We aim to provide you with the critical and practical skills necessary for further research as well as transferable skills suited to a wide range of professional contexts.
Our aims to give you a thorough grounding in bioinformatics and equip you with the skills and tools necessary to interpret the wealth of biological data available.

Why study Bioinformatics?

A computer-based approach is now central to biological research. Our program provides essential training for working in this cutting-edge discipline.

Strong reputation

This interdisciplinary, is Research Training Program - including Drug Discovery and Translational Biology, Biotechnology and Systems & Synthetic Biology - offering you an unparalleled choice of courses and opportunities in these areas.

Training in the latest technology

Bioinformatics is fundamentally about the application of computer-based approaches to the understanding of biological processes.
Our program will introduce you to the current methods used to interpret the vast amounts of data generated by modern high-throughput technologies such as:
• genome sequencing
• next-generation sequencing
• microarray profiling

Data processing for the post-genomicera

Bioinformatics operates at the intersection of biology and informatics and has a strong mathematical component.
Today’s technology has given us high-capacity analysis of genes and proteins which make it necessary to integrate informatics when solving biological problems. It has become an important focus for industry, particularly in the post-genomicera.
This program equip you with essential training in computing and statistics and give you valuable hands-on experience of modern bioinformatics research themes and methods.

Progress onto further research

With a working knowledge of the practical and theoretical concepts of bioinformatics, you will be well qualified to progress onto advanced graduate study.
The portfolio of skills developed on the program is also suited to academic research or work within the bioinformatics industry as well as range of commercial settings.


Our program aims to:

• Develop your research skills in authentic bioinformatics-related problems.
• Raise an awareness of unresolved issues and unanswered questions in the area of bioinformatics.
• Improve your career prospects by developing a range of transferable skills such as numeracy, team work and database-interrogating skills.

Learning outcomes

As a graduate from our program you will have gained:

• A clear overview of the theoretical and intellectual basis of modern bioinformatics.
• An appreciation of the roles of computational and experimental research in biology.
• Experience of algorithms, programs and approaches to solving bioinformatics problems.
• The ability to appraise information from disparate sources in relation to scientific hypotheses and communicate your knowledge to the wider public.
• Experience of presenting scholarly work that demonstrates an understanding of the aims, methods and considerations required as well as an ability to form your own conclusions.
• Knowledge of the principles of programming and database science, particularly those applied to biological data.
• an understanding of probabilistic approaches to biological systems.

Learning and Collaborating

Teaching hours
Period 3 hours
Skill level All levels
Time period 7-90 Days
Course materials
Registration form
PDF of the course
  • How you will be taught?
    We employ a wide variety of teaching methods, from lectures to computer practical. Taught element A variety of teaching methods are used including lectures, tutorials and seminars. You will also have the opportunity to participate in computer-based assignments, lab demonstrations and, in some courses, experimental practical.
  • Research project
    The research project is an essential component of our program. This is a substantial piece of full-time, independent research which occupies the final three to four months of the program. You are then expected to submit a written dissertation. A wide range of projects are available and these vary from year to year. The purpose of the project is to give you the opportunity to apply new skills and to acquire first-hand experience of research in a cutting-edge environment.
Bio Re Inventors Offers Bioinformatics training in following fields: Basic Bioinformatics, Biological Databases & Structure, Data Mining, Phylogenetic Analysis & Algorithm, Epitope Mapping, Protein Docking, Live Bioinformatics Project and Advance Perl Programming for Bioinformatics Application development.

7 days Training Modules

Module BRi-701: Sequence Analysis, Basic Bioinformatics
Module BRi-702: Protein Docking
Module BRi-703: Epitope Mapping
Module BRi-704: Basic Bioinformatics, Data Mining

15 days Training Modules

Module BRi -1501: Sequence Analysis, Basic Bioinformatics, Biological Database & Structure
Module BRi -1502: Protein Docking, Epitope Mapping
Module BRi -1503: Data Mining, Phylogenetic Analysis
Module BRi -1504: Phylogenetic Analysis, Epitope Mapping

1 month Training Modules

Module BRi -3001: Sequence Analysis, Basic Bioinformatics, Biological Database & Structure, Data Mining
Module BRi -3002: Data Mining, Phylogenetic Analysis, Epitope Mapping
Module BRi -3003: Phylogenetic Analysis, Epitope Mapping, Protein Docking

2 months Training Modules

Module BRi -2301: Sequence Analysis, Basic Bioinformatics, Biological Database, Data Mining, Phylogenetic Analysis
Module BRi -2302: Data Mining, Phylogenetic Analysis, Epitope Mapping, Protein Docking
Module BRi -2303: Small Live Project**
Module BRi-3301: Live Project**, Protein Docking
Module BRi-3302: Live Project**, Epitope Mapping

Course Module Type Fees(INR)

Module Fees
7 Days 8,000/-
15 Days 10,000/-
One Month 15,000/-
Two Months 20,000/-
Three Months 24,000/-
Well balanced training programs with theoretical insights and hands-on sessions addressing intricacies of NGS data analytics, covering all major NGS applications. The course is covered in multiple modules.

• Introduction to NGS data formats and quality analytics
• De-novo DNA-seq analytics
• De-novo RNA-seq analytics
• DNA re-seq analytics
• RNA re-seq analytics
• smallRNA-seq analytics
• Epigenome-seq (Bisulfite-seq and ChIP-seq) analytics
Drug discovery and development is an intense, lengthy and an interdisciplinary endeavor. Drug discovery is mostly portrayed as a linear, consecutive process that starts with thetarget and leads discovery, followed by lead optimization and pre-clinical in-vitro and in vivo studies to determine if such compounds satisfy a number of pre-set criteria for initiating clinical development. For the pharmaceutical industry, the number of years to bring a drug from discovery to market is approximately 12-14 years and costing up to $1.2 - $1.4 billion dollars.

Protein modeling and rational drug designing are now a popular technique used for increasing the speed of drug designing process. This was made possible by the availability of many protein structures which helped in developing tools to understand the structure-function relationships, automated docking, and virtual screening.The goal is to identify a key drug target based on a thorough understanding of regulatory networks and metabolic pathways and to design a highly specific drug based on the known three-dimensional (3D) structure of that target.
Course covers the topics like mining of genomes of pathogenic organisms for potential targets, prediction of the structure and function of target macromolecules, Ligand and target-based in silico screening for first hits, compound library shaping, design and optimization of lead compounds, prediction of ADMET properties and off-pharmacology, up to selectivity.his course offers a unique blend of modern information technology and pharmaceutical sciences to the students.
Bioinformatics institutes of India offers Genomics & Proteomics It will give a general understanding of the proteome, describe many of the different aspects of proteomics that have been developed recently, identify the technologic limitations related to proteomics. To organize the large amount of information about genomics, proteomics, and bioinformatics and offer basic knowledge of genome sequencing, major differences between prokaryotic and eukaryotic genomes, basic proteomics and its applications, basics in bioinformatics, comparative and evolutionary genomics and applications.
Immunoinformatics is using the basic bioinformatics tools such as ClustalW, BLAST, and Tree View as well as specialized Immunoinformatics tools, such as EpiMatrix, IMGT/V-QUEST for IG and TR sequence analysis. There are also tools which are used for T and B-cell Epitope mapping, proteasomal cleavage site prediction, and TAP– peptide prediction. Immunoinformatics is capable of identifying virulence genes and surface-associated proteins. We describe various information regarding classical immunology, different immunogenic databases, and B-cell and T-cell Epitope prediction tools and software.
Bioperl is a toolkit of Perl modules useful in building bioinformatics solutions in Perl. In India offers BioPerl it can be used to parse sequence data retrieved from local and remote databases, to transform the formats of sequence data and files, to manipulate individual sequences, to search for patterns in sequences, to assist with creating and manipulating sequence alignments, and to search for genes, transposons, and other structures in genomic data.
This course focuses on programming and the development of new software tools to solve biological problems (as opposed to simply using existing tools). Prior programming experience is desirable but not required; on the other hand, students should be prepared to demonstrate a strong commitment towards learning a Programming language.Learning the basics of Python programming: different variables, reading files, writing files, conditional statements. Being able to write a basic Python script from scratch.
The Biopython Project is an international association of developers of non-commercial Python tools for computational molecular biology, as well as bioinformatics.BioPython is one of a number of Bioprojects designed to reduce code duplication.Biopython allows the usage of a number of popular bioinformatics algorithms, through the web or locally. Such approach makes easier both running the algorithm and the extraction of information from its output.The goal of the biojava project is to facilitate rapid application development for bioinformatics.
Protein modeling and rational drug designing are now a popular technique used for increasing the speed of drug designing process. This was made possible by the availability of many protein structures which helped in developing tools to understand the structure-function relationships, automated docking, and virtual screening.
Advanced introduction to systems biology and the quantitative analysis of how cells Work: from gene regulation to complex networks to examples of chemotaxis, kinetic Proofreading, and collective behaviors. the aim will be to develop quantitative toolkits to analyze the complex mechanisms behind the regulation, design, and operation of biological circuits. Computer programming will be done in Matlab, though no prior experience with Matlab is necessary for the course.
This Course will deal with molecular biology. From determining the genetic sequence in a scrap of DNA to creating a 3-D virtual model of a protein, scientists use computer modeling in this field to help us better understand the world far beyond the reaches of the microscope. A study in molecular biology yields vast amounts of data that must be carefully analyzed and interconnected to construct a realistic picture of this world. Computers greatly reduce the manual workload and error associated with thecomplex analysis. In this unit, you will learn how to use computers in order to better understand DNA sequencing, transcriptional regulation, protein structure, and protein interactions. Upon completion of this unit, you should understand each process and be able to create your own models based upon the principles and procedures studied.An advanced course for students specializing in computational biology and bioinformatics for optimization, comparative genomics and phylogenetic, functional genomics (microarray analysis) network reconstruction and data integration.
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