BINF 1101. Introduction to Bioinformatics and Genomics (4) Designed to introduce students to the genomics perspective in the life sciences, this course combines a general introduction to genomic technologies and the bioinformatics methods used to analyze genome-scale data with a presentation of real world scientific problems where these technologies are having an impact. This course provides hands-on experience with biological sequence and structure databases, using small-scale projects to introduce students to the world of bioinformatics research. This course fulfills a general education science requirement. Syllabus
BINF 2111. Introduction to Bioinformatics Computing.(4) This course introduces fundamentals of programming for bioinformatics (sometimes called “scripting”) using current programming languages and paradigms. Introduces both the language and the use of the language within a Unix environment, demonstrating how interpreted languages serve both as a useful tool for writing and testing programs interactively and as a powerful data analysis and processing tool for bioinformatics. Syllabus
BINF 3101. Sequence Analysis.(3) Prerequisite: Permission of instructor. This course covers the purpose, application, and biological significance of bioinformatics methods that identify sequence similarity, methods that rely on sequence similarity to produce models of biological processes and systems, as well as methods that use sequence characteristics to predict functional features in genomic sequence data. Syllabus
BINF 3121. Statistics for Bioinformatics.(3) Prerequisite: BINF 2111 and satisfactory completion of either MATH 1103, MATH 1120, MATH 1121, MATH 1241, STAT 1220, STAT 1221, STAT 2122, or permission of instructor based on sufficient demonstration of foundational mathematics concepts. Concepts from probability, stochastic processes, information theory, and other statistical methods will be introduced and illustrated by examples from molecular biology, genomics and population genetics while exploring the use of the R and Bioconductor software for biostatistical analysis. Syllabus
BINF 3131. Bioinformatics Algorithms. (4) Introduction to common algorithms and data structures for bioinformatics problems. Focuses on teaching students how to formulate a biological problem as a computational problem, and then solving it using efficient algorithms. Intended for students who have programming skills and basic molecular biology knowledge.
BINF 3201. Genomic Methods. (3) Prerequisites: BIOL 1101 and 1101L, or BIOL 2120, or permission of instructor. Pre- or corequisite: BINF 1101. Corequisite: BINF 32011L. Lecture topics introduce students to core concepts in genomics that allow bench scientists to acquire large datasets in a high-throughput manner as well as address the computational methods used to analyze these data resources.
BINF 3211. Bioinformatics Databases and Data Mining Technologies. (3) Prerequisite: BINF 1101. Lecture courses that incorportates extensive computational exercises, some of which will be done in class. Lecture topics are intended to introduce students to core concepts in both database management system theory and implementation and in data modeling for genomics data types. Exercises are intended to give students practical experience in setting up and populating a database, using public data repositories and using standard tools for retrieving data (SQL), and further, using existing tools for data mining and visualization of genomics data types. Emphasis placed on standards and emerging practices.
BINF 3900. Undergraduate Research. (1-3) Prerequisites: BINF 1101 and permission of the instructor. Enables students in the Bioinformatics and Genomics program to initiate research projects in their respective fields of interest and to interact with faculty in pursuing research experience. May be repeated for credit.
BINF 4010. Topics in Bioinformatics and Genomics. (1-3) Permission of department.
BINF 4101. Computational Systems Biology. (3) Prerequisite: BINF 3101. The process of reconstructing complex biological networks. Reconstruction of metabolic networks, regulatory networks and signaling networks using bottom-up and top-down approaches will be addressed using collections of historical data as well as departmentally generated data. The principles underlying highthroughput experimental technologies and examples given on how this data is used for network reconstruction, consistency checking, and validation will be covered throughout the semester.
BINF 4111. Structural Bioinformatics (3) Prerequisite: BINF 3101. Includes the physical forces that shape biological moleculeds, assemblies and cells; overview of protein and nucleic acid structure; experimental methods of structure determination; data formats and software for structure visualization; computational methods to evaluate structure; structural classification; structure alignment; computational algorithms for structure prediction; and structural analysis of disease-causing mutations.
BINF 4171. Business of Biotechnology. (3) Prerequisite: Junior or Senior standing in a scientific/technical course of study or if in a non-biological/technical or scientific program, special permission of the instructor. Introduces students to the field of biotechnology and how biotech businesses are created and managed. The students should be able to define biotechnology and understand the difference between a biotech company and a pharmaceutical company. Additional concepts covered will include platform technology, biotechnology’s history, biotechnology products and development processes, current technologies used by biotech companies today, biotechnology business fundamentals, research and development within biotech companies, exit strategies, and careers in the biotech field.
BINF 4191. Biotechnology and the Law. (3) Prerequisite: Junior or Senior standing in a scientific/technical course of study or if in a non-biological/technical or scientific program, special permission of the instructor. At the intersection of biotechnology and the law, an intricate body of law is forming based on constitutional, case, regulatory and administrative law. This body of legal knowledge is interwoven with ethics, policy and public opinion. Because biotechnology impacts everything in our lives, the course will provide an overview of salient legal biotechnology topics, including but not limited to: intellectual property, innovation and approvals in agriculture, drug and diagnostic discovery, the use of human and animal subjects, criminal law and the courtroom, agriculture (from farm to fork), patient care, bioethics, and privacy. The body of law is quite complex and it is inundated with a deluge of acronyms. The course will provide a foundation to law and a resource to help students decipher laws and regulation when they are brought up in the workplace.
BINF 4211. Applied Data Mining for Bioinformatics. (4) Restrictions: Permission of department. Concepts and techniques of evaluating bioinformatics data. The objective of this course is to provide studens with a working knowledge of data sources, current tools and methodologies used for bioinformatics research through a variety of hands-on data analysis activities.
BINF 4600. Bioinformatics and Genomics Seminar. (1) Prerequisite: BINF 3101 or permission of instructor. A senior level seminar course designed to introduce students to the research being conducted in both the Department of Bioinformatics and Genomics at UNC Charlotte, as well as through invited speakers from other universities. Syllabus
BINF 4650. Senior Project (On Demand) (1-3) Prerequisites: Senior standing and permission of the department. An individual or group project in the teaching, theory, or application of bioinformatics, genomics, or computational biology under the direction of a faculty member. Projects must be approved by the department before they can be initiated.