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

Course Duration

4 Semesters
(2 Years)

Eligibility Criteria

B.Sc. in any field of Life Sciences/ Agricultural Sciences/Bioinformatics/ Computer Science securing at least 60% marks (40 % in the case of candidates belonging to SC/ST) in aggregate of all optional subjects from any recognized University/ Institute or any other qualification recognized as equivalent there to are eligible.

Overview

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

  • Interdisciplinary Science amalgamating Biology, Medicine, Mathematics, Statistics, Computer Science.
  • Guidance from expert academicians and lead researchers in the field of Clinical Research, agriculture, microbiology, and biostatistics.
  • Projects based learning in collaborations with multiple industry partners such as Strand Genomics, Med Genome, Eurofins, ThermoFisher Scientific, Qiagen, etc.
  • Platform to explore the frontiers of bioscience from precision medicine to precision agriculture, and other emerging fields, including molecular ecosystems biology.
  • Opportunity to analyses predominant omics datatypes including next generation sequencing, mass spectrometry, emerging single molecule techniques, genome engineering,
  • imaging, and integrative analysis toolsets.
  • Strong foundation in statistical machine learning to shape career related to the field of information sciences
  • Student exchange programme in collaborations with foreign Universities.
  • Guidance from highly qualified faculty members, industry

Core Modules

  • Advanced Genomic Data Sciences
  • R and Python Programming
  • Biostatistical Analysis
  • Big Data analytics
  • Cloud based analytics in genomics
  • Data Mining and Artificial Intelligence
  • Webservers and Database development
  • Artificial Intelligence and Deep Learning techniques
  • Clinical Genomics
  • Agri-genomics
  • Nutrigenomics
  • AI based tool Development

Course Curriculum

01Introduction to Genomic Data Science

02Introduction to R Programming

03Programming in Python

04Fundamentals of Biostatistics

01Advanced Genomic Data Science

02Big Data Analytics

03Advanced R & Python Programming

04Research methodology & IPR

01Artificial Intelligence & Deep learning Techniques

02Integrated Omics

03Computational Drug Discovery

01Industrial Project/ Internship

02MOOC/SWAYAM/ Other -1

03MOOC/SWAYAM/ Other -2

Programme Educational Objectives (PEOs)

PEO-1

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

PEO-2

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

PEO-3

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

With an emerging focus on biotechnology and the need for products to have a greater societal impact, this program will equip students with the knowledge, skills, experience, and personal attributes to successfully translate biotechnology ideas into new commercial ventures. Skills in these areas are highly sought after by employers due to the unique attribute’s graduates will gain. Job profile includes

  • Genomic Data Scientist
  • Data Analyst
  • Bioinformatician
  • Bioprogrammer
  • Computational Biologist
  • Software developer
  • Bioinformatics Research Scientist
  • Programmer for Database
  • Pharmacogenomist
  • Entrepreneurs

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
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