforts will not be valued as much as instruction within

their department. Representatives of both the administrationand faculty governance, including those involved in tenureand promotion decisions, should move to allay these fears.These members of the shared governance structure shouldmake it clear that such efforts to keep current in increasinglyinterdisciplinary practices in higher education will be val-ued and rewarded.

Use the computer savvy and technical inclinations of themillennial generation of students to advantage in recruitingstudents for classes featuring hands-on software programexperiences in bioinformatics. The most capable studentsthen can serve as the next wave of teaching assistants.

Support for bioinformatics, or informatics in general, goesbeyond the need for informed classroom instructors. IT,library science, and laboratory support staff may need towork together to assemble a bioinformatics computer lab ina manner that is novel to the institution. Such critical tech-nology support may require new duties for existing person-nel or new staff hires.

Use of external expertise is often desirable, if not neces-sary, and may come in different forms and through differentvenues. Visiting scientists from established bioinformaticsprograms at either teaching or research-intensive institu-tions are especially helpful. The duration and form of exper-tise sharing is dependent on time and budgetary consider-ations. For institutions with divisional or departmentalseminar series, now may be the optimal time to choosebioinformatics as the series theme. Speakers can performdouble duties as guest lecturers in nascent Bioinformaticscourses or in related Genetics, Cell and Molecular Biology,or Biochemistry courses. The large-scale application of com-puter science-based technology to biological problems is anexciting new development in science. The need to introducebioinformatics to the undergraduate curriculum is irrefut-able. Done properly, this will excite the new generation ofstudents as well as prepare them for their future careers.

REFERENCES

Goode, E., and Trajkovski, G. (2007). Developing a truly interdisci-plinary bioinformatics track: work in progress, J. Comput. Sci. Coll.22, 73–79.

Hemminger, B., Losi, T., and Bauers, A. (2005). Survey of bioinfor-matics programs in the United States. J. Am. Soc Inf. Sci. Technol.56, 529–537.

LeBlanc, M. D., and Dyer, B. D. (2004). Bioinformatics and comput-ing curricula 2001—why computer science is well positioned in apost-genomic world. ACM SIGCSE Bull. 36, 64–67.

LeBlanc, M. D., Gousie, M. and Armstrong, T. (2010). Connectingacross campus. In: Proceedings of the 41st SIGCSE Technical Sym-posium on Computer Science Education, 10–13 March 2010, Mil-waukee. WI. ACM Special, Interest group on Computer ScenceEducation. www.sigcse.org/sigcse2010 (accessed 16 July 2010).

Maloney, M., Imumorin, I., and Bauerle, C. (2007) Teaching millen-nial science students in the (bio)informatics age. Network: A Journalof Faculty Development. www.nyu.edu/frn/publications/millennial.student/Bioinformatic.html (accessed 16 July 2010).

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