2021 LBRN Virtual Summer Research Program

Summer Training Opportunities for undergraduate & graduate students, faculty, and staff from Louisiana Academic Institutions
Starting JUNE 16

2021 Virtual LBRN Summer REU Complete v2

LBRN is pleased to sponsor and make available our 2021 Virtual Summer Program Opportunities for undergraduate and graduate students, faculty, and staff from institutions across Louisiana. The Online Program includes access to mentor-guided training, asynchronous coursework and research support. The deadline for registration is June 16, 2021. The program begins on June 21, 2021. Applications will be reviewed on a first-come basis immediately after the deadline. All these courses are free for undergraduate, graduate students, faculty, and staff from institutions across Louisiana.

Owing to scheduling logistics "Omic Logic" is the only course that can be taken as a combination with one of the other * programs.

Sponsored Resources for Louisiana Biomedical Research Network

Online Bioinformatics Resources for Learning & Research

T-Bio Info Server
Logical Pipelines for Big Data
Machine Learning
Application to Biomedical Data
Multi-omics Data
Analysis and Integration of X-omics
Structural Biology
Linking sequence and structure

LBRN Summer Computational Biology & Data Science Training 

Omics Logic Introduction to Bioinformatics 

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OmicsLogic Bioinformatics - 3 months asynchronous subscription to bioinformatics training

Learn about the impact of the genomic revolution, next-generation sequencing - and computational technologies in every area of life sciences: Including - research, biomedical, biotechnology, and agrobiology. 

This program is best suited for students interested to learn about various -omics technologies and how bioinformatics is used in biotechnology, healthcare, agriculture, and basic research. Program access provides access to all the asynchronous* online courses (basic course certificates only):

  • Asynchronous access to Omics Logic coursework for self-guided study (Omicslogic Learn & Code)
  • An introduction to bioinformatics for beginners: Bytes and Molecules
  • Overview of 6 key areas: 1) Bioinformatics, 2) Genomics, 3) Transcriptomics, 4) Epigenomics, 5) Metagenomics, and 6) Data Science: Using R & Python (Code playground)
  • Example datasets and tutorials for hands-on analysis 
  • Self-paced research projects to apply Omics data  in oncology, neuroscience, infectious diseases, and agriculture using bioinformatics & data Science tools  

    In this program, you will be able to learn about the application of bioinformatics in various areas of research and then how can you start doing it yourself that is to apply NGS applications for the identification of germline and somatic pathogenic variants, measurement of gene expression, detection of methylation patterns on DNA and even studies of microbial communities on human skin, in the gut, lungs, and other organs.  This online program is designed for everyone including students who don't have a background in Bioinformatics. The hands-on learning experience is enabled by our AI-guided T-bio platform that allows for the processing and analytics of BIG data on various NGS data types, Mass-Spectroscopy, Structural Biology, and Machine Learning. This 3-month self-paced program includes Instructor support, tracking of progress, access to all resources and materials online for self-paced learning, access to expert guidance and problem-solving, and access and training to use the T-Bio info platform.

NOTE: For Louisiana university students/faculty, the programs will be fully paid for through LBRN scholarships (a limited number is available). For others, the programs are available through Pine Biotech direct subscription charges. To register through lBRN, visit: https://lbrn.lsu.edu/virtual-summer-research-program.html

To register with Pine Biotech, submit the form at the end of this page.

SARS-COV-2 Genomics Data Analysis & Tracking of Variants of Concern (VOCs)

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COVID-19 Genomics: 1 month

In this program, we will learn about the way the SARS-COV-2 pandemic has transformed our appreciation of genomics and bioinformatics. understand how genomic data analysis tools can help identify specific viral strains, understand multiple sequence alignment, phylogenetic analysis, and the significance of mutations in the context of viral protein structure and function. We will further discuss the viral genomes of Covid-19, genes, proteins, and the virology of the disease. We will discuss how the data and the various analysis tools can help in the detection of viral genomes, compare and distinguish between viral strains, identify the impact of mutations on the functionality of viral proteins, and discuss virology from the standpoint of data. 

  • Using online repositories like NCBI and GISAID
  • Phylogeny and evolution - origins and zoonotic transmission
  • Genomic analysis and Variant Analysis
  • Tracking and reporting variants of concern


Bioinformatics for Infectious Diseases

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Bioinformatics for Infectious Diseases: 3 months

This program is dedicated to the study of viral diversity and its role in epidemic infectious diseases that keep re-emerging, including zoonotic spillover, transmission between humans, and the process of viral and bacterial disease development. Participants will get a chance to learn about bioinformatics and analyze genomic data by applying various analysis approaches to study viral, bacterial, and parasite genomes. As a result, you will learn to understand relationships between viral strains and haplotypes, find differences in sequence data, and see the implications for drug and vaccine design. This program will provide opportunities to practice analyzing data to gain hands-on experience with curated datasets from public domain collections, guided by experts with bioinformatics experience and knowledge about virology. 

  • Genomics of Viral, Bacterial and Parasite infectious diseases
  • Structure and Function - using UCSF Chimera to visualize conservation, chemical properties, and functional domains
  • B-cell and T-cell repertoire analysis using online analysis tools
  • Transcriptomic Data Analysis (RNA-Seq) for Immunology: host response to infection
  • Bulk and Single Cell Transcriptomics Analysis

Omicslogic Data Science

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Data Science for Biomedical Data: 1 month

The rapid growth of high-throughput data, including -omics technologies, gave rise to significant demand for data science skills and experience with bioinformatics methods of analysis. To help introduce biologists, clinicians, and students to cutting-edge bioinformatics methods and commonly used data science concepts, our team designed an online bioinformatics training program called OmicsLogic. This online summer program is designed for Data science beginners students interested in data-driven research questions. 

The program will include aspects of data science, such as data wrangling, visualization, statistical analysis, and machine learning. The methods will be reviewed in the context of biomedical and other scientific problems students will study during this 2-weeks intensive Training program. 

  • Big data challenges, HPC and cloud computing
  • NGS: omics data types and use cases
  • Processing data using computational pipelines
  • Introduction to Programming: R and Python
    • Data visualization
    • Statistical Analysis
    • Machine Learning
    • Annotation using databases

Research Support: Omics Logic Research FELLOWSHIP 

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Research Fellowship (3-months)

In Silico research: Develop a research study/Project using bioinformatics:

The research fellowship program is designed to provide support and guidance on the development of an independent research project within a given timeframe (3-6 months). During this time, participants meet on a weekly basis to share their progress and get feedback from the program coordinators. They can also request one-on-one sessions with a mentor on a weekly basis or meet in smaller focus groups.

The Bioinformatics fellowship is a structured program that guides students through various areas of Big Data Bioinformatics Research using practical examples. During this program, we go through several high-quality research publications and learn about applications of computational biology in projects these publications describe. This kind of experience allows beginners to try computational biology techniques on public domain data, making it possible to work with large files and extract meaningful information from patient samples, animal models, cell lines, and microbiota. The program provides support and mentorship, therefore it is an intensive research program involving training tasks, access to our online sessions, and a guide on the implementation of learned skills to proposed research ideas. 


Introduction to bioinformatics theory, methodology, and applications:

  • cloud tools for big data processing
  • Introductory coursework
  • NGS data types: Genomics, Transcriptomics, Metagenomics, Epigenomics


Independent project topic selection through literature review:

  • Research Proposal (Project Title, Project Description, Reference Publication & Datasets), 
  • Experimental design: Pipelines & Algorithms, Data Processing, and normalization. 


Practical coursework and exemplar projects in cancer, neuroscience, agriculture, biotechnology, and infectious diseases:

  • Processing, analysis, and integration methods
  • Reproducibility of research findings
  • Extracting meaningful insights from large datasets
  • Controlled and “real-world” experiments and data sources

Comprehension & Analysis

Exploratory analysis of a focused set of publicly available datasets to identify major trends and patterns for investigation:

  • Overview of project meta-data, practice of analytical tests
  • Processing of data for analysis
  • Design of a statistical metric for inference
  • Analysis review and internal presentation


In-depth review and practice of analytical methods, best data science practices and algorithms applied to data type of choice

  • Exploratory data analysis
  • Data-driven research hypothesis
  • Statistical testing and inference
  • Unsupervised and supervised Machine Learning

Writing, Editing, and preparing the Project for submission

Preparing the project report for an external audience:

  • Background, significance, methodology and results
  • Discussion of project findings and limitations
  • Comparison to other research

The Research Fellowship program is designed for those interested in the intersection of data and biology for a research project. Most research fellows come from a life science background and learn to use bioinformatics tools in the first month of the program. Program length can be 3-6 months and follows a well-defined structure with mentor guidance completely done online via ZOOM in individual and group settings. 


Outcome 1: Understanding of challenges associated with bioinformatics

Even if the research fellow does not complete the program with a project, they will get to experience what a research activity is like, how it is different from training, and what are the challenges with independent research.

Outcome 2: Training and Skill Development

Another possible outcome is to get familiar with analytical methods and approaches, including some level of hands-on experience. As a result of completing such training, students get a certificate of participation and course completion that reflects the skills they have learned and mastered.

Outcome 3: Independent or Group Research Project

A typical outcome is to get a project completed independently or as a group and present it to a group of fellows in our sessions. This can also be adapted to a science fair, conference poster, or class presentation.

Outcome 4: Poster presentation or Research Publication

For a competitive project, the next step is to submit the manuscript to a journal. That still does not guarantee acceptance - for example, many manuscripts take years to revise, edit and complete before passing peer-review. However, there are many journals that accept research projects developed by novices, high school students, and undergraduates. 

Registration is on a rolling schedule. 

For any additional questions, you can view previous research project submissions and outcomes on this :https://learn.omicslogic.com/blog/post/research-fellowship-with-pine-biotech-independent-research-projects-using-bioinformatics

NOTE: For Louisiana university students/faculty, the programs will be fully paid for through LBRN scholarships (a limited number is available). For others, the programs are available through Pine Biotech direct subscription charges. To register through lBRN, visit: https://lbrn.lsu.edu/virtual-summer-research-program.html

LBRN scholarships

To register with Pine Biotech, submit the form at the end of this page.


Register for the program of your preference

LBRN Program Interest: The 2021 LBRN Virtual Research Summer Program will be available to students & researchers outside the partner university. if you are interested in the upcoming summer programs, please fill up the form and we will share with you the registration details and the schedule of the program that you are interested in. Email us for any other questions at marketing@pine.bio for any NGS research related query email support@pine.bio.