IUPUI Bulletins » Schools » School of Informatics and Computing » Courses » Bioinformatics Courses

Bioinformatics Courses

  • INFO-I 501 Introduction to Informatics (3 cr.) Basic information representation and processing; searching and organization; evaluation and analysis of information. Internet-based information access tools; ethics and economics of information sharing.
  • INFO-B 505 Informatics Project Management (3 cr.) This course introduces standard project management concepts and capabilities, in the context of innovative and creative knowledge-work projects involving computers. These are targeted as a common ground for all members of a successful team, not only for the Project Manager. Through lecture, reading, discussion, computer lab exercises, and projects, students will become more proficient with basic project management terminology, techniques and technologies. Students will apply industry-standard project management in a framework of productive team dynamics, consumer frame of reference, and organizational change and optionally continuing to professional certification.
  • INFO-B 510 Data Acquisition and Laboratory Automation (3 cr.) This course covers the entire process by which signals from laboratory instruments are turned into useful data: (1) fundamentals of signal conditioning and sampling; (2) interfacing, communications, and data transfer; (3) markup languages and capability systems datasets; (4) general lab automation; (5) robotics. A significant portion of this course is devoted to practical learning using LabVIEW.
  • INFO-B 512 Scientific and Clinical Data Management (3 cr.) Management and mining of data generated in scientific laboratories and clinical trials for data mining and knowledge discovery requires robust solutions that include knowledge discovery techniques and databases, extraction of data/metadata stored in data warehouses that use Storage Use Networks and dealing with security issues of handling this data.
  • INFO-B 519 Introduction to Bioinformatics (3 cr.) In this course, students learn fundamental concepts and methods in bioinformatics, a field at the intersection of biology and computing. It surveys a wide range of topics including computational sequence analysis, sequence homology searching and motif finding, gene finding and genome annotation, protein structure analysis and modeling, genomics and SNP analysis, DNA microarrays and gene expression analysis, Proteomics, network/systems biology, and biological knowledge discovery. It serves a gateway course for all entry-level bioinformatics graduate students. Prerequisite: students should be enrolled in the graduate program of bioinformatics, or have advanced training in at least one of the following areas: computer science, applied mathematics, quantitative biomedical sciences, bioengineering, biotechnology, and biostatistics.
  • INFO-B 529 Machine Learning for Bioinformatics (3 cr.) P: B519 The course covers advanced topics in bioinformatics with a focus on machine learning. The course will review existing techniques such as hidden Markov models, artificial neural network, decision trees, stochastic grammars, and kernel methods. Examine application of these techniques to current bioinformatics problems including: genome annotation and comparison, gene finding, RNA secondary structure prediction, protein structure prediction, gene expression analysis, proteomics, and integrative functional genomics.
  • INFO-B 531 Seminar in BioHealth Informatics (1-3 cr.) Presentation and discussion of new topics in bioinformatics as seminar by students. Concentration on a particular area each semester to be announced before registration. May be taken up to 3 times. Total credit for seminars and independent study courses may not exceed 9 credit hours.
  • INFO-B 552 Independent Study in Bioinformatics (1-3 cr.) Independent study under the direction of a faculty member, culminating in a written report. May be repeated for credit. Total credit for seminars and independent study courses may not exceed 9 hours.
  • INFO-B 556 Biological Database Management (3 cr.) This course studies database management and its application to bioinformatics. Topics include data modeling, data indexing and query optimization with a bioinformatics perspective, and database issues arising from the complex nature of bioinformatics data. The course also involves the study of current challenges related to bioinformatics data management, data integration, and the Semantic Web.
  • INFO-B 573 Programming for Science Informatics (3 cr.) Students will receive a thorough understanding of software development for chem- and bioinformatics, and broaden experience of working in a scientific computing group. Topics include programming for the web, depiction of chemical and biological structures in 2D and 3D, science informatics tool kits, software APIS, AI and machine-learning algorithm development, high-performance computing, database management, managing a small software development group, and design and usability of science informatics software.
  • INFO-I 575 Informatics Research Design (3 cr.) Full spectrum of research concepts, designs, and methodologies used in informatics research, from quantitative to qualitative research; from deterministic, hypothesis-driven experimental designs to a posteriori discovery through data mining. Philosophical foundations to practical applications. Provides the conceptual framework in which the informatics graduate student may develop their own research agenda.
  • INFO-B 576 Structural Approaches to Systems Biology (3 cr.) Computational approaches to characterizing and predicting tertiary protein configuration, based on known data of atomic, intramolecular and intermolecular interactions. The course presents a balanced and integrative outlook at the various molecular components that determine biological function, sub-cellular organization, dysfunction and even disease examined at the nanoscale.
  • INFO-B 601 Introduction to Complex Systems (3 cr.) This course is an introduction to dynamic complex systems and complexity management, using the basic mathematical notions of dynamical system theory, without being highly technical mathematically. The course provides an evaluation of models, theories, methods and research from an operational and disciplined approach. Students will be introduced with a new way of making sense of each of these and other issues by exploring how other complex adaptive systems behave. The course will revolve around some cardinal topics including but not limited to reductionism versus system biology, chaos theory, fractal networks, self similarity, agent-based models, discrete and continuous simulation, evolution, artificial life, social network theory, etc. each one introduced by specific examples and abstracted thereby.
  • INFO-B 619 Structural Bioinformatics (3 cr.) This course covers the function of biological macromolecules (DNA, RNA, protein) and informatics approaches based on their sequence and 3D structure. Topics include molecular  visualization, structure determination and alignment, and the prediction of protein structure, interactions, and function.
  • INFO-B 621 Computational Techniques in Comparative Genomics (3 cr.) Course will summarize computational techniques for comparing genomes on the DNA and protein sequence levels. Topics include state-of-the-art computational techniques and their applications: understanding of hereditary diseases and cancer, genetic mobile elements, genome rearrangements, genome evolution, and the identification of potential drug targets in microbial genomes.
  • INFO-B 627 Advanced Seminar I–Bioinformatics (3 cr.) Introduce students to major historical, contemporary, and emerging theories, methods, techniques, technologies and applications in the field of Bioinformatics. Students will explore relevant and influential research, results and applications. Students will develop an understanding of leading research approaches and paradigms, and will design an independent research program in relation to their individual research fields and personal interests. The course will focus on research approaches in bioinformatics, emerging technologies in biology and chemistry, and basic computational techniques.
  • INFO-B 637 Advanced Seminar II – Bioinformatics (3 cr.) P: Advanced graduate standing or consent of instructor. Introduces students to major historical contemporary and emerging theories, methods, and techniques in the field of Bioinformatics. Students will examine and explore relevant and influential research, results and applications. Students will develop an understanding of leading research approaches and paradigms, and will design and independent research program in relation to their individual research fields and personal interests. The course will focus on research approaches in bioinformatics, emerging technologies in biology and chemistry, and basic computational techniques.
  • INFO-B 646 Computational Systems Biology (3 cr.) Introduction of how Omics data are generated, managed, analyzed from large-scale computational perspectives, exploring computational resources, especially biological pathways for integrative mining and computational analysis representing and modeling multiscale biological networks, relating static/dynamic properties to the understanding phenotypic functions at the molecular systems level.
  • INFO-B 656 Translational Bioinformatics Applications (3 cr.) This course entails a cohesive approach to the theory and practice of bioinformatics applications in translational medicine (TM). It includes topics related to the complexities of low, medium and high-throughput applications in TM and powerful solutions to TM data management problems by employing various informatics frameworks.
  • INFO-B 691 Thesis/Project in Health Informatics (1-6 cr.) The student prepares and presents a thesis or project in the area of health informatics. The product is substantial, typically multi-chapter paper or carefully designed and evaluated application, based on well-planned research or scholarly project. Details are worked out between the student and sponsoring faculty member.
  • INFO-B 692 Thesis/Project in Bioinformatics (1-6 cr.) The student prepares and presents thesis or project in an area of bioinformatics. The product is substantial, typically a multi-chapter paper or carefully designed and evaluated application, based on well-planned research or scholarly project. Details are worked out between student and sponsoring faculty member.
  • INFO-B 605 Social Foundations of Informatics (3 cr.) Topics include the economics of information businesses and information societies, legal and regulatory factors that shape information and information technology use, the relationship between organization cultures and their use of information and information technology, and ownership of intellectual property.
  • INFO-I 590 Topics in Informatics (3 cr.) Variable topic. Emphasis is on new developments and research in informatics. Can be repeated with different topics, subject to approval of the Dean.
  • INFO-B 690 Topics in Informatics (3 cr.) Variable topic. Course is intended for Ph.D. students in the School of Informatics. Can be repeated with different topics, subject to approval of the dean.
  • INFO-I 699 Independent Study in Informatics (1-3 cr.) Independent readings and research for Ph.D. students under the direction of a faculty member, culminating in a written report. May be repeated for a maximum of 12 credit hours.
  • INFO-I 790 Informatics Research Rotation (3 cr.) Work with faculty, investigate research opportunities. Can be repeated for a total of 6 credit hours.
  • INFO-I 890 Thesis Readings and Research (1-12 cr.) Research under the direction of a member of the graduate faculty leading to a Ph.D. dissertation. Can be repeated for credit for a total of 30 credit hours.
  • INFO-B 698 Research in Informatics (1-12 cr.) Research under the direction of a member of the graduate faculty that is not dissertation related. Can be repeated for credit for a total of 30 credit hours.
  • INFO-I 600 Professionalism and Pedagogy in Informatics (3 cr.) This course introduces students to topics and skills necessary for entering careers in industry or the academy. Topics covered include career planning, curriculum development, effective teaching, research ethics, scholarly and trade publishing, grantsmanship, and intellectual property consideration.
  • INFO-G 599 Thesis Research (0 cr.) P: Master's students who have enrolled in 30 or more hours of graduate course work applicable to the degree and who have completed all other requirements of the degree except the thesis of final project of performance. Requires section authorization.  
  • INFO-H 559 MEDIA AND TECHNOLOGY ENTREPRENEURSHIP (3 cr.) This course is intended for students who are interested in starting their own company or who anticipate joining a start-up company. It will provide students with a solid foundation on a variety of legal and business matters that need to be considered when starting a new company, such as selecting a business structure (sole proprietorship, partnership, corporation, etc.), financing and credit, drafting business plans, preparing appropriate paperwork such as articles of incorporation and bylaws, tax implications, marketing and public relations, bankruptcy and other pitfalls, insurance, planning for growth, resources for entrepreneurs, contracts, real and personal property, shareholder and governance issues and working with professionals such as attorneys, accountants and insurance agents.
  • INFO-H 611 Mathematical and Logical Foundations of Informatics (3 cr.) An introduction to mathematical methods for information modeling, analysis, and manipulation. The topics include proof methods in mathematics, models or computation, counting techniques and discrete probability, optimization, statistical inference and core advanced topics that include, but are not limited to, Markov chains and random walks, random graphs, and Fourier analysis.
  • INFO-B 572 Computational Chemistry and Molecular Modeling (3 cr.) P: INFO-I 571. Computer models of molecules and their behavior in gas and condensed phases; implicit and explicit solvation models; quantum and molecular mechanics; search strategies for conformational analysis; geometry optimization methods; information content from Monte Carlo and molecular dynamics simulations; QSAR; CoMFO; docking.
  • INFO-H 504 Social Dimensions of Science Informatics (3 cr.) Course will examine ethical, legal, and social issues surrounding contemporary research and practice in science informatics. Topics include the nature of science and technology, the ramifications of recent advances in science informatics, and relevant science policy and research ethics. General knowledge of science informatics is assumed.
  • INFO-B 528 Computational Analysis of High-Throughput Biomedical Data (3 cr.) Course covers advanced concepts of genomics, molecular biology, and systems biology and explores computational methods for analyzing their high-throughput datasets. Problems in biology and biomedicine will motivate the development of algorithms to apply to these datasets.
  • INFO-B 585 Biomedical Analytics (3 cr.) Course introduces the use of patient data, genomic databases, and electronic health records (EHR) to improve patient care and to achieve greater efficiencies in public and private healthcare systems. The course explores clinical intelligence and the role of analytics in supporting a data-driven learning healthcare system. Topics include the value-driven healthcare system, measuring health system performance, existing quality/performance measurement frameworks (NQF, HEDIS), comparing healthcare delivery, attributes of high performing healthcare systems, and the IT infrastructure and human capital needed to leverage analytics for health improvement.
  • INFO-I 595 Professional Internship (1-6 cr.) An experiential learning course where students apply classroom theory and learning in degree-related work experience under the supervision of a mentoring supervisor and course instructor.
  • INFO-B 636 Genomic Data Analytics and Precision Medicine (3 cr.) This advanced course covers how massive clinical and biomedical genomic sequencing datasets from various sequencing platforms motivate computational needs and tasks for analysis, how to devise approaches for analyzing these datasets, how to develop sound hypotheses and predictions from them, and related ethical, privacy, and legal issues.
  • INFO-B 667 Seminar in Interprofessional Collaboration (3 cr.) This seminar provides graduate students with in depth experiences in interprofessional thinking and collaboration when implementing informatics applications. Biohealth Informatics applications are developed an interprofessional learning laboratory rooted in real-life innovation, discovery, and collaboration related to health and wellbeing.
  • INFO-B 668 Advanced Seminar in BioHealth Informatics (3 cr.) Course provides graduate students with knowledge on a wide range of current topics in health informatics from faculty and professionals engaged in cutting edge research and practice. Students connect with innovative faculty while learning through a combination of lectures, practicums, and discussions. The topics and presenters will be different each semester.