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. Department of Biomedical Informatics and Data Science (DBIDS) faculty provide mentoring and research opportunities for students interested in bioinformatics.
The Bioinformatics Track is a collaborative effort between the Department of Biomedical Informatics and Data Science and Ph.D. students within the Department of Biomedical Engineering. Students will have their dissertation research and most of their elective coursework focused on bioinformatics. Elective bioinformatics courses include Algorithms in Bioinformatics, Biological Data Management, and Next-Generation Sequencing Data Analysis.
Admissions and Application
Applications for Fall 2024 will open around August 2024. Applications are not accepted for spring or summer terms.
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
Master of Science in Multidisciplinary Biomedical Science
Bioinformatics is offered as one of the five concentration options within the Master of Science in Multidisciplinary Biomedical Science (MSMBS) Program. This program is targeted at students or employees who wish to improve their career success in biomedical sciences. Thesis and non-thesis options are available and students may start during any semester.
Application and Admissions
Application Deadlines
Fall: August 1
Spring: December 1
Summer: April 15
Click here for admissions and application requirements
Curriculum
Thesis (Plan I)
Students completing this plan must take 45 credit hours and complete a research project. To earn the Bioinformatics concentration, 9 out of 15 elective credit hours must be bioinformatics electives (INFO 601, 602, 603, 604 and 662).
Non-thesis (Plan II)
Students completing this plan must take 30 credit hours. To earn the Bioinformatics concentration, 9 out of 12 elective credit hours must be bioinformatics electives (INFO 601, 602, 603, 604 and 662).
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
Students may also obtain this degree through the Accelerated Bachelor's/Master's Program (ABM).
Graduate Informatics Courses
If you have questions about graduate opportunities in Bioinformatics contact Dr. Jake Chen, Director of Bioinformatic Graduate Program.
Below is a listing of graduate-level informatics courses.
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Remedial Courses for Bioinformatics Majors
INFO 501: Biomedical Informatics Research
3 hoursThis 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 hoursThis 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
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Core Courses for Bioinformatics Majors
INFO 601/701: Introduction to Bioinformatics
3 hoursIntroduction 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 hoursThis 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 hoursThe 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 hoursThe introduction of next-generation sequencing (NGS) technologies and the various new genomics applications. The basic analysis begins with NGS data representations using FASTQ, BAM, and VCF files. Major NGS applications characterizing 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 621Students 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 790Students 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 further 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, the 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 hourFor master’s students 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 hourFor master’s students 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 hoursStudents 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 hoursAdmission to the 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 hoursAdmission to the bioinformatics master’s program (Plan A: “Thesis Option”) is required.
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Core Course for Bioinformatics Majors-Ph.D. Only
INFO 794: Advanced Bioinformatics Journal Club
2 hoursStudents 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 hoursAdmission to candidacy is required
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Informatics Elective Courses
INFO 671: Clinical Informatics Seminar I
1 hourFor master’s students 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 hourFor master’s students 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-VTQThis course exposes students to cutting-edge research in 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 a discussion of historical context of the work, a comparison with similar papers, and a critique of the science presented.
Prerequisites: INFO 671 [Min Grade: C]
INFO 612/712: Visual Analytics for Biomedical Research
3 hoursIn 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 the representation of different data types, concentrating on those generated by data-rich platforms such as next-generation sequencing applications, cytometry, and proteomics. We 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 hoursThe 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 662Students 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 hoursTopics 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 hoursIndependent 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.
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Fall 2024
INFO 601: Introduction to Bioinformatics
CRN: 62026
Min CR: 3
Schedule Type: Lecture Online
Instructor: Zechen ChongPrerequisites
Graduate level INFO 510 Minimum Grade of C
Description
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 662: Biomed Appl Nat Lang Processing
CRN: 62037
Min CR: 3
Schedule Type: Lecture Online
Instructor: John D OsborneDescription
Students will be introduced to Natural Language Processing (NLP) including core linguistic tasks such as tokenization, lemmatization/stemming, POS tagging, parsing and chunking. Applications will focus on Deep Learning methods using pytorch with a focus in information extraction including Named Entity Recognition, semantic role labeling, word sense disambiguation, normalization, summarization, question answering and text classification. Applications and data will have a biomedical focus, but no biology or medical background is required.
INFO 662: Biomed Appl Nat Lang Processing
CRN: 67415
Min CR: 3
Schedule Type: Lecture Online
Instructor: John D OsborneDescription
Students will be introduced to Natural Language Processing (NLP) including core linguistic tasks such as tokenization, lemmatization/stemming, POS tagging, parsing and chunking. Applications will focus on Deep Learning methods using pytorch with a focus in information extraction including Named Entity Recognition, semantic role labeling, word sense disambiguation, normalization, summarization, question answering and text classification. Applications and data will have a biomedical focus, but no biology or medical background is required.
INFO 673: Clinical Informatics Journal Club
CRN: 62070
Min CR: 0
Max CR: 1
Schedule Type: Lecture
Instructor: James CiminoDescription
Students will learn how to read, present, and critique primary research publications in clinical informatics. 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 691: Bioinformatics Seminar I
CRN: 64963
Min CR: 1
Schedule Type: Lecture Seminar
Instructor: Amy WangPrerequisites
Graduate level INFO 601 Minimum Grade of CDescription
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: Bioinformatics Journal Club
CRN: 64960
Min CR: 2
Schedule Type: Lecture
Instructor: Yanfeng ZhangDescription
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 696: Intro to Biomed Info Research
CRN: 66344
Min CR: 3
Schedule Type: Lecture Online
Instructor: Amy WangDescription
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.
INFO 701: Introduction to Bioinformatics
CRN: 62025
Min CR: 3
Schedule Type: Lecture
Instructor: Zechen ChongDescription
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 762: Biomed Appl Natural Language Processing
CRN: 62056
Min CR: 3
Schedule Type: Lecture
Instructor: John OsborneDescription
Students will be introduced to Natural Language Processing (NLP) including core linguistic tasks such as tokenization, lemmatization/stemming, POS tagging, parsing and chunking. Applications will focus on Deep Learning methods using pytorch with a focus in information extraction including Named Entity Recognition, semantic role labeling, word sense disambiguation, normalization, summarization, question answering and text classification. Applications and data will have a biomedical focus, but no biology or medical background is required.
INFO 773: Clinical Informatics Journal Club
CRN: 63082
Min CR: 1
Schedule Type: Lecture
Instructor: James CiminoDescription
Students will learn how to read, present, and critique research publications in clinical informatics. 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 791: Bioinformatics Seminar I
CRN: 64964
Min CR: 1
Schedule Type: Lecture
Instructor: Amy WangPrerequisites
Graduate level INFO 701 Minimum Grade of CDescription
For doctoral 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 793: Bioinformatics Journal Club
CRN: 64943
Min CR: 2
Schedule Type: Lecture
Instructor: Yanfeng ZhangDescription
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 796: Bioinformatics Journal Club
CRN: 64942
Min CR: 3
Schedule Type: Lecture Online
Instructor: Amy WangDescription
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