BIFX - Bioinformatics

Prerequisite: Admission to the MS in Bioinformatics. Lab fee. A foundation course in cell biology and genome science for the non-life scientist.

Prerequisite: Admission to the MS in Bioinformatics. Lab fee. This course provides students with an introduction to programming concepts and techniques used in problem solving. Students will study general programming concepts for the purpose of data analysis. These concepts are demonstrated through the use of a modern programming language. Students will design, implement and test programs to solve analytical problems primarily in IT, business, and science. Students will develop the ability to logically plan and develop programs, and learn to write, test, and debug programs. Topics include file I/O, expressions, types, variables, branching, loops, data access, data profiling, and data manipulation. Students will apply their knowledge through hands-on programming projects.

Prerequisite: Admission to the Certificate or MS in Bioinformatics. Lab fee. This course will focus on the statistical concepts that are used in biology and medicine to analyze and validate data. Topics will include probability, hypothesis testing, tests for variables (e.g. chi-square, Fisher’s test), t-test, linear and multivariate regression, covariance and Bayesian statistic.

Prerequisite: BIFX 551 or permission of the instructor. Lab fee. A study of the design and implementation of databases from a real world applications point of view. The course includes a review of database concepts such as basic architectural issues, the relational model, query processing, logical database design and normalization theory and data protection issues. The course will also address topics such as assessing end-user needs, developing specifications, designing functionally equivalent solutions and evaluating commercial database packages.

Prerequisites: BIFX 501 or 502. Lab fee. Within the context of Bioinformatics – a cross-disciplinary field that uses computers, statistics, and mathematics to store, model and analyze biological data - the goal of the course is to enable translational, interdisciplinary scientists to understand the importance of leadership to the field and the team. Candidates will explore their own leadership style, consider leadership qualities necessary for a successful team, understand the interactions within a complex matrix environment in a Life Science organization and apply leadership and management skills to bioinformatics projects.

Prerequisites: BIFX 501 or 502 and BIFX 503. Lab fee. This course will provide an introduction to knowledge reasoning and the field of machine learning, allowing the students to capture and represent in a computer real world data (such as biological data) that can be used to solve complex problems. The foundations of machine learning will provide the students with more advanced methods to analyze data. Topics that will be covered include logic, ontology engineering and semantic, reasoning systems, pattern recognition, supervised and unsupervised learning, data mining.

Prerequisites: BIFX 501 or BIFX 502. Lab fee. The goal of this course is to provide the students with a more in-depth overview of web-based bioinformatics tools and other freely available tools. As a bioinformatician works to solve specific problems, sometimes it is easier to use the existing, available tools rather than building a new one, thus providing a time-saving approach to the specific task. The course will emphasize a hands-on approach using available tools and public domain data.

Prerequisite: BIFX 551. Lab fee. Data visualization is a sub-area of Human-Computer Interaction (HCI). Students will learn the theories and tools of data visualization. The course content is about 40% theory and 60% practice. This course covers the basic theories of data visualization, such as data types, chart types, visual variables, visualization techniques, structure of data visualization, navigation in data visualization, color theory, cognitive theory, and visualization evaluation.

Prerequisite: Admission to the Bioinformatics Certificate or the Biomedical Science program and BIFX 501. Lab fee. This course will begin and extend beyond the basics and prepare students to use sequence and structural information to solve biological problems. This course serves as an intermediate level class for graduate students who plan to work in the areas of computational biology or bioinformatics using available applications. This course will lay foundations for data storage, visualization, manipulation, comparison, and analysis of 1D-protein/DNA sequences and their corresponding experimental/model 3D-structures using existing bioinformatics tools. A basic introduction to scripting will also be included.

Prerequisite: Admission to the Bioinformatics Certificate or the Biomedical Science program and BIFX 501 or BIFX 502. Lab fee. This class will provide students with an introduction to the Perl, Python and R programming languages. The concepts will be put in context with examples and uses relevant to Bioinformatics. Examples covered will range from data file retrieval and manipulation, to sequence analysis, microarray analysis, data presentation and visualization.

Prerequisite: Admission to the Bioinformatics Certificate or the Biomedical Science program and BIFX 551. Lab fee. This class provides an introduction to manipulating primary data and the application of the statistical methods to evaluate this complex data. Common bioinformatics tasks should be automated to not only improve efficiency but also to avoid manual errors. There are many ways to automate these common tasks, the popular ones are shell scripting and programming using higher level languages. Shell scripting provides access to a powerful command interpreter that is often used to prepare and organize data. Of several similar languages, Perl is commonly used in bioinformatics because of the number of readily available modules for recurring tasks and relative ease to learn to code. A statistical and visualization programming environment, R, will also be introduced using specific bioinformatics examples.

Prerequisite: Admission to the Bioinformatics Certificate or the Biomedical Science program and BIFX 552. Lab fee. This class builds on the statistics and programming skills introduced in BIFX 552. Additional statistical concepts will be introduced as applied to the analysis of transcripts, biomarker discovery (proteomics) and microarray analysis. Students will execute these concepts using their previous experiences with Perl and/or R as well as incorporating new and more complex programming tasks.

Prerequisites: BIFX 553. Lab fee. This course offers students the opportunity to synthesize all the concepts and skills acquired in the previous BIFX bioinformatics courses. Students will apply basic database concepts to generate an internal database from public primary data and develop and execute a project to address a biological question using appropriate statistics and programming skills.

Prerequisite: Completion of or concurrent enrollment in BIFX 545 and 550 and permission of the instructor. Lab fee. The Capstone Project will provide the student with the opportunity to apply bioinformatics skills and techniques to actual genomic and proteomic data in a real life sciences research environment. An internship with a leading research groups that make use of bioinformatics tools is strongly suggested, and the students will also further develop the ability to work in a matrix team. As an alternative, students will work with Hood Faculty on a specific project.