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
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.
The RGCB Academic Committee will screen all applications and
potential candidates will be invited for an online interview.
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.
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.
At least one guest lecture per module. Final list of guest
faculties will be published soon.
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
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
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
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.
Module 5: Structural Bioinformatics & Fundamentals of drug
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
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
Monday to Friday
Monday to Friday
9:00 AM to 10:00 AM
9:00 AM to 5:00 PM
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 / 471-2781-236 email@example.com /
Find us here
Rajiv Gandhi Centre for Biotechnology (RGCB), Thycaud Post,
Poojappura, Thiruvananthapuram - 695 014, Kerala, India +91-471-2529400
| 2347975 | 2348753 +91-471-2348096