Graduate Classes
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Core Courses
Fall Only
Students will engage in the applications of bioinformatics tools and database searching to better understand DNA and protein structure, function, and evolution. Students will be able to apply their understanding of genetic and evolutionary processes to the appropriate use of bioinformatic web solutions and manipulation of large databases. This course also introduces students to scripting languages for working with biological data.
Spring Only
This course presents an algorithmic focus to problems in computational biology. As such it is built on earlier courses in programming and bioinformatics, advancing students’ proficiency in Python scripting and familiarity with current tools in the field. This course culminates in a project; students develop a software solution to meet a real need in the life sciences.
Spring Only
This course explores recently developed mathematical, probabilistic and statistical methods currently used in the field of bioinformatics. These include random variable and their distributions, parametric and non-parametric tests, linear regression, hidden Markov Models, cross validation techniques, and principal component analysis. Our focus in this course is on the application of these techniques using the R statistical programming language and on meaningful interpretation of results.
Spring Only
Students will present and discuss primary literature and emerging software tools in the field. The course will also include small group projects evaluating different algorithmic approaches to solve current questions in the field. Students will gain hands-on experience with current bioinformatics tools.
Spring Only
The ability to prepare and deliver presentations in bioinformatics is essential for many careers, as well as for study at a higher level. The seminar will cultivate students' presentation skills through participation in and critical discussion of lectures by others on familiar and unfamiliar topics. Students will develop the ability to think critically when introduced to new concepts.
Fall, Spring, & Summer
A supervised placement intended to give students training or work experience in aspects of bioinformatics. Students will acquire practical experience in bioinformatics-related job settings. At the conclusion, students will present (written and oral) the results of their internship.
Fall, Spring, & Summer
Laboratory research under faculty guidance emphasizing hypothesis testing, literature searches, experimental design, and use of appropriate techniques. Students will develop research skills while conducting an independent project.
Fall, Spring, & Summer
Laboratory research under faculty guidance including training in scientific writing and the production of a thesis and research presentation. Students will develop skills in scientific writing and presentation. At the conclusion, students will present (written and oral) the results of their research.
Fall Only
This course focuses on research practices, including data collection and management, the experimental design process, and tools for critical analysis and preparation of scientific literature will be discussed. Students will obtain the background needed to conduct research in their own areas of interest. At the conclusion of the semester, students will develop their thesis proposal.
Fall, Spring, & Summer 2-day course
Loyola University actively promotes a culture of responsible and ethical behaviors among all people associated with the University. This course provides students with a strong foundation of the basic ethical principles and professional standards that can then be built upon by future experiences. Topics include those identified by the US Department of Health & Human Services Office of Research Integrity as critical to research activities as well as those of value to scholars here at Loyola.
Fall Only
Students will explore the concepts of protein structure, protein folding, and structural features in proteins. Students will learn to visualize and analyze experimentally determined protein structures, collect protein-related data from multiple databases, use computer-based programs and online tools to calculate properties of protein surfaces and simulate protein-ligand interactions and ultimately to interpret data in the context for protein structure-based drug design.
Spring, Odd Years Only
Students will learn the concepts of protein identification and homology modeling. Using homology modeling and molecular dynamics simulation tools, students will gain hands-on experience in protein structure prediction and analyzing simulation data.
Biology
Ad Hoc
A comprehensive survey of the molecular biology of the gene. The course will cover contemporary knowledge about gene structure and function primarily in bacteria, including protein synthesis, control of RNA synthesis, DNA structure and replication.
Fall Only
Exploration of next-generation sequencing technologies for assessing microbial diversity in ecological niches. Students will gain hands-on experience with metagenomic methodologies while working in an interdisciplinary, collaborative setting.
Spring Only
This course will introduce the students to the study of genome structure and function and its application to biomedicine, agriculture, and evolution. Students will acquire an in-depth knowledge of the nature of gene and genome structure, function, and evolution as well as the methods used to obtain and evaluate this knowledge.
Spring Only
The nature, diversity, functional ecology, and evolutionary relationship of both prokaryotic and eukaryotic microbes with relationship to higher organisms are discussed. Students will learn the differences between the 3 domains of life and will comprehend the biochemistry, morphology, growth characteristics, structure and ecology of microbes.
Spring Only
Introduction to the molecular mechanisms of disease pathology and therapeutic and control strategies. The experimental basis of the proposed mechanisms will also be examined to demonstrate how basic research is used to address clinical questions and design treatments.
Chemistry
Spring Even Years Only
The major themes in this course will be about topics that are related to plant biochemistry and metabolism. The structure of the course will involve lectures for each topic, with discussion with the students. Students will learn how plants and photosynthetic organisms acquire and process energy. Plant metabolism will constitute a central part of the course, focusing on the main references from other living organisms. A solid understanding of plant metabolism will inspire the student to think about all the possibilities that plant biochemistry and biotechnology offer to solve critical problems, such as malnutrition, global climate change, drug discovery, and infectious diseases.
Spring Only
This course examines how medicinal chemists design and synthesize drug candidates to meet FDA requirements of efficacy and safety, and how a testing strategy measures efficacy vs. toxicity comprising the therapeutic index. Topics include drug-receptor/enzyme binding, PK, ADME, patenting of IP, and the ethical aspects of pharmaceuticals.
Ad Hoc
This course will be about topics related to modern enzymology, with a special emphasis on enzyme kinetics. The structure of the course will involve lectures, intermixed with class discussion. Since this is an advanced course, the instructor may slightly adjust the topics presented to better accommodate class interest and the more suitable pace.
Ad Hoc
This course treats selected topics not normally covered in the department’s regular offerings in biochemistry. (Special Topic offerings must be approved by the Bioinformatics GPD as a Bioinformatics Elective option.)
Computer Science
Fall Only
This course covers the fundamentals of database application development using C++, C, or Java by accessing a transaction-oriented database server. A commercial database environment such as Oracle is used. Additional topics may include enabling access to databases via the web, and administering large databases.
Fall, Spring & Summer
Object-orientation continues to be a dominant approach to software development. This intermediate programming-intensive course studies the use of classes and objects with an emphasis on collaboration among objects
Spring Even Years Only
This course covers theory and practice of the analysis (mining) of extremely large datasets with datasets. With data growing at exponential rates knowledge gathering and exploration techniques are essential for gaining useful intelligence. Students are able to define and critically analyze data mining approaches.
Fall Only
Topics include a wide variety of supervised learning methods, both regression and classification, with and emphasis on those that perform well on large feature sets. Students in this course will learn how to apply sophisticated algorithms to large data sets to make inferences for prediction or decision making.
Spring Only
This course provides an introduction to the field of natural language processing (NLP). NLP is concerned with computational approaches to analyzing, generating, and understanding human language. This course will introduce the students to the problems, methods, and applications of NLP.
Spring Odd Years Only
This course is designed as a modern discussion of distributed computing systems, which represent one of the most important areas in academic and business computing today. Topics covered include distributed computing, interactive services, collaborative computing, and peer-to-peer sharing. Various distributed frameworks and technologies will be explored.
Spring Only
There are over two thousand programming languages. This course studies several languages that represent the much smaller number of underlying principles and paradigms. An understanding of key principles and paradigms underlying the design and implementation of commonly used programming languages; exposure to formal mechanisms for describing language syntax and semantics; programming experience in several representative languages.
Spring Only
The design and analysis of algorithms is central to computer science. This course will focus both on presenting general techniques for designing correct and efficient algorithms, as well as on formal methods for proving the correctness and analyzing the complexity of such algorithms. Also included will be an introduction to the theory of NP-completeness.
Statistics
Ad Hoc
This course will use the R language to solve statistical problems through simulation techniques. Topics covered will include random number generation, bootstrapping, permutation testing, Monte Carlo approaches, Markov Chain Monte Carlo (MCMC) algorithms, and parallel computing.
Ad Hoc
This course treats selected topics not normally covered in the department’s regular offerings in statistics. (Topic offerings must be approved by the Bioinformatics GPD as a Bioinformatics Elective option.)
Spring Only
An introduction to modern-day extensions of simple linear regression and ANOVA to the chi- square test including logistic regression and log-linear modeling techniques based on generalized linear models. Specialized methods for ordinal data, small samples, multi-category data, and matched pairs will also be discussed. The focus throughout this course will be on applications and real-life data sets.
Ad Hoc
This course introduces finite-state Markov processes. Markov chains, classification of states, long-run behavior, continuous time processes such as the Poisson process, birth and death processes, random walks, and Brownian motion. Examples in genetics, population growth, inventory, cash management, and the gambling theory.
Fall Only
This course provides students with a thorough introduction to statistical experimental design and to the statistical methods used to analyze the resulting data. The concepts of comparative experiments, ANOVA and mean separation procedures will be reviewed; blocking (complete and incomplete) will be discussed, as will be factorial designs, fractional factorial designs, and confounding. The course will focus on biometric applications such as clinical trials, HIV studies, and environmental and agricultural research, but industrial and other examples will occasionally be provided to show the breadth of application of experimental design ideas.
Fall Only
This course provides students with a thorough introduction to applied regression methodology. The concept of simple linear regression will be reviewed and discussed using matrices, and multiple linear regression, transformations, diagnostics, polynomial regression, indicator variables, model building and multicolinearity will be discussed, as will be nonlinear and generalized linear regression. The course will focus on applications such as those from biometry and biostatistics, sports, engineering, agriculture and environmental science.