BINF Course Descriptions
BINF 354 Foundations in Mathematical Biology (3:3:0).
Prerequisites: completion or concurrent enrollment in all other required
general education courses; chemistry and integral calculus; or
permission of instructor. Interdisciplinary course designed as an
introduction to life sciences for physicists, chemists, engineers, and
mathematicians. Combines knowledge from the core General Education areas
of natural sciences, social and behavioral sciences, quantitative
reasoning, and information technology. Covers selected topics in
ecology, physiology, biochemistry, and behavior. May include biochemical
reaction kinetics, Hodgki Huxley model for cellular electrical activity,
continuous and discrete population interactions, and neural network
models of learning. Techniques utilized include ordinary differential
equations, difference equations, algebraic equations, and computer
BINF 401 Bioinformatics and Computational Biology I (3:3:0).
Prerequisites: BIO 213, IT 108, IT 208, STAT 344 or STAT 250.
Topics are presented as 3-week units: protein sequence, structure prediction and
modeling methods; nucleic acid sequence and structure prediction and evolutionary
models; gene structure prediction in prokaryotes and eukaryotes; image analysis
and biomedical applications.
BINF 402 Bioinformatics and Computational Biology II (3:3:0).
Prerequisites: BINF 401 and BINF 403. Topics are presented as 3-week units:
the design and use of parallel genomics platforms, mapping the measurements to
biomolecules; approaches for inferring biological pathways; simulation methods for
the dynamics of biomolecules; systems approaches to biology.
BINF 403 Bioinformatics and Computational Biology Lab I (1:0:3).
Prerequisites: concurrent enrollment in BINF 401. Laboratories will introduce students to
bioinformatics tools designed to answer research problems in the topics covered in lectures,
such as sequence alignment, sequence pattern recognition, structural conformation modeling,
phylogenetic analysis methods and image comparisons.
BINF 404 Bioinformatics and Computational Biology Lab II (1:0:3).
Prerequisites: concurrent enrollment in 402 and a passing grade in BINF 401 and BINF 403.
Laboratories will introduce students to research bioinformatics tools relevant to lecture
topics such as: the correspondence of measured fragments to parent biomolecules, inference
methods for gene and protein networks, predicting system outputs given specified inputs.
BINF450 Bioinformatics for Life Sciences (4:3:3).
Prerequisites: BIOL 213 and either BIOL 482 or CHEM 463/BIOL 483. The use of bioinformatics
has become pervasive throughout the life sciences. This course will teach the students how
to understand the basis of and use of bioinformatics software in database searching, sequence
analysis, gene identification, genomics, protein structure and phylogeny.
BINF 470 Molecular Biophysics (3:3:0).
Prerequisites: PHYS307 or CHEM331 or permission of instructor. The course offers a broad
introduction into molecular biophysics. The course demonstrates that the application of
methods of physics provides a unique opportunity to tackle complex biological problems.
The course is mainly designed for the students majoring in physics or chemistry, but it
is also useful for the biology majors interested in bioinformatics and computational biology.
This course is cross-listed with PHYS 370.
BINF 491 Senior Thesis in Bioinformatics (1:1:3).
Prerequisites: the bioinformatics minor core classes. A project is chosen and completed under
the guidance of a bioinformatics department faculty member. An oral progress report with a
poster at the fall semester Bioinformatics Student Research Day is required.
BINF 492 Senior Thesis in Bioinformatics (1:1:3).
Prerequisites: BINF 492. A project is chosen and completed under the guidance of a bioinformatics
department faculty member. A written thesis in standard format is required.
BINF 630 Bioinformatics Methods (3:3:0).
Prerequisites: Graduate standing or permission of instructor.
Introduction to bioinformatics methods and tools for pairwise sequence
comparison, multiple sequence alignment, phylogenetic analysis, protein
structure prediction and comparison, database similarity searches, and
discovery of conserved patterns in protein sequence and structures.
BINF 631 Molecular Cell Biology for Bioinformatics (3:3:0).
Prerequisites: Undergraduate background in biochemistry or cell
biology, or permission of instructor. Intensive review of aspects of
biochemistry, molecular biology, and cell biology necessary to begin
research in bioinformatics. Topics include cell structure and cell
cycle; DNA replication, transcription, and translation; molecular
structure of genes and chromosomes.
BINF 633 Molecular Biotechnology (3:3:0).
standing or permission of instructor. Lecture-based course introducing
the theory and practice of biotechnology, with emphasis on molecular
biotechnology. The lectures address how biotechnology and recombinant
DNA technology affects society. Topics include a review of protein
and nucleic acids technology, a review of recombinant DNA principles
and applications, topics in prokaryotic and eukaryotic gene expression
and products purification, medical applications and agricultural
applications. Lectures reflect the recent advances and applications in the field.
BINF 634 Bioinformatics Programming (3:3:0).
Prerequisites: Graduate standing and computer programming experience or
permission of instructor. Data representation, control structures, file
input/output, subroutines, regular expressions, debugging, introduction
to relational databases. An emphasis on bioinformatics applications
including DNA sequence analysis, parsing FASTA and GenBank files,
processing BLAST output files, SQL or equivalent query language.
BINF 636 Microarray Methodology and Analysis (3:3:0).
Prerequisite: BINF 633 or permission of instructor.
Theory and practice of genome analysis, including the genetics,
biochemistry, and tools for analysis of global gene expression, as
well as the detection and quantification of genes and gene products.
BINF 637 Forensic DNA Sciences (3:3:0). Prerequisites: Graduate
standing or permission of instructor. Intensive introduction to parameters
affecting data QC and analysis, including factors arising from biochemistry,
chemistry, genetics, statistics, instrumentation, and software.
BINF 639 Biometrics (3:3:0). Prerequisites: Programming
experience (e.g. CSI 603 and 604) or permission of instructor.
Introduction into methods for measuring humans. Topics include face
recognition, speaker recognition, fingerprint recognition, shoeprint
recognition, hand writing analysis, and other topics as time permits.
Students will develop computer programs to perform many of these
BINF 650 Data Modeling for Bioinformatics (3:3:0). Prerequisites:
BINF 634 or equivalent, or written permission of the instructor.
Bioinformatics Databases and Data Models Students will acquire skills
needed to exploit public biological databases, and establish and maintain
personal databases that support their own research; such skills include
learning underlying data models and the basics of DBMS, and SQL.
BINF 690 Numerical Methods for Bioinformatics (3:3:0). Prerequisites:
Calculus and knowledge of a programming language, e.g., CS 112 and MATH
113, or permission of the instructor. Computational techniques for
solving scientific problems focusing on applications in bioinformatics
and computational biology. The student will develop the ability to
convert a quantitative problem into computer programs to solve the
problem. Efficiency and readability of code will be emphasized.
BINF 701/BIOS 701 Biochemical Systematics (Biochemistry)(3:3:0).
Prerequisite: Admission to the Ph.D. program in biosciences or
bioinformatics, CHEM 663 or equivalent. Introduction to biochemical
systems now in use to investigate complex, multicomponent, dynamic
functions of cellular systems. Such studies employ myriad conceptual and
technical approaches in their application. Articles from current
literature are basis of course offering. The application of molecular
techniques within biosciences is now universal. The cell: What is its
structure and how does it function? This is the underlying question of
BINF 702/BIOS 702 Research Methods (3:3:0). Prerequisite:
Admission to the Ph.D. program in bioinformatics or biosciences or
permission from instructor. This course trains students in research
methodologies for the life sciences. The course will cover the three
phases of biological research projects: experimental design, data
collection, and data analysis.
BINF 703 Bioinformatics Lab Rotation (1:0:1). Prerequisite: Permission of
instructor. Short-term introductory research on a specific topic in
computational sciences and informatics under the direction of a faculty
member. May be repeated as necessary.
BINF 704 Colloquium in Bioinformatics (1:1:0). Prerequisite: Graduate
standing. Seminar presentations in a variety of areas of bioinformatics
and computational biology by School of Computational Sciences faculty,
staff, advanced Ph.D. students, and professional visitors. May be
repeated for credit.
BINF 705 Research Ethics (1:1:0). Prerequisite: Permission of instructor. An
examination of ethical issues in scientific research. The course begins
with a reflection on the purpose of scientific research and a review of
the foundational principles used for evaluating ethical issues. It
provides skills for survival in scientific research through training in
moral reasoning and teaching of responsible conduct. Students learn to
apply critical thinking skills to the design, execution, and analysis of
experiments and to the analysis of current ethical issues in
research. Such issues include the use of animals and humans in research,
ethical standards in the computer community, and research fraud. In
addition, currently accepted guidelines for behavior in areas such as
data ownership, manuscript preparation, and conduct of persons in
authority may be presented and discussed in terms of relevant ethical
BINF 730 Biological Sequence Analysis (3:3:0). Prerequisites:
BINF 702 or previous courses in programming, molecular biology, and
probability, or permission of instructor. Fundamental methods for the
analysis of nucleic acid and protein sequences, including pairwise
alignment, multiple alignment, database search methods, profile
searches, and phylogenetic inference. Development of probabilistic
tools, including hidden Markov models and optimization
algorithms. Survey of current software tools.
BINF 731 Protein Structure Analysis (3:3:0). Prerequisite: Permission
of instructor, or coursework in molecular biology, biochemistry, and
computer programming. Computational methods for the
analysis, classification and prediction of three-dimensional protein
structures. The course covers theoretical approaches, techniques, and
computational tools for protein structure analysis.
BINF 732 Genomics (3:3:0). Prerequisites: BINF 730 or previous courses
in biology, numerical methods, and programming, or permission of
instructor. A survey of computational tools and techniques used to study
whole genomes. The biological basis of genome analysis algorithms will
be explored. Lecture topics include genome mapping, comparative
genomics, and functional genomics.
BINF 733 Gene Expression Analysis (3:3:0). Prerequisites:
Programming experience and a course in molecular biology, or
permission of instructor; S-Plus or Matlab experience may also be
helpful. This course will focus on the analysis of gene expression
data. Particular topics include: cluster analysis and visualization of
expression data; inference of genetic regulatory networks; and
theoretical models of genetic networks.
BINF 734 Advanced Bioinformatics Programming (3:3:0).
Prerequisites: BINF 634 or permission of the instructor. Selected
topics including algorithm design, complex data structures, object
oriented programming, relational databases, designing modules, graphics
programming, web programming. Students will complete a bioinformatics
BINF 739 Topics in Bioinformatics (3:3:0). Prerequisite: Permission of
instructor. Selected topics in bioinformatics not covered in
fixed-content bioinformatics courses. May be repeated for credit as
BINF 740 Introduction to Biophysics (3:3:0). Prerequisites: The students are
expected to be familiar with basic physical concepts, calculus, and biology on
undergraduate level. This graduate course is designed as a broad introduction
into the field of biophysics for the students with the background in biology,
chemistry, computer science, or physics. The goal of the course is to present
basic concepts of physics and chemistry and map them on a rapidly expanding
interdisciplinary interface, combining biology, chemistry, and physics. The
course reveals multiscale nature of biophysics by exploring macroscopic and
microscopic applications. The course aims to balance the need for rigorous
mathematical treatment with the simplicity of presentation.
BINF 741 Computer Simulation of Biomolecules (3:3:0).
Prerequisites: Students are expected to be familiar, on an
undergraduate level, with basic concepts in physics, calculus, and
programming language suitable for numerical computations.
Knowledge of biological aspects of simulations is not
required. This course is intended to serve as an introduction to
computational methods for simulating biological macromolecules, such as
proteins, DNA and RNA. It is designed for the students who are
interested in computational biology and whose background is in physics,
chemistry, biology, computer science, or mathematics.
BINF 751 Biochemical & Cellular Models (3:3:0).
Prerequisites: Calculus and knowledge of a programming language.
Knowledge of differential equations is helpful. A student in this
course will learn concepts and techniques that will enable them study
cellular and subcellular processes using computational and mathematical
methods. They will learn to describe a cellular or subcellular process
by mathematical equations and analysis this system using mathematical
and computational methods in order to get insight into cellular function
in normal and diseased organisms.
BINF 760 Machine Learning for Bioinformatics (3:3:0). Prerequisites:
Familiarity with bioinformatics methods and databases (e.g., BINF630), molecular
cell biology (e.g., BINF631), bioinformatics programming (e.g., BINF634), or
permission of the instructor. The course introduces machine learning and data
mining methods relevant to application to problems in computational biology.
Methods include decision trees, random forests, rule learning methods, support
vector machines, neural networks, genetic algorithms, instance based learning,
Bayesian networks, and evaluation metrics for learning systems. Applications
include cancer prediction, gene finding, protein function classification, gene
regulation network inference, and other recent bioinformatics applications
selected from the literature. In addition to lectures from the instructor,
students will present papers from the literature, and complete a machine learning project.
BINF 796 Directed Reading and Research (3:3:0).
Prerequisites: Permission of the instructor. Reading and research
on a specific topic in bioinformatics under the
direction of a faculty member. May be repeated as necessary.
BINF 798 Research Project (3:0:0).
Prerequisites: Twelve graduate credits and permission of instructor.
Project chosen and completed under the guidance of a graduate faculty
member, which results in an acceptable technical report.
BINF 799 Master's Thesis (1-6:0:0).
Prerequisites: Twelve graduate credits and permission of instructor.
Project chosen and completed under the guidance of a graduate faculty
member, which results in an acceptable technical report (master's
thesis) and oral defense. Graded S/IP.
BINF 820 Advanced Topics in Molecular Cell Biology (3:3:0).
Prerequisites: Molecular Cell Biology for Bioinformatics or permission
from the instructor. This course will provide a molecular and cellular
biology foundation for bioinformatics students, especially those with
non biology backgrounds. It will also provide an opportunity to polish
verbal presentation skills. The course will cover advanced topics in
biochemistry, cellular biology, molecular biology and genomics, based on
the foundations of Molecular Cell Biology for Bioinformatics. Continued
background for bioinformatics research. May include reviews of Molecular
Cell Biology for Bioinformatics.
BINF 831 Structural Genomics Project (3:3:0). Prerequisites: BINF 731.
This is a project-based course, in which students work under the supervision
of the instructor on solving the real-world problems in structural genomics.
The course is designed to mimic a full cycle of the research enterprise: from
developing and defending a proposal to peer reviewed publication. Most
projects will involve applications of various knowledge based methods to
the large scale protein structure analysis.
BINF 841 Research Topics in Biomolecular Simulations (3:3:0).
Prerequisites: BINF 741 or good knowledge of one of the programmic
languages and protein molecular structure and properties. This course,
which is a sequel to BINF 741, is designed for students who are interested
in computer simulations of biomolecules. The goal is to introduce students
to cutting-edge research work in computer simulations on the basis of
individual research projects. Each of the projects represents a small novel
problem, which offers the potential for new original results. To maximize
the productive participation of students in their research, the course
emphasizes individual work with the instructor. Suggested research topics
include a wide range of problems in the area of protein structure dynamics,
folding and unfolding, docking, and aggregation. Students may also select
several computational approaches, from molecular dynamics to Langevin
dynamics or Monte Carlo simulations.
BINF 996 Doctoral Reading and Research (1-12:0:0). Prerequisites:
Admission to doctoral program and permission of instructor. Reading and
research on a specific topic in bioinformatics
under the direction of a faculty member. May be repeated as needed.
BINF 998 Doctoral Dissertation Proposal (1-12:0:0). Prerequisite:
Permission of advisor. Covers development of a research proposal, which
forms the basis for a doctoral dissertation, under the guidance of a
dissertation director and the doctoral committee. May be repeated.
BINF 999 Doctoral Dissertation (1-12:0:0). Prerequisite: Admission to
doctoral candidacy. Doctoral dissertation research under the direction
of the dissertation director. May be repeated as needed; however, no
more than a total of 24 credits in BINF 998 and 999 may be applied
toward satisfying doctoral degree requirements.