M.Sc. (Bioinformatics)

Post Graduate Programmes

APPLY NOW 2020 Admissions

Program Code 10003

Course Overview

  • Campus
  • Noida
  • Institute
  • Amity Institute of Biotechnology
  • University
  • Amity University Uttar Pradesh
  • Program Code
  • 10003
  • Eligibility
  • B. Sc in Life Sciences / Computer Science (min 60%) & 10+2 (min 60%). Eligibility will be relaxed by 5% for Sponsored category at 10+2 level.

  • Duration
  • 2 years
  • 1st Year Non Sponsored Semester Fee (Rs. in Lacs)
  • 0.72
  • 1st Year Sponsored Semester Fee (Rs. in Lacs)
  • 1.08
 
  • Fee Structure
  • Program Educational Objectives
  • Program Learning Outcomes
1st Year Non Sponsored Semester Fee (Rs. in Lacs) : 0.72
1st Year Sponsored Semester Fee (Rs. in Lacs) : 1.08
  • The student shall develop conceptual as well as applied knowledge and skills in the field of Bioinformatics, AI, neural networks and Data Science.
  • The student shall demonstrate strategic thinking for data analysis and development of solutions through Bioinformatics tools and techniques.
  • The student shall be able to use and apply latest technologies and tools to analyze and interpret complex biological problems through Machine learning algorithms and big data analytics.
  • The student shall be able to demonstrate innovative and sustainable approach in order to solve statistical problems and research projects.
  • The student shall be confident in interpersonal skills relationship-building and communication for industry and alumni.
  • The student shall be able to demonstrate team work and conflict resolution through leadership qualities.
  • The student shall be able to execute their knowledge and technical skills for the conferences, panel discussions, globalization and environmental conservation
  • The student shall be able to practice the ethical principles, IPR and understand their social responsibilities.
  • The student shall be able to develop innovative and creative decision making for various projects at national and international level in Bioinformatics.
  • The student shall be able to good managerial skills to enhance employment and entrepreneurship opportunities and able to create the virtue of lifelong learning.
  • The student will be a responsible global citizen with environment conserving attitude.
  • The student will demonstrate ethically, environmentally and socially aware attitude.
  • The student will principles of project management to manage one’s own work and/or project work as a member or a leader in a team, by work experience gathered through short term training / dissertation projects with proper statistical representation.
  • The student will have lifelong learning approach to create new knowledge from existing knowledge.
  • The student will develop technical mindset to find strategic solutions to diverse problem in bioinformatics data analytics.
  • The student will have decision making capabilities to find apt and sustainable solutions to complex biological problem.
  • The student will apply modern IT tools and Artificial Intelligence for acquisition and analysis of biological data.
  • The student will be able to demonstrate innovative and sustainable approach in order to solve statistical problems and research projects.
  • The student will be confident in communication, interpersonal skills and relationship-building.
  • The student will be able to demonstrate team work and conflict resolution strategies through leadership qualities

Course Structure

  • 1st Year

Semester 1

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Basics of Computational Biology (PG) Core Courses 3 0 0 0 3.00 View
Statistical Methods and Sas (PG) Core Courses 3 0 0 0 3.00 View
Advanced Genetics (PG) Core Courses 3 0 2 0 4.00 View
Molecular Cell Biology (PG) Core Courses 3 0 2 0 4.00 View
Biophysics and Structural Biology (PG) Core Courses 3 0 2 0 4.00 View
Computer Fundamentals and C Programming (PG) Core Courses 3 0 4 0 5.00 View

Semester 2

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Advanced Immunology (PG) Core Courses 3 0 2 0 4.00 View
Cloud Computing and its Applications (PG) Core Courses 4 0 0 0 4.00 View
Introduction to Hadoop and MapReduce (PG) Core Courses 3 0 2 0 4.00 View
Genome Organization and Analysis (PG) Core Courses 3 0 2 0 4.00 View
Clinical Data Management (PG) Specialisation Elective Courses 2 0 0 0 2.00 View
Insilico Systems Biology (PG) Specialisation Elective Courses 0 0 0 0 0.00 View
Relational Data Base Management System (PG) Specialisation Elective Courses 3 0 2 0 4.00 View
Data Structures Using C Language (PG) Specialisation Elective Courses 3 0 4 0 5.00 View