Course Overview

This one year certificate program is a platform for highly motivated students to explore bioinformatics through practical experience. It provides a solid base to the use of bioinformatics by providing theory and hands-on training in methods and resources appropriate to all major fields of biological research. This Program provides best strategies for undertaking bioinformatics analysis, computer programming, statistical analysis, data management and reproducibility. All participants will have close and correct mentoring by RGCB faculty. Special invited lectures will be arranged by distinguished scientists and academicians.

Who should apply?

The Course is aimed at people with a biological science who have little or no experience in bioinformatics. Previous knowledge of computer programming is not required for this program.

Essential qualifications

Bachelor's Degree or Master’s degree in any branch of Life Sciences, Physical Sciences or Medical/Engineering Science. Those awaiting their final results are also eligible to apply.

Selection Procedure

The RGCB Academic Committee will screen all applications and potential candidates will be invited for an online interview.

Program Fee

As per the table of fee structure given above. No certificate will be issued without fulfilment of the curriculum & payment of the total fee. Program fees include admission, study materials, access to internal computational facilities and consumables used in the Bioinformatics Facility. It does not cover your travel and local accommodation.

Accommodation (For Project students)

RGCB Hostel facility will be limited. Assistance will be provided to find suitable local accommodation if hostel rooms are not available.

Application

Submit your online application here. Please note, your application will not be considered without a Statement of Purpose (Why you want to get trained in this specialization?) & resume.

Trainers

RGCB Scientists, Teaching Assistants & Visiting Faculty

Guest Lectures

At least one guest lecture per module.
Final list of guest faculties will be published soon.

Course Modules

The curriculum is divided into 6 core bioinformatics modules. Each module is of 3 credits with 12 hours of theory and 6 hours of practical sessions . The syllabus includes:

Module 1: Fundamentals of Unix and Programming

Introduction to Linux/UNIX environment:Unix file system; Installing & executing programs in LINUX environment; Navigating your computer from the shell; Basic command line operations; Introduction to common text editors like gedit, nedit, emacs & vi with special emphasis on vi editor basic commands. Working with remote machines.

Python Programming: Python variables (String, List, Dictionary, Tuple and Set), Control structures and loops like if, while, if-else, if-elsif-else, foreach, for, and unless loops for simple data structures. Complex data structures, tuples & dictionaries, Use of loops through complex data structures; Useful python libraries for Biologists.

Introduction to R package: Installation in windows/Mac/Linux environment, basic commands to store and print variables; Use of commands like read.table, read.csv, write.table to read/write data in R console. Basic statistics (Mean, standard deviation, correlation coeffiecient and p-value) in R, Generating simple plots on screen or/and in pdf/png/jpg and Publication quality figures.

Module 2: Bioinformatics data resources, Biological sequence analysis, phylogeny

Biological data resources, access & management : Genomes across the tree of life, Major sequencing projects, Major centralized bioinformatics databases to store DNA, RNA & protein sequences. Major resources and services at NCBI, Web based and command-line access to information. Navigating through major resources and services at NCBI; Overview of major web resources for the study of genomes: Enseml, NCBI-Genome and UCSC genome browser.

Biological sequence analysis : Homology, Similarity & Identity, Scoring matrices, EMBOSS tools, NCBI blast programs, Evaluation of significance of results using E-value and Bit score, Profile searches, HMMER, Sequence alignment programs. Different approaches to perform Multiple Sequence Alignment, Best strategies to perform pairwise and multiple sequence alignment. Multiple sequence alignment of genomic regions. Databases of Multiple sequence alignment.

Molecular phylogeny & Evolution : Principles of molecular phylogeny and evolution; Stages of Phylogenetic Analysis, Distance-Based, Character based & Model-Based Phylogenetic Inference; Model based phylogenetic inference (ML), Bayesian inference methods, PHYLIP, MEGA, Evaluation of phylogenetic trees, Phylogenetic networks;

Module 3: : Introduction to Next Generation Sequence Analysis

Introduction to DNA Sequencing Technologies: From Generating Sequence Data to FASTQ; Quality control; Different genome assembly programs; Multiple read alignment software programs; The SAM format & SAMtools; Variant calling, VCF format & VCF tools; Interpreting variants; Visualizing & Tabulating NGS data; The GATK Genome analysis suite. Analysis of Human genome using GATK. Storing Data in public repositories; Applications of NGS.

Genome analysis: : Completed genomes: Viruses, Bacteria, Archaea & Eukaryotes; Comparison of prokaryotic genomes; Plant genomes; Major genome analysis projects; ENCODE project; Finding Genes in Eukaryotic Genomes; Human Genome project; A Bioinformatics perspective on Human Disease.

Module 4: Transcriptomics and proteomics

Introduction to Microarrays and RNA-Seq: Data acquisition & Analysis. Microarray data analysis with NCBI-GEO2R/Bioconductor; RNA-Seq analysis using TopHat and Cuffflinks, Functional annotation of microarray/Rna-seq data.

Bioconductor in R: Brief introduction to various Bioconductor packages for NGS; Quality assessment (packages: qrqc, seqbias, ReQON, htSeqTools, TEQC, Rolexa & ShortRead), RNA-seq (packages: DEXSeq, EDASeq, edgeR etc). Alignment (packages: Rsubread & Biostrings), Microbiome (packages: phyloseq, DirichletMultinomial, clstutils, manta & mcaGUI), Work flows (packages: ArrayExpressHTS, Genominator, easyRNASeq, oneChannelGUI & rnaSeqMap), Database (SRAdb).

Module 5: Structural Bioinformatics & Fundamentals of drug discovery

Proteomics: Protein analysis & prediction – Principles of Protein Structure, Overview of structural databases, UniProt database, Protein Data Bank (PDB), Protein structure visualization tools, Protein Domains and Motifs, SCOP & CATH Database; Proteomic resources;

Fundamental of biomolecular structures: Nucleic acids and Proteins, Three-dimensional structure representations and coordinate formats. Calculating solvent accessibility, membrane region and secondary structure:- DSSP/STRIDE/PSIPRED/JPRED, Structure prediction: Homology modeling and Ab-initio modeling:- SWISS-MODEL /I-TASSER2, Ligand binding site prediction and docking:- Vina/Patchdock, Computer-aided drug design.

Module 6: Computational Biochemistry & Computer aided drug design

Computational Biochemistry: Protein Structure, properties and Databses, Introduction toStatistical Thermodynamics, Introduction to Molecular modeling techniques, Molecular Mechanics Force fields, Molecular dynamics Simulations, Medicinal Chemistry and Drug discovery Processes

Computer aided drug design: Introduction to CAAD Methods-Structure and Ligand based drug design, Artificial Intelligence for drug design, Chemiinformatics for Biomedical drug discovery, Quantitative Structure Activity Relationship, Drug Designing approaches to COVID19

Practicals: Protein Structure visualization using chimera,Molecular dynamics Simulations using NAMD/Gromacs, Protein Structure visualization using VMD VMD Tcl Scripting, MD Trajectory Analysis using VMD, Plotting graphs with Gnuplot

Training Schedule

	Part A	Part B
Mode	Online	Offline
Days	Monday to Friday	Monday to Friday
Timings	9:00 AM to 10:00 AM	9:00 AM to 5:00 PM

Exam

Part A: Two online exams (mid term and final exam) will be conducted during Aug and Dec (dates will be announced soon). Final grade will be calculated based on exams, lab activities (assignments, discussion etc).
Part B: Final dissertation project and viva- voce (only for selected candidates based on Part A performance) .

For more details contact:

Office of Academic Affairs,
Rajiv Gandhi Centre for Biotechnology (RGCB),
Thiruvananthapuram, Kerala.
+91 471-2529-653
oaa@rgcb.res.in / bioinfo@rgcb.res.in

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