Collaborative Summer Bioinformatics & Data Science University Partnership Training Program with REVA University- Pine Biotech 2022

According to the National Human Genome Research Institute, it is estimated that within the next decade, scientific research would generate a tremendous amount of biological data that can range anywhere between 2 and 40 exabytes! To extract valuable information from big data, it is important that the students and researchers are equipped with the necessary bioinformatics and computational skills to tap into their full potential. To meet the increasing demand for quality bioinformatics and data science training, REVA University is collaborating with Pine Biotech to upskill the students pursuing their Master’s Degree in Biochemistry. 

A Brief About REVA University And Pine Biotech Collaboration

Located in Bangalore, Karnataka, India the REVA University is a private university established in the year 2004 by Rukmini Educational Charitable Trust. With the best mentors and faculty, REVA University strives for academic excellence by offering modern education of global standards.

In 2016, REVA University had envisioned a future-ready and technology-based learning system for their students that would surpass the traditional teaching-learning methods. When the pandemic hit in 2020 and the landscape of traditional education changed, REVA University was able to transition to 100% online classes and digital examinations that offered future-ready exemplary academic experience. As a part of the drive for tech-based quality education, REVA University in collaboration with Pine Biotech launched the OmicsLogic Bioinformatics And Data Science Summer Training Program that was held online from 11 April 2022 - to 30 April 2022. 

The participants who enrolled in the online training program consisted of students pursuing their Master of Science in Biochemistry from REVA University. They received access to the OmicsLogic Portal which offers a diverse range of comprehensive and up-to-date online courses on topics ranging from genomics, transcriptomics, metagenomics, and epigenomics to single-cell transcriptomics. The portal also offers example projects on oncology, virology, neuroscience, agriculture, and infectious diseases that are sourced from high-impact research publications. For hands-on analytical experience and practice for bioinformatics education, learners also receive access to the AI-guided and user-friendly T-BioInfo platform that combines statistical analysis modules into bioinformatics pipelines. 

To learn more about the collaboration here:  - https://edu.omicslogic.com/reva-university-bangalore 

About University Partnership Training Program

Reva mentors

The university partner program is designed for the university to benefit from the collaborative association with Pine Biotech and partners. This special program is designed by utilizing the best of the resources hosted at learn.omicslogic includes coursework & project-based training for beginner, intermediate, and advanced users helping them achieve the objective of omicslogic data science and bioinformatics research-based training.  The Omics Logic partner university program follows a unique curriculum (propriety to Pine Biotech Inc) designed for personalized training & research experience that enables the participants to develop critical scientific thinking utilizing modern bioinformatics and Data science practices on industry-relevant problems.

Topics and Practical Sessions:

1. Introduction to bioinformatics & understanding the Bytes and Molecules in life sciences
2. Understanding Biomolecular data & Data Analysis in Bioinformatics
3. Introduction to NGS (Genomics, Transcriptomics, Metagenomics), Mapping on genome, transcriptome & database, and overview of NGS project example pipelines.
4. Understanding the different analysis methods and outputs (Table of expression, Mutations & Variants, Operational taxonomic units)
5. Machine Learning - Supervised and unsupervised methods (Clustering, Classification & PCA & H-Clustering)
6. Coding in R & Python for bioinformatics (Loading data, analyzing biological data, and visualization)
7. Big Data Bioinformatics projects (Omics Biological research, Data Science & Drug Discovery, Precision Health, Agriculture and Biotechnology)


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Learn more about our university collaborative training programs here.

 

Outcomes of OmicsLogic Bioinformatics And Data Science Training For REVA University

During the first session of the program, the OmicsLogic team provided an introduction to the faculty/mentors of the program, program structure and expectations, and all the tools and resources that the students receive as a part of the program. The second session introduced the students to the field of genomics and next-generation sequencing data. The topics covered during the session include advantages and applications of NGS in -omics data; various technologies for DNA and RNA sequencing and computational challenges associated with short-read sequencing. The associated online resources for this session consisted of lessons from Course 3 Genomics — Introduction to Genomics and DNA Structure and Variants. The students also received a practical session on genomic variation analysis using NGS data on the T-BioInfo Server. 

Online Training

 

The third session of the program was designed to introduce the students to scripting in R and Python using the OmicsLogic Code Playground. The associated online resources for this session were: Introduction to Bioinformatics Languages (R), Loading data in R, and Loading data in Python. The fourth session provided students with an introduction to metagenomics for studying the microbial community. The topics covered during the session include microbiome function and 16s ribosomal RNA; types of metagenomic analysis, metagenomics data analysis, and metagenomics projects. The associated online resource for the session was the lesson Introduction to Metagenomics

The fifth session was designed to introduce the students to next-generation sequencing transcriptomics and covered topics on mRNA Biology; methods of RNA quantification; mRNA library preparation; Illumina, Microarray, Oxford Nanopore, and PacBio. The associated online resource was the lesson on Introduction to Transcriptomics and a practical session on RNA sequencing analysis on the T-BioInfo server. The program concluded by conducting a final examination for the students, followed by a program review, feedback and joint certification. 

Now, let us also take a look at the statistical outcomes of the courses offered on the OmicsLogic portal. 

 

Fig. 1 - Graph depicting the number of participants who completed the OmicsLogic courses

 

Out of all the OmicsLogic courses offered, the Introduction To Bioinformatics had the highest number of participants (n=61) completing the course. 

Course 1: Introduction To Bioinformatics is an introductory course that covers the topics of big data bioinformatics and its uses in basic research, healthcare, and the biotech and pharmaceutical industries. 

Course 3: Genomics had the second-highest number of participants (n=56) completing the course. The course on Genomics serves as an introduction to the bioinformatics sub-discipline of genomics and covers topics on advanced concepts in genomics; phylogenetic analysis; analysis of VCF files; mutability analysis; differential mutation analysis and copy number variation analysis. 

Followed by this course, the Python Course 1: Getting Started With Bioinformatics had the third-highest number of participants (n=46) completing the course. Python Course 1 is designed for students who are getting started with bioinformatics and want to analyze biological data using Python. The topics covered include loading data, data visualization, DNA replication, and creating reverse complements using Python.  

The number of students completing Course 2: Bytes and Molecules were quite similar to that of Python Course 1: Getting Started With Bioinformatics, achieving the fourth-highest position (n=44). The course is designed to introduce key concepts of molecular biology (molecules) and how they can be studied using data (bytes). 

Course 4: Metagenomics (n-11) and R Coding Course 1: Getting Started With Bioinformatics (n=11) had the same number of participants completing the course, thereby securing the fifth-highest position among other courses. Course 4: Metagenomics is designed to teach students about processing 16s rRNA data and visualizing the abundance tables for diversity and composition. The R Coding Course 1: Getting Started With Bioinformatics introduces the learners to the analysis of biological data using R.

Course 4: Transcriptomics discusses transcriptomic (RNA-Seq) data analysis from basic visualization to statistical analysis of differentially expressed genes. This had the sixth-highest number of participants (n=6) completing the course. The students had also completed the following courses on the OmicsLogic learn portal: R Coding Course 2: Introduction to Data Science (n=4); Course 9: Designing A Bioinformatics Research Project (n=4); Python Course 2: Introduction to Data Science (n=3); Course 7: BioML - Machine Learning For Biomedical Data (n=3); Course 11: Structural Biology and Cheminformatics (n=2); Course 10: Biomolecular Data Analysis (n=2) and Course 8: Epigenomics (n=1).   

 

Fig. 2 - Graph depicting final exam score achieved by the participants

After the training program ended, a final exam in the form of multiple-choice questions was conducted for a duration of 30-minutes. Out of 21 questions, the students were required to answer any 20 questions. Followed by this, students who had a completed user profile were given 10 points. The total score for the final exam was out of 30 points. As seen in Fig.2, the majority of the students (n=38) scored points in the range of 20-30. A moderate number of students (n=23) had also scored points in the range of 10-20. Finally, there was a very low number of students (n=2) scoring points in the range 0-10.  

 

Fig. 3 - Graph depicting OmicsLogic Learn Points achieved by participants

 

As observed in Fig. 3, there were n=7 students achieving OmicsLogic learn points in the range of 0-2000. This was followed by an increase in the number of students (n=16) achieving learn points in the range of 2000-4000. The majority of the students (n=30) had achieved learn points in the range of 4000-6000. There is a significant decrease in the number of students achieving higher points as the range of learning points achieved increases. The number of students achieving learn points in the range of 6000-8000 (n=4) and 8000-10000 (n=4) was the same. One of the highlights of the program was the participant (n=1) who had achieved the learning points in the range of 10000-12000 just by completing the free lessons without the basic subscription. 

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Top 10 Participants From Reva University

  • Bhagavanthi K. Patel achieved 10371 points on her OmicsLogic learn portal earning her the title of the participant who has achieved the highest points. She has completed the courses: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Course 3: Genomics, Course 4: Metagenomics, Course 5: Transcriptomics, Course 7: BioML-Machine Learning for Biomedical Data, Course 9: Designing a Bioinformatics Research Project, Course 10: Biomolecular Data Analysis, Python Course 1: Getting Started with Bioinformatics, Python Course 2: Introduction to Data Science (BioML), R-Coding Course 1: Getting Started with Bioinformatics, and R-Coding Course 2: Introduction to Data Science (BioML). She has also completed the following example projects: Project 02: Ebolavirus: Deadly Mutations and Project 03: TCGA Liver Cancer - Precision Oncology.

    Link to Bhagavanthi learn profile - https://learn.omicslogic.com/user/besmF9lKDRPwg9xTLErBdgHAqVM2  

  • Karthik K. P. achieved 9930 points on the OmicsLogic learn portal thereby becoming the participant who has achieved the second-highest points. He has completed the following courses: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Course 3: Genomics, Course 4: Metagenomics, Course 5: Transcriptomics, Course 7: BioML-Machine Learning for Biomedical Data, Course 9: Designing a Bioinformatics Research Project, Course 10: Biomolecular Data Analysis, Python Course 1: Getting Started with Bioinformatics, Python Course 2: Introduction to Data Science (BioML), R-Coding Course 1: Getting Started with Bioinformatics, R-Coding Course 2: Introduction to Data Science (BioML). He has also completed the following example projects on the learn portal: Project 02: Ebolavirus: Deadly Mutations, and Project 03: TCGA Liver Cancer - Precision Oncology.

    Link to Karthik learn profile - https://learn.omicslogic.com/user/SHT7S7aFhyY7FcIw4mOJwcLCXGC2 

  • Lekhana H achieved 8211 points on the OmicsLogic learn portal thereby coming in the third position. She has completed the following courses on the learn portal: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Course 3: Genomics, Course 4: Metagenomics, Course 5: Transcriptomics, Python Course 1: Getting Started with Bioinformatics, Python Course 2: Introduction to Data Science (BioML), R-Coding Course 1: Getting Started with Bioinformatics, R-Coding Course 2: Introduction to Data Science (BioML) and also an example project on Project 02: Ebolavirus: Deadly Mutations.                                                      
    Link to Lekhana learn profile - https://learn.omicslogic.com/user/qSw9uWcIY0Smw9Kg2M0Cnd2K3IO2 
  • Maria Jamatia achieved the fourth position by gaining 6913 points on the learn portal. She has completed the following courses on the learn portal: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Course 3: Genomics, and Python Course 1: Getting Started with Bioinformatics. She has also completed the following example projects: Project 01: COVID-19 Origin & Pathogenesis of SARS-COV2, Project 02: Ebolavirus: Deadly Mutations, Project 03: TCGA Liver Cancer - Precision Oncology and Project 05: Modeling Cancer Precision Medicine. 

    Link to Maria learn profile - https://learn.omicslogic.com/user/AA5DiXWhHOM9pQ1hj9EYh6M9MNt2 

  • Meghana S achieved 6491 points on the OmicsLogic learn portal thereby coming in the fifth position. She completed the following courses on the learn portal: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Course 3: Genomics, Course 4: Metagenomics, and Python Course 1: Getting Started with Bioinformatics. She also worked on two example projects on Project 02: Ebolavirus: Deadly Mutations and Project 14: Breast Cancer : Oncogene Variant Calling. 

    Link to Meghana learn profile - https://learn.omicslogic.com/user/kLdhbGmFFlYh3XS5C3lFjxEwcjI2 

  • Chandana V achieved 5822 points on the OmicsLogic learn portal thereby coming in the sixth position. She completed courses on: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules; Course 3: Genomics; R-Coding Course 1: Getting Started with Bioinformatics; and Python Course 1: Getting Started with Bioinformatics. She has also completed an example project on Project 02: Ebolavirus: Deadly Mutations.

    Link to her learn profile - https://learn.omicslogic.com/user/ztR4dJOcwtgtrGu5pOezDZqIepI3 

  • Nithya Shree P.V achieved the seventh position by gaining 5653 points on the learn portal. She has completed the following courses on the learn portal: Course 1: Introduction to Bioinformatics; Course 2: Bytes and Molecules; Course 3: Genomics and Python Course 1: Getting Started with Bioinformatics. She has also completed an example project on Project 02: Ebolavirus: Deadly Mutations. 

    Link to Nithya learn profile - https://learn.omicslogic.com/user/1PkULVbf5rNMTpedLHrIwqNwImi1 

  • Anushka K. S achieved 5543 points on the OmicsLogic learn portal thereby coming in the eighth position.  She has completed the following courses on the learn portal: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Course 3: Genomics, and Python Course 1: Getting Started with Bioinformatics. She has also completed an example project on Project 02: Ebolavirus: Deadly Mutations. 

    Link to Anushka learn profile - https://learn.omicslogic.com/user/ptYSkCowR2S4Sq3InDyXfqwhJ6u1 

  • Architha C achieved the ninth position by gaining 5553 points on the learn portal. She has completed the following courses on the learn portal: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Python Course 1: Getting Started with Bioinformatics,  and Course 3: Genomics. 

    Link to Architha learn profile - https://learn.omicslogic.com/user/MPZnOK3ZgWQMQBp9OlYzkBAGc1V2  

  • Joseph Jolly achieved 4367 points on the OmicsLogic learn portal thereby coming in the tenth position.  He has completed the following courses on the learn portal: Course 1: Introduction to Bioinformatics, Course 2: Bytes and Molecules, Course 3: Genomics, and Python Course 1: Getting Started with Bioinformatics.

    Link to Joseph learn profile - https://learn.omicslogic.com/user/Qui3FT8kysX94tqbLafRCnt1khc2  

Link to the above-mentioned bioinformatics and data science courses - 

If you are faculty or from the administration interested in the omicslogic university partnership program for your students, please email us at mohit@pine.bio or elia@pine.bio

 

or Schedule a meeting with an expert.