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GBS-Genetics, Genomics & Bioinformatics Theme

The Genetics, Genomics & Bioinformatics (GGB) theme of the Graduate Biomedical Science (GBS) Doctoral Program is one of eight interdisciplinary Ph.D. themes. Though students select a theme upon application, flexibility in research and academics is still available in the program with access to faculty and courses across GBS. The program prepares students for independent research careers in experimental and computational disciplines. Students are encouraged to collaborate with graduate students, postdoctoral fellows and faculty during their training and to participate in the biological scientist community at UAB and Hudson Alpha Institute for Biotechnology. Informatics Institute faculty provide mentoring and research opportunities for students interested in bioinformatics. 

Admissions and Application

Applications for Fall 2019 are open 

  • Priority Application Deadline: November 26, 2018 - FREE domestic applications if submitted by this date
  • Final Application Deadline: December 31, 2018

Click here for admissions and application requirements

Training Plan

GGB training incorporates hands-on experience in state-of-the-art molecular techniques to study gene structure, expression, and function in diverse experimental systems.

Click here for GGB training plans


Other Graduate Programs with Informatics Institute Involvement 

School of Nursing

Master of Science in Nursing Informatics

School of Health Professions

Master of Science in Health Informatics

College of Arts and Science-Department of Computer Science

Master of Science in Data Science-Bioinformatics Track 

School of Public Health

Master of Science in Biomedical and Health Sciences-Bioinformatics Track


Graduate Informatics Courses

If you have question about graduate opportunities in Bioinformatics contact Dr. Jake Chen, Director of Bioinformatic Graduate Program.

Below is a listing of graduate level informatics courses.

Remedial Courses for Bioinformatics Majors

INFO 501:Biomedical Informatics Research
3 hours

This course provides an overview of the field of biomedical informatics, including subfields ranging from bioinformatics to public health informatics, from the perspective of research accomplishments and challenges. Each topic will be taken from a historical perspective – where are we now and how did we get here – and then explore the current research directions. There will be an emphasis on underlying concepts, theories, and methods. It is intended for students who are studying applied areas of informatics (including Health Informatics and Nursing Informatics) as well as students who would like to explore the possibility of an informatics research career. Although this course can serve as a survey of the field, it is also intended for students who will pursue research in some area of biomedical informatics. 


INFO 510: Bioinformatics Application Skills
2 hours

This course provides students necessary bioinformatics programming and data skills using Linux, MySQL and R. Linux commands and use of scripting languages will be taught in the context of bioinformatics data processing. Basic and practical database skills will be covered. Basic statistics using R to conduct reproducible research will be taught. Students will learn homology search using BLAST, understand basic next-generation sequencing data processing and analysis pipeline development. The focus will be on practical bioinformatics concepts using scripting/programming applied to data analysis problems

Core Courses for Bioinformatics Majors

INFO 601/701: Introduction to Bioinformatics
3 hours

Introduction to bioinformatics and computational biology, with emphasis on concepts and application of informatics tools to molecular biology. It covers biological sequence analysis, gene prediction, genome annotation, gene expression analysis, protein structure prediction, evolutionary biology and comparative genomics, bioinformatics databases, cloud computing, basic R-based data analysis, simple programming skills using Perl, Linux/Unix environment and command lines, visual analytics, and social/legal aspects of open science. It will have a class research project component.


INFO 602/702: Agorithms in Bioinformatics
3 hours

This course introduces various fundamental algorithms and computational concepts for solving questions in bioinformatics and functional genomics. These include graph algorithms, dynamic programming, combinatorial algorithms, randomized algorithms, pattern matching, classification and clustering algorithms, hidden Markov models and more. Each concept will be introduced in the context of a concrete biological or genomic application. A broad range of topics will be covered, ranging from gene identification, genome reconstruction, microarray data analysis, phylogeny reconstruction, sequence alignments, to variant detection. Pre-requisite is INFO 701 or with instructor permission.

Prerequisites: INFO 601/701 [Min Grade: C]


INFO 603/703: Biological Data Management
3 hours

The introduction of biological data management concepts, theories, and applications. Basic concepts such as relational data representation, relational database modeling, and relational database queries will be introduced in the context of SQL and relational algebra. Advanced concepts including ontology representation and database development workflow will be introduced. Emerging big data concepts and tools, including Hadoop and NoSQL, will be introduced in the context of managing semi-structured and unstructured data. Application of biological data management in biology will be covered using case studies of high-impact widely used biological databases. A class project will be required of all participants. 

Prerequisites: INFO 601/701 [Min Grade: C]


INFO 604/704: Next-generation Sequencing Data Analysis
3 hours

The introduction of next-generation sequencing (NGS) technologies and the various new genomics applications. Basic analysis begins with NGS data representations using FASTQ, BAM, and VCF files. Major NGS applications in the characterization of DNA, RNA, methylation, ChIP, and chromatin structure analysis will be described. Topics will cover alignment, whole genome de novo assembly, variant detection, third generation sequencing technologies, functional genomics, metagenomics, single cell genomics, genetic diseases and cancer genomics. NGS workflows and translational applications in disease biology and genome medicine will also be emphasized. 

Prerequisites:
 INFO 601/701 [Min Grade: C]


INFO 611/711: Intermediate Statistical Analysis I
3 hours
Cross listed to BST 621

Students will gain a thorough understanding of basic analysis methods, elementary concepts, statistical models and applications of probability, commonly used sampling distributions, parametric and non-parametric one and two sample tests, confidence intervals, applications of analysis of two-way contingency table data, simple linear regression, and simple analysis of variance. Students are taught to conduct the relevant analysis using current software such as the Statistical Analysis System (SAS).


INFO 690/790: Data Mining and Statistical Learning
3 hours
Cross listed to NUR 790

Students will learn to discover and implement meaningful insights and knowledge from data. This course covers major concepts and algorithms of data mining. The course will be taught using the SAS Enterprise Miner program. The final project will demonstrate all the data mining techniques covered in the course and furthermore expose students working with real data. At the end of the course students will be proficient in utilizing data mining techniques to exploit data patterns and behavior, gain insider understanding of the data, and produce new knowledge that healthcare decision-makers can act upon. Furthermore, SAS Certified Predictive Modeler certification exam will be offered at the end of the course. Instructor permission is required.


INFO 691/791: Bioinformatics Seminar I       
1 hour

For master’s student only. Students will learn how to prepare, present, and critique research presentations in bioinformatics by attending seminar presentations made by presenters. Seminars are presented by graduate students, faculty, visitors, or online speakers. Students must show evidence of prior preparation, active participation, and documented comprehension of the topics. 

Prerequisites: INFO 601/701 [Min Grade: C]


INFO 692/792: Bioinformatics Seminar II 
1 hour

For master’s student only. Students will learn how to prepare, present, and critique research presentations in bioinformatics by attending seminar presentations made by presenters. Seminars are presented by graduate students, faculty, visitors, or online speakers. Students must show evidence of prior preparation, active participation, and documented comprehension of the topics. 

Prerequisites: INFO 691/791 [Min Grade: C]


INFO 693/793: Bioinformatics Journal Club   
2 hours

Students will learn how to read, present, and critique primary research publications in bioinformatics. Journal club participants will present high-impact recent journal publications selected by course instructors and learn how to read the paper, write critiques, and organize analysis insights into review papers. Students must show evidence of prior preparation prior to journal clubs and write critiques to show comprehension of the topics throughout the semester. 

Prerequisites: INFO 691/791 [Min Grade: C]

Core Course for Bioinformatics Majors-MS Only

INFO 698: Bioinformatics Master’s Projects
1-6 hours

Admission to bioinformatics master’s program (Plan B: “Project Option”) is required. Independent study to conduct bioinformatics research projects, guided by the instructor as the mentor. Permission of instructor and graduate program director is required.


INFO 699: Bioinformatics Master’s Thesis Research
1-6 hours

Admission to bioinformatics master’s program (Plan A: “Thesis Option”) is required.

Core Course for Bioinformatics Majors-Ph.D. Only

INFO 794: Advanced Bioinformatics Journal Club
2 hours

Students will learn how to read, present, and critique primary research publications in bioinformatics. Journal club participants will present high-impact recent journal publications selected by course instructors and learn how to read the paper, write critiques, and organize analysis insights into review papers. Students must show evidence of prior preparation prior to journal clubs and write critiques to show comprehension of the topics throughout the semester. 

Prerequisites: INFO 793 [Min Grade: P]


INFO 799: Bioinformatics Research for Dissertation
1-12 hours

Admission to candidacy is required

Informatics Elective Courses

INFO 671: Clinical Informatics Seminar I 
1 hour

For master’s student only. Students will learn how to prepare, present, and critique research presentations in clinical informatics by attending seminar presentations made by presenters. Seminars are presented by graduate students, faculty, visitors, or online speakers. Students must show evidence of prior preparation, active participation, and documented comprehension of the topics.

Prerequisites: INFO 501 [Min Grade: C]


INFO 672: Clinical Informatics Seminar II  
1 hour

For master’s student only. Students will learn how to prepare, present, and critique research presentations in clinical informatics by attending seminar presentations made by presenters. Seminars are presented by graduate students, faculty, visitors, or online speakers. Students must show evidence of prior preparation, active participation, and documented comprehension of the topics. 

Prerequisites: INFO 671 [Min Grade: C]


INFO 673: Clinical Informatics Journal Club
1 hour
Cross listed to GBSC 700-VTQ

This course exposes students to cutting edge research in the field of clinical informatics, including (but not limited to) clinical information systems, electronic health records, decision support systems, and medical expert systems.  The objective is for the student to understand that informatics is not just a field of solutions to be applied to biomedical problems but that it is a hypothesis-driven endeavor in its own right. Presenters will be expected to discuss papers approved by the instructor, with discussion of historical context of the work, comparison with similar papers, and critique of the science presented.

Prerequisites: INFO 671 [Min Grade: C]


INFO 612/712: Visual Analytics for Biomedical Research
3 hours

In this course, we will explore the use of visualization techniques as a concise and effective way to help understand, interpret and communicate complex biological data. Principles of design, visual rhetoric/communication, and appropriate usage will be introduced. We will cover representation of different data types, concentrating on those generated by data-rich platforms such as next-generation sequencing applications, cytometry, and proteomics, and will discuss the use of visualization techniques applied to assessing data quality and troubleshooting. Various topics including dimension reduction, hierarchical visualizations, unsupervised learning, graph theory, networks/layouts and interactivity will be covered. We will review the algorithmic underpinnings of various methods that lead to their appropriate and effective use. Finally, we will review a variety of genomics/bioinformatics-related visualization tools that are available online, and will explore the use of lower-level approaches (like Matlab or R) to create beautiful and effective visualizations.

Prerequisites: INFO 603/703 [Min Grade: C] or permission of the instructor.


INFO 651/751: Systems Biomedicine of Human Microbiota
3 hours

The human microbiota is the collection of microorganisms (bacteria, archaea, fungi and viruses) that reside within human tissues and biofluids. Such resident microorganisms compose the majority of cells in human bodies and are key contributors to human development, health, and disease. However, most studies focus on genomics and microbiome statistical representations alone, while spatial-temporal analysis, multi-source data integration and modeling are necessary to predict and understand interactions between microorganisms, human hosts, and the environment. This course will highlight state-of-the-art microbiome/microbiota research and provide essential training in mathematical, computational and systems biology to derive integrative and predictive models of microbiota-host interactions in the context of human health and disease.

Prerequisites: INFO 601/701 [Min Grade: C] and MA 560 or BME670 [Min Grade: C] or permission of the instructor.


INFO 662/762: Biomedical Applications of Natural Language Processing
3 hours
Cross listed to CS 662

Students will be introduced to Natural Language Processing (NLP) including core linguistic tasks such as tokenization, lemmatization/stemming, POS tagging, parsing and chunking. Applications covered include Named Entity Recognition, semantic role labeling, word sense disambiguation, normalization, information retrieval, question answering and text classification. Applications and data will have a biomedical focus, but no biology or medical background is required.

Prerequisites: INFO 601/701 [Min Grade: C] or permission of the instructor and programming experience equivalent to CS 303/350/355.


INFO 695/795: Special Topics in Bioinformatics
3 hours

Topics of current research interest, such as metagenomics, microbiome, computational medicine, complex systems, deep learning in biology, artificial intelligence in biomedical, and translational bioinformatics applications. May be repeated as different sections taught by different instructors for credit. Permission of instructor is required.


INFO 798: Bioinformatics Independent Study
1-6 hours

Independent study to conduct bioinformatics research projects, guided by the instructor as the mentor. Permission of instructor and graduate program director is required.

Below is a listing of graduate level informatics courses being offered in the next term. 

Spring 2019

INFO 602/702: Algorithms in Bioinformatics
602 CRN: 42384
702 CRN: 42388 
Min CR: 3
Schedule Type: Lecture
Instructor: Andre Leier (P)

Prerequisites
Graduate level INFO 601/701 with a minimum grade of C or with instructor permission 

Description
This course introduces various fundamental algorithms and computational concepts for solving questions in bioinformatics and functional genomics. These include graph algorithms, dynamic programming, combinatorial algorithms, randomized algorithms, pattern matching, classification and clustering algorithms, hidden Markov models and more. Each concept will be introduced in the context of a concrete biological or genomic application. A broad range of topics will be covered, ranging from gene identification, genome reconstruction, microarray data analysis, phylogeny reconstruction, sequence alignments, to variant detection.


INFO 603/703: Biological Data Management
603 CRN: 42385  
703 CRN: 42389   
Min CR: 3
Schedule Type: Lecture
Instructor: Jake Chen (P)

Prerequisites
Graduate level INFO 601 with a minimum grade of C

Description
The introduction of biological data management concepts, theories, and applications. Basic concepts such as relational data representation, relational database modeling, and relational database queries will be introduced in the context of SQL and relational algebra. Advanced concepts including ontology representation and database development workflow will be introduced. Emerging big data concepts and tools, including Hadoop and NoSQL, will be introduced in the context of managing semi-structured and unstructured data. Application of biological data management in biology will be covered using case studies of high-impact widely used biological databases. A class project will be required of all participants. 


INFO 651/751: Systems Biomedicine of Human Microbiota
651 CRN: 42386
751 CRN: 42534    
Min CR: 3
Schedule Type: Lecture
Instructor: Tatiana Marquez Lago (P)

Prerequisites
Graduate level INFO 601 and one of [MA 560, BME670] with a minimum grade of C or permission of the instructor.

Description
The human microbiota is the collection of microorganisms (bacteria, archaea, fungi and viruses) that reside within human tissues and biofluids. Such resident microorganisms compose the majority of cells in human bodies and are key contributors to human development, health, and disease. However, most studies focus on genomics and microbiome statistical representations alone, while spatial-temporal analysis, multi-source data integration and modeling are necessary to predict and understand interactions between microorganisms, human hosts, and the environment. This course will highlight state-of-the-art microbiome/microbiota research and provide essential training in mathematical, computational and systems biology to derive integrative and predictive models of microbiota-host interactions in the context of human health and disease. 


INFO 692/792: Bioinformatics Seminar II
692 CRN: 42725
792 CRN: 42726 
Min CR: 1
Schedule Type: Lecture
Instructor: Amy Wang (P)

Prerequisites
Graduate level INFO 691/INFO 791 with a minimum grade of C

Description
For master’s student only. Students will learn how to prepare, present, and critique research presentations in bioinformatics by attending seminar presentations made by presenters. Seminars are presented by graduate students, faculty, visitors, or online speakers. Students must show evidence of prior preparation, active participation, and documented comprehension of the topics.


INFO 693/793: Bioinformatics Journal Club
693 CRN: 42329  
793 CRN: 43290
Min CR: 2
Schedule Type: Lecture
Instructor: Jake Chen

Prerequisites
Graduate level INFO 691/INFO 791 with a minimum grade of C        

Description
Students will learn how to read, present, and critique primary research publications in bioinformatics. Journal club participants will present high-impact recent journal publications selected by course instructors and learn how to read the paper, write critiques, and organize analysis insights into review papers. Students must show evidence of prior preparation prior to journal clubs and write critiques to show comprehension of the topics throughout the semester.


INFO 695/795, NNI 630/730: Special Topics in Bioinformatics: Biomedical Informatics Methods I 
INFO 695 CRN: 42387  
INFO 795 CRN: 42391
NNI 630 CRN: 42993
NNI 730 CRN: 43000
Min CR: 3
Schedule Type: Lecture
Instructor: Wayne Liang (P)
Tuesdays 3:00 to 5:30 p.m., THT 144, Vault Conference Room 

Description
Biomedical informatics is the art and science of collecting, representing and analyzing patient and biomedical information and translating insights from the information into better health and new medical discoveries. The spectrum of informatics applications ranges from molecules (bioinformatics) to individuals and populations (clinical and public health informatics). We will examine the scientific field and research methods that form the foundation for biomedical informatics research. The course will include didactics, readings, hands-on tool explorations, and a summative work product. This foundational course is intended for informatics majors and students in allied fields (e.g., health, biological, or computer sciences) who are interested in exploring the field of informatics.

GBS Students: INFO 795 is approved as a GBS Advanced Course.

Click here for course registration