Online Graduate Certificate in Applied Bioinformatics
Important notice (April 2019)
The certificate program will only run until 2020!
Students must complete all course requirements by the end of the Spring 2020 semester.
- Summer 2019: BMMB 554: Foundations in Life Sciences
- Fall 2019: STAT 555 Statistical Analysis in Life Sciences
- Spring 2020: BMMB 852 Applied Bioinformatics
- Spring 2020: BMMB 551 Genomics
We do not accept new students in the program. Existing students must ensure that they register and take all the courses to qualify for the certificate.
I currently serve as the Program Director for the Online Graduate Certificate
in Applied Bioinformatics offered by the Penn State World Campus.
This page collects common answers to questions submitted by applicants and current students.
If you have a question not answered here or need more information on the program
Email is the preferred mode of communication.
Please note that the academic staff are not knowledgeable about technical
problems that may occur while using World Campus Resources.
The speediest responses regarding technical problems, course registration and other administrative
issues may be obtained by contacting
firstname.lastname@example.org or other resources on
the PSU World Campus website.
How does online education work?
Penn State World Campus maintains a helpful overview here How
It Works (FAQs). In a nutshell World Campus courses are designed with your
busy schedule in mind, providing the flexibility you need to study at the times
most convenient to you. The majority of the courses are structured for
asynchronous learning to provide maximum flexibility. All course activities,
assignments, and exams, however, must be completed by their respective due
Can PSU resident students obtain the certificate?
Yes. Resident students that have completed the required courses (BMMB 551, BMMB 852,
BMMB 554 and STAT 555) either
online or in residential instruction will qualify for the Certificate. These students
may obtain the certificate by applying to the program then requesting the certificate.
How long does it take to get a certificate?
Currently the shortest time frame to take all four courses is one year.
We will do our best effort to schedule at least one offering of each of the four courses
within a calendar year.
What is the best time to start?
Admissions are ongoing throughout the year. Course enrollment takes place three times a
year according to the Penn State Academic Calendar. The Fall and Spring semesters are 15 weeks long, the Summer semester is
12 weeks long.
Are all courses offered at all times?
No. Courses are offered based on the academic schedule. We offer each course at
least once over the period of one Acdemic Calendar year (three semesters): Fall,
Spring, Summer. Depending on enrollment and instructor availability we may offer
some courses more than once per Academic Calendar but that is determined at
least one year in advance. We recommend that students enroll for courses as soon
We try not to oversubscribe courses but due to the online nature and the
different paths that students take through the program it is possible for a
course to become full in a given semester.
What are the deadlines for applying/enrolling?
Please consult the PSU Academic calendar for the enrollment deadlines. We close enrollment
one week before classes begin.
Is there a list of courses by dates?
- BMMB 551 Genomics: typically offered in the Spring (Jan-May) semester
- BMMB 852 Applied Bioinformatics: typically offered in the Spring (Jan-May) semester
- BMMB 554 Foundations in Life Sciences: typically offered in the Summer (May-Aug) semester
- STAT 555 Statistical Analysis in Life Sciences: typically offered in the (Aug-Dec) semester
What is the cost of the program?
Prices are set by the Penn State World Campus as an institution and not
by the department or the instructors. See the
Certificate in Applied Bioinformatics page.
The total cost is the number of credits × cost for one credit.
Does the program offer financial aid?
The program itself does not directly offer financial aid, but since
the course is offered by an accredited institution students
enrolled in the course may qualify for other financial aid programs.
When/how are acceptance decisions made?
The application process in ongoing and we review the applications about once a month.
If you need more information sooner contact admissions
How to apply to the program?
Visit the Graduate
Certificate in Applied Bioinformatics page
What happens after being accepted into the program?
Upon being accepted into the
BIONC program, students will receive an
Access Account Activation email from the World Campus Helpdesk.
This will provide them with instructions on how to establish their
Penn State email account. Very soon after, the World Campus sends
students a program Welcome Letter that provides them with instructions on
how to register and pay for their first course.
Students will have the
BIONC code added to their record,
but will appear in the University systems as a grad non-degree student.
They will see the program on their transcript upon completion.
How to schedule courses?
After receiving the communications about the acceptance into the program and
following those steps, students can schedule their first course. Students can
schedule courses using the instructions on the World Campus site.
How to troubleshoot problems with the World Campus Services?
The academic staff are not knowledgeable about technical
problems that may occur while using World Campus Resources.
The speediest responses may be obtained via
Is there a short overview of each course that is part of the certificate?
The official source of information can be seen on the course
list as well a the course
Course: BMMB 551, Genomics
Throughout this course we will introduce and/or review the fundamentals of genomics.
You will alos learn about the approaches used to asses function of genomic DNA. As
you acquire this information, you will be asked to apply this information for cutting
edge exploration of functional regions of genomes. Additionally, this course
will serve as a forum to explore new approaches to self-motivation and group
Phase 1: Genome Sequences and Resources
- Fundamentals of genomics
- Sequencing technologies
- Aligning biological sequences
- Genome and transcript assembly
- Resources for comparative genomics: Browsers, Galaxy
Phase 2: Finding biological functions encoded in a genome
- Finding protein-coding genes within genomes
- Finding transcribed regions
- Finding evolutionary signatures of function
- Finding non-coding functional sequences: gene regulation
- Finding function by phenotype
Course: BMMB 852, Applied Bioinformatics
The purpose of this course is to introduce students to the various applications
of high-throughput sequencing including: chip-Seq, RNA-Seq, SNP calling, metagenomics,
de-novo assembly and others. The course material will concentrate on presenting
complete data analysis scenarios for each of these domains of applications and
will introduce students to a wide variety of existing tools and techniques.
We expect that by the end of the course work students will:
- understand common bioinformatics data formats and standards
- become familiar with the practice of analyzing short-read sequencing data from
- develop a computationally oriented thinking that is necessary to take on large-scale
- understand data analysis principles of methodologies such as:
- short read and long read alignments
- interval query and manipulation
- SNP calling and genomic variation detection o genome assembly with open
- metagenomics analyses
- Chip-Seq analysis and peak calling
- filter, extract and combine data with scripting languages
- automate tasks with shell scripts to create reusable data pipelines
- plot and visualize results with R and other packages
Access to a Mac or Linux computer is necessary to perform the homework. We can provide
access to Linux computational resources. Only Mac OSX (Tiger/Leopard) and
Linux operating systems are supported.
Course: BMMB 554, Foundations in Data Driven Life Sciences
This course is designed as a preparation routine for graduate students
in Life Sciences. It has several focus areas including evolution of life
sciences as well as in-depth overview of sequencing technologies and
their applications. A key feature of this course is a set of lectures
intended to draw students’ attention to critical importance of speaking and
writing skills for successful careers in highly competitive biomedical field.
Module 1: History
- History of Genetics
- History of Molecular Biology
- History of Genomics
- The Human Genome Project
Module 2: NGS in-depth:
- Chemistry, Molecular Biology and Applications
- Illumina: Chemistry and Molecular Biology
- Illumina: Realities of the data
- Sequencing by ligation
- Non-optical sequencing
- Single Molecule Sequencing
- ddPCR, and a bit on optical mapping
Module 3: Biology with NGS:
- Re-sequencing: Basic Ideas
- Re-sequencing: GWAS
- Transcriptomics: Chemistry, Molecular Biology, Algorithmics, and Applications
- Ribosomal Footprinting and transcoding
- RNA structure analysis
- Analysis of spacial conformation of the genome
- Nucleic Acid/Protein interactions: Chemistry and Molecular Biology
Module 4: Key Skills for Survival
- Oral Presentation
- Writing Grants and Papers
Course: STAT 555, Statistical Analysis of Genomics Data
The course is dedicated to statistical and computational methods for the design and
The course has no pre-requisites, but some computational skills and/or familiarity with
bioinformatics and/or cell biology will help.
Topics (with approximate number of lectures):
- Introduction to R and RStudio (2)
- Introduction to cell biology. (2)
- Introduction to measurement technologies: microarrays, sequencing, SNPs and ChIP.
- Basic statistics (2)
Gene Expression Microarrays: experimental designs, preprocessing and normalization,
RNA-seq: experimental designs, preprocessing and normalization, differential
Replication and pooling (1)
Gene Set enrichment analysis (2)
Clustering samples and genes (3)
Classifying samples using statistical machine learning (3)
Dimension reduction (2)
Combining data from multiple platforms (3)
Selected topics such as gene networks, time course experiments