New Year Offer End Date: 30th April 2024
Program
Biological Sequence Analysis using R Programming
Unraveling Nature’s Code: Biological Sequence Analysis with R Programming
Skills you will gain:
About Program:
Aim: The aim of this program is to provide participants with hands-on experience in utilizing R Studio for computational biology and bioinformatics tasks. Participants will gain practical skills in analyzing DNA and protein sequences, constructing phylogenetic trees, conducting differential gene expression analysis, and performing functional annotation using R.
Program Objectives:
- To introduce participants to the fundamentals of R Studio and its applications in computational biology.
- To guide participants in installing and managing requisite libraries for bioinformatics analyses.
- To instruct participants on reading and storing DNA sequences, and applying basic statistical analyses.
- To familiarize participants with techniques for transforming data, finding motifs, and performing advanced statistical analyses on DNA sequences.
- To enable participants to analyze protein properties using R.
- To teach participants Multiple Sequence Alignment (MSA) and phylogenetic tree construction in R.
- To guide participants through the creation of Neighbor-Joining (NJ) trees and understanding bootstrapping in phylogenetic analysis.
- To introduce participants to Bioconductor and its applications in bioinformatics.
- To instruct participants on conducting differential gene expression analysis of RNA sequencing data using R.
- To enable participants to generate heat maps for visualizing gene expression patterns.
- To provide participants with the skills needed for functional annotation of genes using Bioconductor tools.
What you will learn?
Day 1:
- Introduction to R studio
- Installing requisite libraries
- Read and Store DNA sequences
- Transform, Find motif and basic statistics
Day 2:
- Analysing Protein Properties
- MSA with R
- Phylogenetic Tree Construction in R
- NJ tree, Bootstrapping
Day 3:
- Introduction to Bioconductor
- Differential gene expression analysis of RNA seq
- Heat map generation
- Functional annotation
Requirement: The program is meant for participants with moderate level of programming proficiency or
with basic idea of R . Requirement any OS with latest version of R and R studio installed
Fee Plan
INR 1999 /- OR USD 50
Intended For :
- Educational Background: Typically, applicants should have a bachelor’s degree or higher in a relevant field such as biology, bioinformatics, computational biology, genetics, biotechnology, or a related discipline.
- Prerequisites: Some programs may require applicants to have completed specific coursework in molecular biology, genetics, bioinformatics, and/or programming fundamentals to ensure they have a strong foundation in the subject matter.
- Computer Skills: Proficiency in programming languages, particularly R programming, as well as familiarity with bioinformatics software packages commonly used for sequence analysis (e.g., BLAST, ClustalW, Bioconductor) may be necessary to effectively participate in the program.
- Research Experience: Applicants with prior research experience in molecular biology, bioinformatics, or computational biology may be given preference, as they are likely to have a deeper understanding of the concepts and techniques covered in the program.
- Letters of Recommendation: Some programs may require letters of recommendation from professors, supervisors, or professionals who can attest to the applicant’s academic abilities, research experience, and suitability for the program.
- Statement of Purpose: Applicants may need to submit a statement of purpose or personal statement outlining their academic background, research interests, career goals, and reasons for applying to the program.
- Language Proficiency: Proficiency in the language of instruction or communication used in the program may be required, especially if the program is conducted in a language other than the applicant’s native language.
- Application Materials: Applicants may need to submit materials such as transcripts, a resume or curriculum vitae (CV), standardized test scores (if applicable), and/or writing samples, depending on the requirements of the program.
Career Supporting Skills
Bioinformatics Analyst Computational Biologist Research Scientist in Genomics Data Analyst in Life Sciences Biostatistician Bioinformatics Software Developer Genomic Data Scientist Research Associate in Systems Biology Computational Genomics Specialist
Program Outcomes
- Proficient use of R Studio for computational biology and bioinformatics analyses.
- Ability to independently install and manage requisite libraries for bioinformatics tasks.
- Competence in reading, storing, and statistically analyzing DNA sequences.
- Advanced skills in transforming data, identifying motifs, and conducting statistical analyses on DNA sequences.
- Capability to analyze protein properties using R.
- Proficiency in Multiple Sequence Alignment (MSA) and phylogenetic tree construction.
- Understanding of Neighbor-Joining (NJ) tree creation and bootstrapping in phylogenetic analysis.
- Familiarity with Bioconductor and its applications in bioinformatics.
- Skill in conducting differential gene expression analysis of RNA sequencing data.
- Ability to generate heat maps for visualizing gene expression patterns.
- Competence in functional annotation of genes using Bioconductor tools.
