ISCB Education and Training Resources

Our Vision is to see high quality computational biology education and training accessible to all interested communities across the world, and instilled in all life science-related educational programs.

Our Mission is to promote worldwide education and training in computational biology by providing guidance and support for educational resources and community activities.

The information contained within this section covers two general areas:

  1. World-wide educational and training resources for all levels from novices to advanced practitioners of computational biology
  2. Resources that enhance learning and preparation geared towards a career in computational biology

In addition to the content generated by ISCB Education, we also solicit and collect input and information from the larger computational biology community to be made available through these pages.

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The Jackson Laboratory Courses and Workshops

The Genomic Education team at The Jackson Laboratory is committed to creating diverse and inclusive educational programs where all students, employees and visitors feel valued and are empowered to participate in our mission to improve human health though genomics research, scientific resources and education. We believe human diversity is an essential ingredient for empowering the global biomedical community, and therefore our programs should reflect, embrace and celebrate the diversity of our world ... JAX's programs for high school and undergraduate students and teachers predate the founding of the Jackson Laboratory by six years. Including our flagship Summer Student Program, JAX offers opportunities for academic year research, teacher professional development, and the Maine State Science Fair.

Courses are designed to impart knowledge through intensive lectures, hands-on training and informal interactions. Workshops offer extensive hands-on training, teaching participants how to perform specific techniques, interspersed with lectures or seminars.

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This portal allows you to browse our course pages and training materials, to download content of interest and/or to upload course pages and training materials.

NOTE: this page has not been updated for more than 4 months.

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Galaxy Training Materials

This web site is a gateway for lessons, tutorial, and examples of using Galaxy for genomics education and analysis. Among other things, links to tutorials for the following subjects are provided:

Events with Galaxy-related content (includes virtual events)

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Data Carpentry Genomics Workshop

Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This workshop teaches data management and analysis for genomics research including: best practices for organization of bioinformatics projects and data, use of command-line utilities, use of command-line tools to analyze sequence quality and perform variant calling, and connecting to and using cloud computing. This workshop is designed to be taught over two full days of instruction.

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Learn Data Science Online

The skills people and businesses need to succeed are changing. No matter where you are in your career or what field you work in, you will need to understand the language of data. With DataCamp, you learn data science today and apply it tomorrow.

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Data Analytics Bootcamp

What you'll learn

We partnered with industry insiders, so you can learn the skills that employers look for. The curriculum is split into 5 units covering the topics below:

  • Framing structured thinking
  • Analyzing business problems
  • Connecting data using SQL
  • Visualizing data with Python
  • Communicating your analysis

Build industry-level projects

In addition to small projects designed to reinforce specific concepts, you'll complete two capstone projects focused on a realistic data analytics scenario that you can show to future employers.

Work 1:1 with a mentor

Mentor-guided learning not only helps you build skills faster, but also enables career growth.

Get the perfect job with unlimited 1:1 career coaching

Career-focused course material is paired with personal coaching calls to help you land your dream job. You'll have 6 scheduled calls, with unlimited access to more. And full career support continues for 6 months after completing the program.

Is this program right for me?

This data analytics bootcamp is designed for people who demonstrate an aptitude towards critical thinking and problem solving, and have two years of work experience.


  • Strong critical thinking and problem-solving skills
  • 2 years of professional work experience working regularly with office, design or programming tools
  • Fluency in English (written and spoken), as determined by initial interactions with the Admissions team


The full tuition for the program is $6,600. If you pay upfront, you get a 17% discount. Remember, if you don't get a job within 6 months of completion, you'll receive a full refund.

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PSC Bioinformatics Summer Institute Workshop

This two-week intensive training workshop provides a robust background in bioinformatics suitable for teaching and research. Every day participants complete hands-on exercises to practice the concepts learned during lectures using various of the Pittsburgh Supercomputing Center's massively parallel computers and various software tools such as the Galaxy web-based biomedical research tool.

A Typical Summer Institute Schedule

Week 1

  • Introduction to the Computing Environments at the Pittsburgh Supercomputing Center
  • Bioinformatics Databases
  • Models and Significance in Searching Bioinformatics Databases
  • Sequence Alignment Algorithms (NW, SW, Fasta, BLAST, BW+FM, "Seeded" SW)
  • Multiple Sequence Alignment & Mapping Realignment
  • Computational Tools: Analyzing Data Using Relational Databases & SQL
  • Next Generation Sequencing (NGS) Technologies
  • Pattern Identification
  • Preparing NGS Datasets for Assembly/Mapping
  • Phylogenetics and Reconciliation with Notung
  • De Novo Genome Assembly
  • The R System for Statistical Analysis

Week 2

  • Functional Annotation for Assembled Genomes
  • Predicting Genes, Identifying Functions
  • Mapping Genome Assemblies
  • RNAseq: De Novo Assembly of RNA Data
  • Identifying Single-nucleotide Polymorphisms (a.k.a. SNPs) and Other Variants
  • RNAseq: De Novo Functional Annotation and Other Post-Assembly Analyses
  • Gene Annotation
  • Ribosomal Profiling: Genome-wide Measurements of mRNA Translation Rates

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Introduction to Analysis of Epigenetic Data 2020

  • UC Davis Bioinformatics Core
  • UC Davis, CA
  • November 30 - December 4, 2020
  • Workshop web site

This workshop will include a rich collection of lectures and hands-on sessions, covering both theory and tools associated with the analysis of data generated by several common types of epigenetic experiments, primarily data from the Illumina platform. Participants will explore experimental design, cost estimation, data generation, and analysis of DNA sequence data. Participants will explore software and protocols, create and modify workflows, and diagnose/treat problematic data utilizing high performance computing services. Exercises will be performed with provided datasets, using command-line interaction on the Genome Center Compute Cluster, which will be available to you to use for a week after the workshop, so you can continue to practice these skills.

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Advanced Sequencing Technologies & Bioinformatics Analysis

  • CSHL Bioinformatics Workshop
  • Online
  • November 16-20, 2020
  • Application Deadline: September 15, 2020
  • Course web site


  • Obi Griffith, Washington University School of Medicine
  • Malachi Griffith, Washington University School of Medicine
  • Elaine Mardis, Nationwide Children's Hospital Research Institute
  • W. Richard McCombie, Cold Spring Harbor Laboratory
  • Aaron Quinlan, University of Utah

Course Description

Over the last decade, massively parallel DNA sequencing has markedly impacted the practice of modern biology and is being utilized in the practice of medicine. The constant improvement of these platforms means that costs and data generation timelines have been reduced by orders of magnitude, facilitating investigators to conceptualize and perform sequencing-based projects that heretofore were time-, cost-, and sample number-prohibitive. Furthermore, the application of these technologies to answer questions previously not experimentally approachable is broadening their impact and application. However, data analysis remains a complex and often vexing challenge, especially as data volumes increase.

This intensive two week course will explore use and applications of massively parallel sequencing technologies, with a focus on data analysis and bioinformatics. Students will be instructed in the detailed operation of several platforms (Illumina, PacBio, Nanopore, Etc.), including library construction procedures, general data processing, and in-depth data analysis. Students will be introduced to Unix command-line, important file formats, alignment, data visualization, basic scripting in R, bash and other program languages, cluster job submission and bioinformatics pipeline development. A diverse range of the types of biological questions enabled by massively parallel sequencing technologies will be explored such as bulk transcriptome profiling (RNAseq), single-cell transcriptome/proteome profiling (scRNAseq, CITEseq), epigenome profiling (ATAC-seq), small variant discovery and interpretation, structural variant discovery, long read applications, probability and statistics for genomics analysis, and others that are tailored to the student's research areas of interest.

Cloud-based computing will also be explored. Guest lecturers will highlight unique applications of these disruptive technologies.

We encourage applicants from a diversity of scientific backgrounds including molecular evolution, development, neuroscience, medicine, cancer, plant biology and microbiology.

Support & Stipends

Major support provided by: National Human Genome Research Institute.

Access to cloud computational resources may be supported by an AWS in Education Grant award from Amazon.

Stipends are available to offset tuition costs as follows:

  • US applicants (National Human Genome Research Institute).
  • Interdisciplinary Fellowships (transitioning from outside biology) & Scholarships (transitioning from other biological disciplines) (Helmsley Charitable Trust).
  • International applicants (Howard Hughes Medical Institute).

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Bioinformatics: Command Line/R Prerequisites 2020

This workshop will cover the basic computational and statistical concepts needed before performing bioinformatics analysis:

  • Access to a multi-core (24 cpu or greater), "high" memory 64Gb or greater Linux server.
  • Familiarity with the 'command line' and constructing scripts/pipelines.
  • Basic knowledge of how to install software
  • Basic knowledge of R (or equivalent) and statistical programming
  • Basic knowledge of Statistics and model building

The course will include experimental data organization, basic command line and high performance computing concepts, how to install software, use help, run applications, and the basics of building scripts and pipelines. Also covered will be basic R programming, working with data tables and generating figures, basic statistical concepts, and statistical model building. There are no prerequisites for this workshop other than an interest in bioinformatics! The workshop will be on the UC Davis campus, and will run from 9am to 5:00pm each day and include light breakfast, lunch, and snacks.

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Bioinformatics Module I

This lab is the beginning of a 12-week project during which students will clone a gene from the ciliate Tetrahymena thermophila, fuse it to the gene encoding GFP, put the engineered gene back into Tetrahymena, and induce its expression. The gene will be cloned by PCR, so the first step is to design primers to allow the amplification of the desired gene. This lab will take students through the steps to do that, and will also demonstrate the use of other bioinformatics tools.

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Bioinformatics Module II

This lab is the beginning of a 13-week project in which students will engineer a construct to knockout a gene from the ciliate Tetrahymena thermophila. The first step is to identify an appropriate gene homolog in Tetrahymena using the databases. Students will then design primers to amplify the gene by PCR and clone it into a plasmid vector.

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Gene Expression Profiling

In this module, students assess the relative amount of expression of a gene of interest throughout different stages in the Tetrahymena life cycle. The life cycle is complex and involves a number of physiological changes and DNA processing events (see Tetrahymena Facts). Gene expression is evaluated through assessing the relative production of gene transcripts at different time points in the life cycle by reverse transcriptase PCR, yielding an "expression profile". (Estimated time: 5 x 4-hour laboratory periods.)

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GFP Tagging Module

This module was developed by Douglas Chalker, Washington University, MO. Students engineer genetic constructs for the tagging and expression of a Tetrahymena protein of interest. Fluorescence microscopy is used to determine localization of the tagged protein. (Estimated time: 9 x 4 hour laboratory periods.)

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Knockout Construction (KOC) Module

In this module, students engineer genetic constructs to delete individual genes from the Tetrahymena genome. (Estimated time: 10 x 4 hour laboratory periods.)

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The Student / Unpublished Results database (SUPRDB) provides a workspace where researchers can share unpublished experimental results with each other. Many of the results in the database are produced by student researchers, and the results are linked to the Tetrahymena Genome Database to enable sharing of the results with the larger Tetrahymena research community.

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Tetrahymena Genome Database

The Tetrahymena Genome Database (TGD) is a wiki for the Tetrahymena research community. It provides a BLAST service, GBrowse genome browsers, and information on Tetrahymena genes and proteins.

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RNA-Seq Analysis GCAT-SEEK Workshop Manual

Developed by Dr. Mark Peterson, this module provides an overview of the different types of RNA-Seq data analyses. It describes how to assess the quality of RNA-Seq data with FastQC, trim adapters and low quality data with Trimmomatic, read mapping with RSEM, differential expression analysis with DESeq, variant detection with VarScan, and de novo assembly with Trinity.

CourseSource Publication

Peterson, M.P., Malloy, J.T., Buonaccorsi, V.P., and Marden, J.H. 2015. Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching. CourseSource.

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