BMI315
Course: BMI-315 Tools for Biomedical informatics with Lab
(5 contact hours, 4 credit hours)
Course Description:
This course explores the concepts of computational medicine and biology using a tools-oriented approach. Topics include string manipulation in PERL, data searches, statistical techniques and programming, and microarray and proteomics technologies. The use of web-based bioinformatics tools is covered in detail. A working knowledge of MATLAB’s Bioinformatics Toolbox and the UNIX/Linux environment is also provided. Lab exercises support topics presented. Prerequisites: BMI310 / 5-4
Texts and Materials:
D. Krane and M. Raymer. Fundamental Concepts of Bioinformatics, Benjamin Cummings. 2003.
C. Gibas and P. Jambeck. Developing Bioinformatics Computer Skills. O'Reilly, 2001.
D. Curtis Jamison Perl programming for Biologists. Wiley & Sons, 2003.
Terminal Course Objectives:
1. Given biomedical informatics data in various formats identify, compare, and analyze data in these formats.
(Gbk; ASN.1; EMBL; PDB; FASTA, HL7 formats)
2. Given an online archive of bioinformatics data, access the data, retrieve information, and perform data analysis operations.
(NCBI: Genbank, OMIM, GEO, SNPdb; EBI, PDB)
3. Given a set of DNA and protein sequences, create and interpret multiple sequence alignments using online and local tools.
(ClustalW; Jalview; Phylip; BLAT; BLAST; FASTA)
4. Given a bioinformatics problem such as reading and manipulating data from a FASTA formatted file, write and document a Perl program to solve this problem.
(Variables; Calculations; Arrays; Hashes; IF; Loops)
5. Given a bioinformatics problem requiring advanced string manipulation, write and test a Perl program to solve this problem.
(Regular expressions; Patterns; File I/O; Subroutines and Functions; Perl Modules and
Packages; Bioperl)
6. Given a bioinformatics problem such as that in TCO#4, utilize the UNIX/Linux operating system to manipulate the FASTA formatted file and other files and directories.
(UNIX commands; Shells; Pattern matching; the vi editor)
7. Given a protein structure file in PDB format, visualize and interpret the structure using a virtual 3D representation.
(RasMol; PyMol; CN3D; VMD)
8. Given genetic data such as microarray data, perform statistical analysis of that data involving confidence intervals, p-values, Bayesian logic, and other common statistical tests.
(Confidence Intervals; P Values and their significance; Bayesian logic; Statistical tests;
Unpaired t test; Paired t test; Chi-Squared test; Correlation Coefficient; ANOVA)
9. Given an example gene data set, implement programs to integrate with key functional categories such as alignments provided in existing bioinformatics software products such as MATLAB’s BioInformatics ToolBox.
(Microarray; Sequencing; Mass spectrometry)
Course Requirements and Policies:
Class attendance and student interactions are important parts of the learning experience. It is expected that each student attends every class, arrives on time, and remains for the entire class period. Absences, tardiness, or partial attendance will result in missed classroom experiences. This in turn could result in a low grade or potential failure in class, as attendance is strongly related to academic performance. Please discuss with me any circumstances that may necessitate missing a class.
Test makeups policy
There are no makeups for a test except emergency situations. Makeup exams are essay. Labs must be turned in on the day they are due. Late labs and homework will be docked 25%.
Resources:
There are many resources available to help students be successful in this course. There is assistance available in the Academic Resource Center in the way of one on one tutoring help. Class notes and handouts provided for topics covered are helpful as well. All lectures, lab materials, exercises and assignments will be available digitally in Doc sharing before or right after each class. Students can also feel free to email me.
Grading:
The grades are based on a standard scale.
For Class and lab:
The class grade for this course will be computed according to the following categories of grades and points indicated.
Course Schedule - 15 Week: