Graduate Curriculum Committee Course Proposal Form

Graduate Curriculum Committee

Course Proposal Form for

Courses Numbered 5000 and Higher

Note: Before completing this form, please carefully read the accompanying instructions.

1. Course Prefix and Number: 2. Date:

3. Requested Action (check only one box):

X / New Course
Revision of Active Course
Revision & Unbanking of a Banked Course
Renumbering of an Existing Course from
from / # / to / #

4. Justification (assessment or accreditation based) for new course or course revision or course renumbering:

Computational skills to handle large amounts of molecular data are essential in modern biological studies. Currently most research universities have university-wide bioinformatics programs. For example, Duke University, UNC, UNCC and NCSU all have bioinformatics institutes or departments. However, no formal Bioinformatics course exists at ECU. As a research university, the Department of Biology graduate faculty determined that such a course is urgently needed to prepare our graduate and undergraduate students for the enormous challenges and opportunities in this new genomics era. The proposal is designed for graduate students, in particular those enrolled in the Ph.D. programs of Biology, Biomedical Physics, Biochemistry and Molecular Biology, Microbiology and Immunology and other related departments, to gain skills necessary for biological data analyses.

5. Course description exactly as it should appear in the next catalog:

7880, 7881. Bioinformatics (4, 0) 1 2-hour lecture and 2 2-hour labs per week. P: Course in biochemistry or consent of instructor. Bioinformatic skills necessary for routine molecular sequence analyses using computational programs.

6. If this is a course revision, briefly describe the requested change:

NA
68

7. Graduate Catalog Page Number from current Graduate catalog:

8. Course Credit:

Lecture Hours / 2 / Weekly / OR / Per Term / Credit Hours / 4 / s.h.
Lab / 4 / Weekly / OR / Per Term / Credit Hours / 0 / s.h.
Studio / Weekly / OR / Per Term / Credit Hours / s.h.
Practicum / Weekly / OR / Per Term / Credit Hours / s.h.
Internship / Weekly / OR / Per Term / Credit Hours / s.h.
Other (e.g., independent study) Please explain.
Total Credit Hours / 4 / s.h.
15

9. Anticipated annual student enrollment:

10. Affected Degrees or Academic Programs:

Degree(s)/Course(s) / Current
Catalog Page / Changes in Degree Hours
NA

11. Overlapping or Duplication with Affected Units or Programs:

X / Not Applicable
Notification & response from affected units is attached

12. Approval by the Council for Teacher Education (required for courses affecting teacher education programs):

X / Not Applicable
Applicable and CTE has given their approval.

13.  Statements of Support:

a. Staff

X / Current staff is adequate
Additional Staff is needed (describe needs in the box below):

b. Facilities

Current facilities are adequate
x / Additional Facilities are needed (describe needs in the box below):
Linux (Unix) machines are needed for labs

c. Library

X / Initial library resources are adequate
Initial resources are needed (in the box below, give a brief explanation and an estimate for the cost of acquisition of required initial resources):

d. Computer resources

Unit computer resources are adequate
x / Additional unit computer resources are needed (in the box below, give a brief explanation and an estimate for the cost of acquisition):
See the following and attached e-mail from Jack Brinn
ITCS Resources are not needed
The following ITCS resources are needed (put a check beside each need):
x / Mainframe computer system
Statistical services
x / Network connections
Computer lab for students
Approval from the Director of ITCS attached

14.  Course information: see Instructions for Completing the Graduate Curriculum Committee Course Proposal Form for more detail

a.  TEXTBOOK(S): author(s), name, publication date, publisher, and city/state/country

b.  Course objectives student –centered behavioral objectives for the course –

c.  A course content outline

d.  A list of course assignments and weighting of each assignment and the grading/evaluation system for determining a grade.

Textbook: Xiong, J. 2006. Essential Bioinformatics. Cambridge University Press.

Course objectives:

The student will be able to:

·  Apply NCBI and other biological databases to analyze data

·  Interpret the output information

·  Perform analyses of molecular sequence data

·  Utilize Unix and associated commands to predict protein structure, gene and motif, and regulatory elements prediction

·  Align multiple sequences in order reconstruct biochemical networks

·  Annotate genome sequences

·  Compare pairwise sequence similarity

·  Design and develop simple bioinformatic programs using programming languages such as Python or Perl

·  Solve problems in their own research areas

Course content:

·  Primary and secondary databases

·  GenBank, EMBL and other data formats conversion

·  Unix environment, file and directory processing etc

·  GenBank non-redundant databases and RefSeq

·  Sequence downloading and database creation using formatdb and xformat

·  Entrez, Pubmed, NCBI Taxonomy, and MapViewer

·  Genome assembly and chromosomal reconstruction

·  Pairwise sequences alignment (dotplot, local and global alignments, Needle and Wunsch as well as Simth-Waterman algorithms)

·  Scoring matrices (PAM and BLOSSUM), alignment score calculation, and alignment quality assessment

·  BLAST algorithm and programs (including PSI-BLAST) and output interpretation

·  FASTA

·  Python and programming using Python (data types, operations, methods and functions, control flow, file processing)

·  Multiple sequence alignments (progressive, consistency-based, and iterative alignment algorithms)

·  Clustalw, T-Coffee, ProbCons, Muscle, Mafft, Dialign, ProDA, POA, SATCHMO, Protal2DNA and RevTrans etc.

·  Sequence editors

·  Principles of phylogenetic analyses

·  Phylogenetic application programs (PAUP, PHYLIP, Tree-Puzzle, PHYML, and MrBayes etc.)

·  Phylogenetic tree visualization and manipulation programs (NJPlot, Treeview, Phyloverde, TreeEdit, and Phylo-win etc.)

·  Motif and domain prediction (regular expression-based and profile-based)

·  PROSITE, Emotif, Pfam, ProDom, PRINT, BLOCKS, and SMART etc.

·  Sequence logos

·  Hidden Markov Model and applications

·  Gene Prediction (prokaryotes and eukaryotes)

·  Gene prediction application programs (Glimmer, GlimmerM, GenMark, FGENES, GenScan etc)

·  Prediction of promoters and regulatory elements (BProm, Eponine, McPromoter, FirstEF, TS-W/TSSG, Consite, PromH, Footprinter, rVISTA, CUBIC, MEME, AlignAce, Melina etc.)

·  Protein structure prediction

·  Biochemical network reconstruction

·  Automation and pipeline program development

Evaluation/Grading Scale:

Homework and lab exercises 40%

Midterm exam 25%

Final exam 35%

A= 90-00

B= 89-80

C= 79-70

F= fail

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