EUE Proposal FY2015 Department Campus Box School/College · Project ID# 15_008 Project Title Towards an Interdisciplinary Bioinformatics Curriculum Project Director ID Number Telephone

EUE Proposal FY2015

Project ID# 15_008 Project Title Towards an Interdisciplinary Bioinformatics Curriculum Project Director ID Number Telephone Email Gunes Ercal 3348 [email protected] Department Campus Box School/College Computer Science 1656 Engineering Course or Program CS 490 Bioinformatics and BIOL 490 Bioinformatics Project Co-Director ID Department Email

Darron Luesse Biological Sciences [email protected] Multiple Submission Priority: 1 Summary: There is an ever-increasing demand for expertise in bioinformatics, an interdisciplinary field crossing biology and computer science that deals with computational methods for efficient storage and analysis of biological data. The number of universities incorporating bioinformatics at various levels into their undergraduate biology or computer science curricula is growing. From the computer science perspective, bioinformatics presents an excellent domain in which to apply algorithmic knowledge, requiring a deep algorithmic understanding to truly tackle the scale of the problems involved. More importantly, the interdisciplinary nature of bioinformatics lends itself to thinking broadly and fundamentally as a scientist rather than as a biologist or a computer scientist in particular. The relevance of the field is amplified in the greater St. Louis region, where major biological research facilities are present. Both Biology and Computer Science departments have an expressed long-term interest in jointly incorporating Bioinformatics into their undergraduate curricula by way of a specialization. An appropriately synchronized two-course offering from Biology and Computer Science, respectively, is an important first step in this regard, by establishing a real rapport between both students and faculty of both departments. One hoped-for long-term byproduct of a bioinformatics curriculum involving such cross-disciplinary course-pairings supported by studies is an increase in female recruitment and retention in Computer Science. EUE funding is requested to support the collaborative development of two interdisciplinary bioinformatics courses to be offered in Spring

2015 and numbered as CS 490 Topics in Computer Science and BIOL 490 Topics in Biology. While each will be taught at the appropriate level for senior/graduate students in their respective disciplines, the execution of the courses will feature lectures from both faculty and interdisciplinary group work on synchronized projects with students from both courses. In addition, funds are requested to support experiential learning in the form of two field trips to biological research facilities in St. Louis. This proposal is well aligned with EUE goals due to the innovative project-based paired-course pedagogical model applicable to interdisciplinary technical subjects in addition to the emphases on female recruitment into Computer Science and experiential learning via projects and field trips. Project Budget Salary Wages Travel Equip. Comm CServ Auto Tele Awards Total 14399 0 2400 0 0 0 0 0 0 16799 Cost-Sharing Salary Wages Travel Equip. Comm CServ Auto Tele Awards Total 0 0 0 0 0 0 0 0 0 0

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Towards an Interdisciplinary Bioinformatics Curriculum

Gunes Ercal and Darron Luesse

Current Situation

Maloney et al. [5] stress the necessity and importance of incorporating bioinformatics into

undergraduate education, going so far as to state, “No science curriculum can remain current without a

bioinformatics component.” Presently, SIUE’s Biology curriculum is lacking in a dedicated

bioinformatics course. The continuation of this situation would be especially problematic for students

whose interests lie in cell biology and genetics (n~20-30 per year) for whom familiarity with

bioinformatics tools and methods is increasingly crucial. Currently the Computer Science department is

moving to address a similar need: For the first time in more than five years, a CS 490 Special Topics:

Bioinformatics course is being taught (Spring 2014, by PD Gunes Ercal), focusing on the analysis of

algorithms to solve cleanly represented genomics problems. Despite deepening students’ algorithmic

understanding in an important application area, its setup is sub-optimal for a sustainable bioinformatics

course: Discussions and examination of the textbook [3] with relevant biology faculty indicate that the

language and focus of the current course setup are not amenable to establishing genuine dialogue

between computer science and biology. However, amongst our over 200 Computer Science majors, most

of whom seek technical employment in greater St. Louis, home to Monsanto, Sigma Aldrich, WUSTL

Genome Institute, and the Danforth Center, at least 15-20 undergraduates per year may greatly benefit

from a Bioinformatics curricular component in which they speak a common language with biologists.

One cannot expect students to speak a common language across disciplines if their respective

professors do not, and indeed the most successful bioinformatics courses and curricula are those that are

genuinely collaborative and cross-disciplinary [5]. Whereas preparation for the current CS 490 course was

done prior to an existing rapport between the Computer Science and Biology departments, now there is a

mutually expressed interest for an interdisciplinary bioinformatics curriculum from both departments

and their chairs. This proposal is designed as a first step in that direction towards which both PDs Darron

Luesse and Gunes Ercal as well as their respective chairs are committed to continue (see support letters).

Towards an Interdisciplinary Bioinformatics Curriculum – Ercal & Luesse

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Proposed Project

Bioinformatics analyses are becoming an increasingly common requirement for execution of

biological research. Current bioinformatics tools allow users to compare unknown DNA or protein

sequence to the vast databases of sequenced genes and genomes. Others align overlapping regions of

millions of short DNA sequences to reconstruct entire chromosomes, or allow researchers to identify

predicted functional areas within a protein. Recent technological advances in DNA sequencing have led

to an explosion of large data sets that require computers for analysis. The accessibility of this technology

has rapidly increased the demand in academia and industry for individuals that can effectively apply

computational methods to advanced biological questions. However, the disparate nature of these skill

sets means that very few graduates fit this description.

There are a wide variety of ways in which bioinformatics can be taught. Some such as [2] are

biology-centric and mostly unintelligible to computer scientists, whereas others such as [1] and [3] are

computer science focused and effectively unintelligible to biologists. Computer Science and Biology are

both technical, vocabulary-intensive disciplines that share little overlap. It is clear that a real collaboration

between Biology and Computer Science is necessary for a truly effective course, and jointly-taught

courses have been particularly successful [5].

We propose collaboratively designing two Bioinformatics courses, one in Biology and the other in

Computer Science, both for Spring 2015. The courses will be synchronized with each other, in particular

regarding the topics and schedule of bioinformatics projects and problems presented. PD Gunes Ercal

will teach the Computer Science offering while PD Darron Luesse will teach the Biology offering, with

frequent guest-lecturing in the other’s class. Classes will be scheduled back to back, hopefully in the same

room, to encourage (but not require) student attendance at both. The text Exploring Bioinformatics: A

Project-Based Approach [6] appears to be a good guide and reference for structuring overlapping

Bioinformatics classes in which students tackle common biologically motivated problems as assigned

projects. With this framework in place, each course can address the topic concurrently, involving guest

lectures from the other instructor. At the end of each of twelve sections, students will complete hands-on


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projects to reinforce the lecture material. One innovative aspect of this proposed joint offering is that

students from both classes will be placed in interdisciplinary groups to complete different yet

complementary aspects of each project.

Another experiential learning component of our project wherein rich cross-disciplinary

interaction will occur is the two fields trips to industrial and academic biological research facilities in the

St. Louis area: Monsanto and the WUSTL Genome Institute, respectively (although Sigma Aldrich and

the Danforth Center are alternatives). These organizations employ a large mix of computer scientists and

biological scientists working together on major biological problems, allowing visitors to experience such

collaboration first-hand. Much can be done with two field trips to show the different aspects of

bioinformatics work: industrial versus academic, agricultural versus medical, biological versus

computational, etc.. Depending on the results of these trips as well as the results of this project in helping

to start an interdisciplinary bioinformatics track, we hope to continue to include this aspect as a

sustainable ingredient of future offerings outside the EUE period. This will be through student-provided

transportation, departmental support, or fees (if the specialization occurs).

Alignment of Objectives with EUE Goals:

There are two levels of objectives that this project entails: the course-specific learning objectives

and the more broadly applicable pedagogical objectives. We invite the interested reader to view the

Appendix on Course Logistics for course-specific learning objectives and further details on

implementation of the courses. Here, we address the pedagogical objectives of our proposal and clarify

the alignment of our proposal with the following EUE goals and 2015 special foci: (a) supporting

retention, (b) innovative pedagogies applicable to a wide-range of disciplines, and (c) experiential

learning strategies and activities. The pedagogical objectives of this project are primarily as follows:

1. Examining the characteristics of learning in a paired, cross disciplinary teaching model for

Computer Science and Biology

2. Exploring a project-based approach to teaching in a pair of cross-disciplinary courses

3. Determining the efficacy of using field trips to deepen the impact of course content and projects


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Prior to considering the three objectives separately, we stress that all objectives of this project,

pedagogical or otherwise, are directed towards building a foundation for an interdisciplinary

specialization or track in bioinformatics within both the Computer Science and Biology departments.

This project is designed to maximize both the faculty and the student experience in bioinformatics,

subject to the constraints that none of the current students have cross-disciplinary background, and that

the current state of bioinformatics understanding by the PDs is restricted to aspects in their own area,

again lacking the deeper cross-disciplinary component, at least partly due to the previous lack of

communication between their respective departments (this proposal is also a first step in that direction).

We believe that, given the current situation, the most effective next-step can occur by designing a pair of

upper-level paired and synchronized Bioinformatics courses in Biology and Computer Science involving

frequent guest lecturing (objective (1)), and strongly emphasizing experiential learning (special focus (c))

via projects involving mixed student groups (objective (2)), as well as field-trips in which the real-world

fruit of such cross-disciplinary interaction can be witnessed (objective (3)). The design is necessarily

innovative (special focus (b)) due to the lack of an appropriate existing model for what it is we are

attempting to accomplish. We detail this issue next.

We have considered and compared against other possible designs, including the Interdisciplinary

Studies model, which is the primary cross-disciplinary model at SIUE. Unfortunately, we do not feel that

the existing IS model is suitable for a serious step towards an interdisciplinary bioinformatics track for a

number of reasons, the primary reason being a more general and inherent problem associated with a

single jointly-taught course: The major concern leading to the preference of a paired, collaborative course

offering rather than a single course in Bioinformatics is the difficulty in maintaining a sufficient level of

challenge for both sets of students without losing either group. Currently, very few biology and computer

science students take classes within the other discipline, and they certainly do not take enough classes to

prepare them for 400-level lecture material. A reasonable pre-requisite for a Computer Science offering of

a Bioinformatics course is the third required programming course of the major, in which relevant data

structures and algorithms are introduced, namely CS 240 Introduction to Computing III, though the


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fourth course CS 340 Data Structures & Algorithms would be preferred. Similarly, from the Biology

perspective, an appropriate understanding of the biological relevance of bioinformatics applications

would require Introductory Biology I and II (BIOL150,151), followed by Genetics (BIOL 220) and Cell &

Molecular Biology (BIOL 319). Our approach allows for an interdisciplinary environment, but avoids the

problem of presenting lectures to students with vastly different course backgrounds, or eliminating

students with onerous prerequisite courses. While the IS model may work well for other situations,

including introductory courses, courses in which at least one subject area is non-technical, or courses in

two subjects sharing a greater traditional overlap, a different model is needed in this situation.

Furthermore, on the subject of why we have preferred a paired, synchronized offering over a

single joint course, we note that there exist successful models of paired interdisciplinary course offerings

between Computer Science and other fields, including Biology, documented in [4], in which the related-

yet-complementary nature of the pairings appears beneficial both to student understanding and

Computer Science recruitment (special focus (a)). Although that study concerns introductory courses at a

small liberal arts colleges in which recruitment into Computer Science is more of a problem than at SIUE,

it was very interesting to see that the interdisciplinary course pairing appeared to help recruit women

into computer science (and help keep them there). Even as undergraduate enrollment and graduation in

computer science has been increasing both nationwide and at SIUE, the percentage of undergraduate

women graduating in the field remains at a dismal 13% nationally [7] and no more than 15% at SIUE.

Given the far greater representation of women in the Biological Sciences, we expect that increasing their

exposure to Computer Science in a way that fundamentally relates to their original field will increase

women’s interest in Computer Science overall, and hopefully also result in the long-term enrollment and

retention increases of women in Computer Science as previously documented elsewhere [4]. Particularly

if this project becomes an effective means by which to start an interdisciplinary bioinformatics track, we

believe that the retention of women in CS will undoubtedly exhibit a long term increase (special focus (a)).

Finally, we note that, even compared to such interdisciplinary paired course models involving

Biology and CS, our emphasis on experiential learning via synchronized projects involving interactions of


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interdisciplinary student groups in addition to visitations to biological research centers makes this project

unique, not only at SIUE but also elsewhere, as far as we are aware. We believe that the innovative

pedagogy involved in the design objective (1), (2), and (3) will be applicable to other upper level

interdisciplinary curricula involving traditionally disparate technical subjects.

Evaluation and Dissemination

Similarly to the objectives, assessment takes two forms as well: subject-specific assessment of

learning, and the overall evaluation of the effectiveness of the interdisciplinary model captured via the

pedagogical objectives. We will assess student learning outcomes via surveys, student evaluation

comments, student performance on projects and exams, and pre-and-post tests to determine knowledge

gains in bioinformatics. For CS students, the instrument will be administered to exiting students enrolled

in the current CS 490 Bioinformatics offering as well as at the beginning and end of the joint course in

Spring 2015. Comparison between current students and Spring ’15 students will determine if

interdisciplinary interactions with faculty and students improve the outcomes. For BIOL students, the

instrument will contain course objective-specific questions, and will be administered on the first day of

class, as well as the end of class. Survey questions will be designed in a way to assess the student

opinions on the effectiveness of the pairing of the courses (objective (1)), projects (objective (2), and field

trips (objective (3)) to enhance their learning and interdisciplinary experience.

But to truly assess the cross-disciplinary effectiveness of the model, a cross-evaluation must also

be conducted: PD Luesse and his BIOL class will qualitatively evaluate PD Ercal and her CS class, and

vice versa, with respect to the ability to communicate bioinformatics problems and solutions, which

require constant translations between a biological language into a computer science language and back.

We believe that the paired aspect of this project lends itself well to such semi-external evaluations, which

are particularly needed for interdisciplinary settings. Finally, another important measure of

interdisciplinary success with regards to the experiential learning objectives will be captured via

performance on the projects, which will involve mixed student groups, particularly requiring the mixing

towards the latter half of the term.


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References

[1] Bockenhauer, H., & Bongartz, D. Algorithmic Aspects of Bioinformatics. Springer-Verlag, 2007.

[2] Higgs, P.G., & Attwood, T.K. Bioinformatics and Molecular Evolution. Blackwell Publishing, 2005.

[3] Jones, N.C., & Pevzner, P.A. (August 2004). An Introduction to Bioinformatics Algorithms. MIT Press,

August 6, 2004.

[4] LeBlanc, M.D., Gousie, M. & Armstrong, T. “Connecting Across Campus.” Proceedings of the 41st

SIGCSE Technical Symposium on Computer Science Education, Milwaukee, WI, March 2010.

[5] Maloney, M., Parker, J., LeBlanc, M.D., Woodard, C.T., Glackin, M., & Hanrahan, M.

“Bioinformatics and the Undergraduate Curriculum.” CBE Life Sci Educ: 172-174, 2010.

[6] St. Clair, C., & Visick, J.E. Exploring Bioinformatics: A Project-Based Approach (Second Edition). Jones

& Bartlett Learning, 2015.

[7] Zweben, S. “Computing Degree and Enrollment Trends From the 2011-2012 Taulbee Survey: PhD

Production in Computer Science Rises to Highest Level Ever While Undergraduate Enrollment Grows for

Fifth Straight Year.” Computing Research Association.

http://cra.org/uploads/documents/resources/taulbee/CRA_Taulbee_CS_Degrees_and_Enrollment_20

11-12.pdf


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Budget and Justification

Total Itemization Note

Salaries

$14,399

$8,150 for PD Gunes Ercal For two courses and based on

monthly salaries of PDs in

accordance with EUE limit $6,249 for PD Darron Luesse

Travel

$2,400

$1,200 = 2 x $600 for bus costs For two field trips with 40-60

students travelling by bus and

including snacks/meal $1,200 = 2 x 60 x $10 for snacks

Total: $16,799

Each of the PDs is requesting one month of summer support for curriculum development in two courses,

in alignment with the EUE per course limit. Additionally, support is requested for implementing two

combined class field trips to biological research facilities in the St. Louis area. The salary portion of the

requested funds total to $14,399 which is due to $8,150 for PD Gunes Ercal based on her monthly salary

and $6,249 for PD Darron Luesse. While both PDs believe that course development is part of a normal

faculty load, the logistics of this interdisciplinary approach to bioinformatics will require considerable

coordination between the faculty as well as intense preparation to learn material outside of each faculty

member’s normal discipline. Even in the current format, the programming skills required of the BIOL

faculty and the Biology knowledge required of the CS faculty will demand more effort than standard new

course preparations. In addition, the summer weeks will be used to analyze the assessment results from

the current CS 490 course to better inform syllabus choices. Furthermore, we believe that this project must

be viewed not only as the sum of two separate courses but as the first major step in an interdisciplinary

effort to initiate a bioinformatics curriculum, which is the true intent.


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The field trips will greatly enhance the student experience by allowing them to see first-hand the

real-world fruit of such scientific collaborations on a much larger scale. Budgeting for the field trips

includes bus travel and student lunch/snacks. Unfortunately, the buses available to rent from SIUE hold

maximum of 16 passengers, whereas we need to plan on accommodating 40 to 60 passengers (including

both student groups, as these will be joint trips). The estimate of the bus cost of $600 per trip is based on

both a quote given by Vandalia bus lines for $575 for the first four hours and $85/hour after that, as well

as other online searches that indicated $2 per passenger per hour as a minimum expected cost. Also

assuming about $10 per student lunch/snack, an additional $600 per trip is requested. Totaling for both

trips, the field trip portion of our budget request becomes $2,400. The total budget becomes $16,799.

Biographical Sketch Gunes Ercal received her B.S. degrees in both Mathematics and Computer Science from the University of Southern California (2001), and her Ph.D. in Computer Science from UCLA (2008). She is an Assistant Professor of Computer Science at SIUE since 2012. She has previously held tenure-track positions at the University of Kansas (KU, 2008-2010) and Istanbul Kultur University (IKU, 2011-2012), as well as other visiting positions. Her primary research area of network analysis is applicable to a broad range of networks, including biological networks. Much of her work has involved both her graduate (one from SIUE and 3 from KU) and undergraduate (3 from SIUE) advisees and has resulted in peer-reviewed publications in journals and conference proceedings in diverse areas including theoretical computer science, economics, psychology, and sensor networks. Two of her 5 journal articles are co-authored with students, and 4 of her 11 conference proceedings are co-authored with students (2 at SIUE). She has submitted 5 NSF proposals, none of which have been funded. Amongst her two internal grant proposals (GRF proposal at KU and STEP at SIUE) she was awarded the GRF grant. She shared her scientific passion with Upward Bound Math and Science high school students last year by conducting a äóìGraph Theory and Networks Workshopäóù for their residential summer program at SIUE. Her teaching at SIUE includes the courses CS 456 Advanced Algorithms, CS 340 Data Structures and Algorithms, CS 490 Computational Geometry, and most recently CS 490 Bioinformatics. She has also previously taught Data Structures, Abstract Machines and Languages, and Network Theory and Science at IKU, as well as Analysis of Algorithms, Network Security, and Discrete Structures at KU. As faculty advisor for SIUEäó»s Society of Women Engineers, she hopes that an interdisciplinary bioinformatics program will help to retain more women in Computer Science. Darron Luesse received his B.S. in Biology from the University of Missouri (1999) and his Ph.D. from Indiana University (2006). After a post doc at Ohio University, he has been an associate professor in the Department of Biological Sciences since 2008. He teaches Cell and Molecular Biology (BIOL 319), Introductory Biology I (BIOL 150), Plant Physiology (BIOL 472), Biochemistry and Molecular Biology of Plants (BIOL 490), Recombinant DNA Technology (BIOL 418a), Graduate seminars on Eukaryotic Cell Signaling and Plant/Environment Interactions (BIOL 595) and Biology for non-majors (BIOL 111). His research focus is the molecular signaling underlying plant/environment interactions, with an emphasis on gravitropism. In his 5.5 years at SIUE, Dr. Luesse has mentored 41 undergraduate students (25 women and 6 minorities) and 6 Masteräó»s students through individual research projects. Of these, 36 have presented 49 first-author research posters at national or regional conferences. In addition he has published three peer-reviewed manuscripts, two with SIUE undergraduate co-authors. He has also presented a talk entitled äóìWhat Plants are Doing When Youäó»re Not Lookingäóù to the freshmen science class at the SIUE East St. Louis Charter High School. He has received two SIUE internal grants (SRF, 2009 and New Directions, 2011). In addition, Dr. Luesse has submitted 11 external research proposals to the NSF, NASA, the U.S. Airforce, and The American Society of Plant Biologists, requesting $1,418,882 in funding. Seven of these have been declined, two have been funded, and two are in review. Currently he and his students are working on a NASA-funded project titled äóìProteomics analysis of Arabidopsis seedlings in microgravity.äóù Much of his work features a strong bioinformatics component. In addition to his research, he has incorporated bioinformatic projects into his Cell and Molecular Biology, Molecular Biology of Plants, and Recombinant DNA Technology courses.


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Appendix

Course Logistics:

The CS part of the paired offering will continue to cover topics that are currently being included

in CS 490, but with fundamental changes in the emphasis and teaching of the problems. In particular,

topics of restriction mapping, regulatory motif discovery, genome rearrangements, sequence alignment

(pairwise and multiple), sequencing by hybridization, and phylogenetic trees (both usage and creation)

will be treated then as now, but with fundamental changes in emphasis. Both across the problems and in

the thinking involved within each problem, the biological relevance will be emphasized by a Biological

Sciences faculty member. In the proposed paired CS offering, special attention will be given to enhancing

students’ ability to do the following: critically question existing algorithmic assumptions involved,

translate as much as possible between the biological context in which the problem is originally stated into

the algorithmic context of the necessary computational solution, compare the optimality of various

computational solutions based not only on standard algorithmic complexity criteria but also on

faithfulness to the realistic biological context, implement select bioinformatics algorithms, and gain

expertise in using and understanding major existing tools and databases. The last mentioned focus

regarding existing tools and databases is something that is not covered in the current offering (though the

related algorithms involved in making the tools are covered), but which is important for a cross-

disciplinary offering due to the importance of such tools and databases to biologists.

The topics for the biology students will mirror those listed above for the CS section. However, the

focus of the material will change. For the biology students, it is more important to have a basic principled

knowledge of computational algorithms to be able to understand the assumptions and limitations

inherent in bioinformatics tools developed by computer scientists. This understanding is critical for

biologists to be able to evaluate and interpret output from complex computational algorithms.

Specifically, this approach will introduce biology students to the types of problems that can be addressed

using bioinformatics, the appropriate tool to answer specific types of biological questions, the available

bioinformatics resources, a basic understanding of how these tools work, and how to interpret their


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output. In addition to these specifics, students from both CS and BIOL will benefit from an

interdisciplinary course environment that features not only lectures from both CS and BIOL faculty, but

also direct, goal-driven interactions with students from the other discipline. Common course objectives

for both courses include: i) understanding fundamental molecular biology laboratory and research

techniques used in generating the genomic/proteomic data of bioinformatics problems, ii) understanding

the computational and algorithmic methods used in tackling the bioinformatics problems, and iii)

understanding and using the existing bioinformatics databases and tools for storage, retrieval, analysis,

and sharing of bioinformatics data. Although both courses must satisfy the three objectives, the BIOL

course will give special focus to (i) and (iii), while the CS course will give special focus to (ii) and (iii),

with the CS emphasis to (iii) being more in the context of understanding rather than using the existing

tools. Projects will be synchronized with respect to the course topics in both CS and BIOL courses, while

project objectives will reflect such differences in emphases across aspects (i), (ii) and (iii).

Campus Box 1608 Tel: 5047 Fax: 5050

COLLEGE OF ARTS AND SCIENCES, OFFICE OF THE DEAN

To: Excellence in Undergraduate Education

From: Wendy Shaw, Associate Dean, College of Arts and Sciences Subject: Dean’s Memo of Support Date: 24 January, 2014 The College of Arts and Sciences supports the application of Dr. Darron Luesse and Dr. Gunes Ercal (from

the School of Engineering) for an EUE grant. As the Chair of his department indicates, this project would

update and enhance the curriculum and would serve the University foci on interdisciplinarity and

collaboration. A robust and updated curriculum, supports the retention of students, which is a high priority

for the University. This project also has the potential to be a first step in future collaborations .

Prior EUE Support Project Director Project Number Award Amount Project Dates Prior Results Additional Information on Prior Projects

Documents

EUE Proposal FY2015 Department Campus Box School/College · Project ID# 15_008 Project Title Towards an Interdisciplinary Bioinformatics Curriculum Project Director ID Number Telephone