Course Overview
This one year internship 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. The internship 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.
Selection
The RGCB Academic Committee will screen all applications and potential candidates will be invited for personal interview (or online interview). In case more than 15 candidates are being short-listed after screening of applications, an online test will be conducted before the selection interview.
Program Fee
The total fee amount of 60,000 INR (This may be paid in monthly
installments). Initial installment INR 10,000 should be paid before
commencing the program. 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 computational biology laboratory. It does
not cover your travel and local accommodation.
Accommodation
RGCB
Hostel facility will be limited. Assistance will be provided to find
suitable local accommodation if hostel rooms are not available.
Who should apply?
This
internship course is aimed at people with a background in biological
sciences who have little or no experience in bioinformatics. Applicants
are expected to be at an early stage of their career with an interest to
develop their bioinformatics skills. Essential qualifications include a
first class bachelor’s degree in medical/engineering sciences or a
masters degree in any branch of life science. Previous knowledge of
computer programming is not required for this program.
Application
Submit
your online application at www.rgcb.res.in/cbb/internshipform.php.
Please note, your application will not be considered without a
motivation letter & contact details of a referee.
Course Modules
The curriculum is divided into 12 core bioinformatics modules (Theory +
Practical exercises) plus a 3-month final dissertation. The syllabus
includes
Module 1:
Bioinformatics: The Big Picture, Open challenges, Web-Based &
Command-Line Software culture, Introduction to UNIX environment, Unix
file system; Installing & executing programs in LINUX environment;
Navigating your computer from the shell; Basic command line operations;
Fundamentals of computer programming & Biostatistics – Perl, Python,
R, shell scripting, Database development using MySQL, working with
remote machines. Introduction to common text editors like gedit, nedit,
emacs & vi with special emphasis on vi editor basic commands.
Module 2:
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. Basic programming in Python and
Perl – Introduction to Perl variables (Scalar, Array and Hash) and
Python variables (String, List, Dictionary, Tuple and Set) with examples
& exercises.
Module 3:
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. Basic loops in Perl
& Python; Use of different loops like if, while, if-else,
if-elsif-else, foreach, for and unless loops for simple data structures.
Module 4:
Molecular phylogeny & Evolution –Principles of molecular phylogeny
and evolution; Stages of Phylogenetic Analysis, Distance-Based,
Character based & Model-Based Phylogenetic Inference;Maximum
Likelihood(ML), Bayesian inference methods, PHYLIP, MEGA, Evaluation of
phylogenetic trees; Phylogenetic networks.
Module 5:
Advanced programming in Perl and Python –Complex data structures; Array
of arrays, array of hashes, hash of hashes in Perl and list of lists,
tuples & dictionaries in Python; Use of loops through complex data
structures; Referencing and Dereferencing in Perl;Common useful perl
modules from CPAN; Useful python libraries for Biologists.
Module 6:
Genomics: Next generation sequence analysis – DNA Introduction to DNA
Sequencing Technologies; Overview of Next-Generation Sequencing Data
Analysis: 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; Storing Data in public repositories; Applications of NGS.
Module 7:
Advanced programming in Perl and Python –Complex data structures;
Array of arrays, array of hashes, hash of hashes in Perl and list of
lists, tuples & dictionaries in Python; Use of loops through complex
data structures; Referencing and Dereferencing in Perl;Common useful
perl modules from CPAN; Useful python libraries for Biologists.
Module 8:
Transcriptomics and Proteomics: Next generation sequence analysis – RNA
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.Proteomics: Protein
analysis&prediction–Principles of Protein Structure (Primary,
Secondary & Tertiary), Protein Data Bank (PDB), Protein structure
visualization tools, Protein Domains and Motifs, SCOP & CATH
Database; COG database; Basics of Protein Structure Prediction (Homology
Modeling, Fold Recognition, Ab-Initio Prediction). Proteomic resources;
Fundamentals of molecular docking,Chip-Seq data analysis;
Module 9:
Fundamentals of systems biology (Networks & Pathways) –
Introduction to systems biology;Functional annotation of gene expression
data; Biological data integration (NCBI Biosystems); Bioinformatics
resources for Pathways, Networks, and their Integration: (KEGG,
REACTOME, MetaCyc); Protein-Protein interaction databases,
Reconstruction of signaling pathways.
Module 10:
R package – Introduction to R pacakge; 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, Use of loops,
operators and assignments in R, Generating simple plots on screen or/and
in pdf/png/jpg files (Publication quality figures).
Module 11:
Bioconductor in R; 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 12:
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.
Final dissertation:
Candidate can choose a six-month project from any of the on-going
research at the Computational Biology & Bioinformatics Facility.
Schedule
Morning lecture (9.30 to 10.30 am) followed by hands-on sessions & exercise until 5.00pm.
Exam and Grades
Upon completion of each module, online exams will be conducted. Final
grade will be calculated based on module exams, lab activities (Journal
presentation, assignments, discussion etc) and final project.
Grade –A >80%, Grade – B 70 - 80%, Grade – C 60 - 70%, Grade – D
<60%
For more information on the internship please contact:Prof. Jagadeesh Chandran Office of Academic AffairsProgram Duration: One year, from September 03, 2018 – August 30, 2019 Number of slots: 10 Venue: Bio-Innovation Centre (BIC), Rajiv Gandhi Centre for Biotechnology,Trivandrum. Application opens: July 18 Application deadline: August 14 Contact: bioinfo@rgcb.res.in Course Fee: ₹60,000 (Payable in monthly installments) To download brochure click hereRajiv Gandhi Centre for Biotechnology (RGCB),Trivandrum,Kerala Ph:+91 471-2529655 E-mail : oaa@rgcb.res.in
To Apply Click on--
http://rgcb.res.in/cbb/internshipform.php
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