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M.Sc. in Bioinformatics(M.Sc. BI)

Course Duration

4 Semesters
(2 Years)

Eligibility Criteria

The candidate should have passed bachelor’s degree of three years with Bioinformatics or any Life Science subject as one of the cognates / major / optional subjects with 60% of marks in aggregate from any recognized University / Institution or any other qualification recognized as equivalent thereto.


MSc (Bioinformatics) Course at REVA University has been designed to meet the human resources needs of existing and futuristic biotech industries, biotech research organizations and academic institutions. This bioinformatics master’s bridges the interfaces between genomics, computing and healthcare and aims to equip you with the skills to analyses, interpret and use biological data to inform and improve healthcare and health outcomes. At REVA University the Bioinformatics Programme focuses on the practical application of Bioinformatics. Depending on previous BSc degree, candidates are requested to follow supplementary introduction courses.

Students with BSc in Computer Science follow courses in molecular biology and students with BSc in Life Science courses on programming and computer science. The curriculum commences with training in programming, data science and elementary bioinformatics tools aimed at using existing software to collect, analyses and interpret DNA and protein sequence information and moves on to more open challenges. Afterwards students follow Molecular Systems Biology.

The Programme also provide sufficient skills and training on entrepreneurship development in Bioinformatics. The Programme deals with courses on Genomic data science, Programming in R and Python, Biostatistical Analysis, Omics Technologies, Systems Biology, Big Data Analytics, Cloud computing, data mining and artificial intelligence, deep learning, and many other related courses.

Program highlights

  • Equips with understanding and hands-on experience of both computing and biological research practices relating to bioinformatics and functional genomics.
  • Benefit from being taught by industry expert faculties and research scientists at the cutting edge of their field with intensive, hands-on experience in active research during the continuous project learning.
  • Learn computer programming in Python, a language used in many areas of bioinformatics and biological computing.
  • Every semester student should undergo internship to industry for the duration of 1 month.
  • The programme offers online courses by MOOC, Swayam, and Coursera Online Courses, along with short-term certification courses and workshops to enhance skill sets necessary for employability and research
  • Certificate based programs related to the domain of Genomic data science, Drug Discovery
  • Real time industry Visits in every semester
  • Student Development Programs (SDP) are offered at every semester in association with various research organizations and industries like Strands Genomics, Med genome, Bionee, Eurofins etc…

Course Curriculum

01Introduction to Genomic Data Science

02Introduction to R Programmeming

03Programmeming in Python

04Fundamentals of Biostatistics

05Genetic Diseases & Counselling

06Biological Pathways

07Fundamental of Computer & Networking

08Biology of Prokaryotic & Eukaryotic Organisms

09Practical Courses

  • Fundamentals of Genomic Data Science
  • R & Python Programmeming

01Advanced Genomic Data Science

02Big Data Analytics

03Advanced R & Python Programmeming

04Research methodology & IPR

05Web server & Database Development 

06Advanced Web based technology

07Genetics & Epigenetics

08Cloud Based Analytics

09Inter Disciplinary Elective 

10Practical Courses

  • Genome Data Analytics
  • Research methodology & Programmeming

01Artificial Intelligence & Deep learning Techniques

02Integrated Omics

03Computational Drug Discovery

04Clinical & Pharmacogenomics

05Nutrigenomics & Agri genomics


07AI based tool Development

08Open Elective

  • Skill enhancement course
  • Soft Skill Training (Mandatory Course)

09Practical Courses

  • Artificial Intelligence & Omics
  • Computational Drug Discovery

01Industrial Project/ Internship

02MOOC/SWAYAM/ Other -1

03MOOC/SWAYAM/ Other -2

Programme Educational Objectives (PEOs)


Develop and integrate problem-solving skills, including the ability to develop new algorithms and analysis methods of computational techniques and diversified bioinformatics tools for processing data, including statistical, machine learning and data mining techniques


Integrate and manage data from different genomic and proteomic research and develop an insight into scientific methodology, advances in bioinformatics research and related ethical issues


Demonstrate an understanding of biological and computer science concepts of current technology trends as well as future directions and recognize the need and develop the necessary skills for continued professional development.

Programme Outcomes (POs)

PO 1

Science knowledge: Demonstrate of the knowledge of bioinformatics for the solution of complex biological problems to understand the molecular functions of organism.

PO 2

Problem analysis: Bioinformatics can solve some of the biological problems based on the gene identification, protein identification and structure prediction. Drug discovery to predict the exact drug to the disease targets and to produce some solutions on statistical interpretations.

PO 3

Conduct investigations of complex problems: Use research-based knowledge including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PO 4

Modern tool usage: Bioinformatics always uses advanced tools, software’s, or algorithms and to create advanced algorithms for product/process development which in turn benefit the society and lifelong learning.

PO 5

Environment and sustainability: Understand and implement environmentally friendly approaches in Biopharmaceutical industries to support sustainable development.

PO 6

Ethics: Apply ethical principles and commit to professional ethics, responsibilities, and norms in Life Sciences.

PO 7

Individual and teamwork: Function effectively as an individual or team work to demonstrate and understand biological problems and manage projects in multidisciplinary and interdisciplinary research.

PO 8

Communication: Communicate effectively with the engineering community and with society at large. Be able to comprehend and write effective reports documentation. Make effective presentations and give and receive clear instructions.

PO 9

Project management and finance: Demonstrate knowledge and understanding of Bioinformatics algorithms and data management principles and apply these to one’s own work, as a member and leader in a team. Manage projects in multidisciplinary environments.

PO 10

Life-long learning: Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Programme Specific Outcomes

After successful completion of the programme, the graduates shall be able to

  • PSO1An ability to integrate algorithms and statistical methods to understand biological data and necessary concepts of information technology.
  • PSO2 Manage health, medical, and bio-informatics information using best practices in data stewardship; data science and data analytics; and human-centered design and systems.
  • PSO3Learn and utilize scripting languages in genomic data science algorithm development and pipeline design of a wide array of technical research skills.

Career Opportunities

This is a new field; thus, we have no hard data on the follow-up. It is however anticipated that five years after graduation, about one third will still be employed as a scientist at a university or research center. Others will choose for a career at research-oriented pharmaceutical and biotechnological companies.

Examples of positions (not being a PhD position) and companies of graduates of the M.Sc. Bioinformatics program are:

  • Bioinformatician
  • Software developer
  • Data scientist
  • Programmer
  • Computational biologist
  • Bioinformatician (now a career path within academia in its own right)
  • Research technician
  • Research scientist
  • Research assistant

Top Indian recruiters in bioinformatics:-

  • Strand Life Sciences
  • Genotypic Technologies
  • Med Genome
  • Agri Genome
  • Mapmygenome
  • Nucleome
  • Eurofins
  • Biocon
  • Thermofisher Scientific
  • Clever gene
  • Genome Life Sciences
Application Fee
  • Indian / SAARC Nationals₹ 1000
  • NRI Fee₹ 2000
  • Foreign NationalsUS$ 50