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Bioinformatics Resources

An explosion of -omics data has lead to increased integration of bioinformatics into many avenues of biological research.  The Department of Microbiology & Immunology does not have sufficient faculty expertise or critical mass to offer courses in these topics, but there are many resources available to interested trainees either on or off campus.  The Education & Training Committee compiled the following resources.  If you are aware of additional resources that could be of benefit to share with our community, please contact our Student Services Specialist Michelle Hightower (michelle_hightower AT med.unc.edu) so we can update this list.

 

UNC Courses & Workshops

UNC Core Facilities

Getting Started with Bioinformatics & Research Computing

Online Bioinformatics Resources

 

UNC COURSES & WORKSHOPS

Curriculum in Bioinformatics and Computational Biology (https://bcb.unc.edu/current-course-schedule/)

NIH BD2K Biomedical Graduate Training Program (http://bd2k.web.unc.edu/about-2/) offers a series of training modules in modeling and large data set analyses, leading to a certificate.

Health Science Library workshops (https://guides.lib.unc.edu/bioinformatics/workshop-descriptions)

UNC CORE FACILITIES

UNC core facilities (https://www.med.unc.edu/corefacilities/) offer services and data analysis tools relevant to their methodologies and can offer advice in applying these tools.  This is a subset of available cores that offer complex data analysis tools:

The UNC Center for Bioinformatics (https://bioinformatics.unc.edu/about/).  Offers computational tools for molecular biology, genetics, biochemistry and biomedical research.  Offers access to data analysis tools, such as Ingenuity Pathway Analysis, Partek Genomics Suite, among others.

Structural Bioinformatics Core (https://www.med.unc.edu/csb/sbi/).  Includes access to various data analysis software: DNA sequence analysis (Muscle, T-Coffee, ClustalX, Seaview, Mega5.2.1), protein fold determination (HHpred, I-Tasser), structure superimposition and comparison (PyMOL), homology modeling (Modeller), active site identification (Discovery Studio, Sybyl), analyzing effects of mutations, docking of drugs (ClusPro, Zdock), and molecular dynamics (AMBER, NAMD, Gromacs).  Other visualization or protein structure analysis software include: SYBYL, Insigtht II, FELIX, QUANTA, spock, VMD, CCP4, AMBER, crystallography or NMR spectroscopy.

Vironomics Core (https://www.med.unc.edu/vironomics/).  Offers a variety of experimental services (including qPCR, DNA sequencing, RNASeq) plus data analysis tailored to fit your research project.

UNC Systems Genetics Core (http://csbio.unc.edu/CCstatus/index.py?run=AvailableLines.information). Tools related to analyzing the mouse genome:

UNC High-Throughput Sequencing Facility (https://www.med.unc.edu/genomics/services/) offers sequencing and analysis services:

UNC Michael Hooker Proteomics Center (https://www.med.unc.edu/proteomics/).  Offers mass spectrometer, protein identification, protein-protein interaction analyses. Data analysis is provided through a variety of database search engines (Mascot, Sequest) and software packages including Protein Pilot, Proteome Discoverer, MaxQuant, Byos, and Scaffold.  The core can also aid in bioinformatics analysis using Ingenuity Pathway Analysis (IPA), David, and Perseus.

The Center for Gastrointestinal Biology and Disease (https://www.med.unc.edu/cgibd/cores/) Offers single cell RNA-sequencing and basic analysis; Biostatistics and Clinical Research services that include assistance with study design.

The Lineberger Biostatistics Core (https://unclineberger.org/biostats/) offers assistance with study design and interpretation.

GETTING STARTED WITH BIOINFORMATICS & RESEARCH COMPUTING

Getting started with UNC research computing

Linux/command line basics

Basics of data science (Python/R)

  • R Open Labs (http://ropenlabs.web.unc.edu). Open labs are (mostly) unstructured workshops designed to help you learn R. Each week brief instruction will be provided, followed by time to practice, work together, ask questions and get help.  Participants can join the lab any time during the session, and are welcome to work on unrelated projects.
  • Datacamp Course Series (http://www.datacamp.com) includes courses (Introduction to R, Introduction to Python) and tracks (Data Analyst with R, Data Scientist with R, Data Analyst with Python, Data Scientist with Python)

ONLINE RESOURCES

Biostars (https://www.biostars.org). Online bioinformatics question and answer forum.  Frequented by professional bioinformaticians and computational biologists.  Crowd-sourced bioinformatics help, practical suggestions, and theory discussions.

SEQanswers (http://seqanswers.com). Similar resource to Biostars, crowd-sourced info typically more focused on next-gen sequencing things.

Stack Overflow (https://stackoverflow.com/questions/). Similar resource to the two above, but for more general computer science, coding, statistics, etc.  If you’re having a computer/tech/math/stats-related problem, chances are it’s already been mentioned and solved on Stack Overflow.

Stack Exchange (https://stackexchange.com/sites). Stack Overflow is part of the Stack Exchange group, which has many different subject specific, crowd-sourced communities like Overflow.  It includes a bioinformatics topic.

NCBI Resources (https://www.ncbi.nlm.nih.gov/home/coursesandwebinars/)  (https://www.ncbi.nlm.nih.gov/home/tutorials/).  Webinars, online courses, videos and tutorials, lots to choose from, often about how to use NCBI-specific services (critical for any biologist).

Data Carpentry (https://datacarpentry.org/lessons/). Detailed lessons and workshops all about data science and coding.  Materials are free to use.

Software Carpentry (https://software-carpentry.org/lessons/). Detailed lessons and workshops all about data science and coding.  Materials are free to use.

MIT OpenCourseWare (https://ocw.mit.edu/index.htm). MIT teaching materials, covering a wide variety of topics, including genomics, biology, bioinformatics and computer science.

Bioconductor/R (https://www.bioconductor.org) R is a popular software choice for bioinformaticians, and Bioconductor is an open-source software development project for all manner of *omic analyses.  There’s a huge variety of tools for multiple fields.  The Support Site, Mailing List and Vignettes for the many Bioconductor packages make excellent resources, including complete step-by-step guides.

Datacamp (https://www.datacamp.com/community/tutorials?tag=r-programming). Tutorials focused on data science and coding.

Free trials to learn coding skills at https://www.codeacademy.com and https://www.udacity.com.