(M.Tech.) Master of Technology in Bioinformatics Syllabus - Amity Institute Of Biotechnology (AIB), Noida

  • Years 2 Years
  • Type Course Post Graduate
  • stream Engineering
  • Delivery Mode
  • university verified
Written By universitykart team | Last updated date Jul, 07, 2024

The Master of Technology (M.Tech.) in Bioinformatics syllabus at Amity Institute Of Biotechnology (AIB), Noida is designed to provide overall knowledge to the students with a strong foundation. Master of Technology (M.Tech.) in Bioinformatics faculty at Amity Institute Of Biotechnology (AIB) specially focus on in-depth learning to relevant subjects. At first semester syllabus of Master of Technology (M.Tech.) in Bioinformatics at Amity Institute Of Biotechnology (AIB), students learn the basics of programme. A strong foundation is very important for comprehensive learning. Master of Technology (M.Tech.) in Bioinformatics syllabus at Amity Institute Of Biotechnology (AIB), Noida maintains a balance between theoretical knowledge and practical knowledge.

Master of Technology (M.Tech.) in Bioinformatics first year students at Amity Institute Of Biotechnology (AIB) are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. Amity Institute Of Biotechnology (AIB), Noida also provides practical training sessions, workshops, projects, and case studies to enhance student skills. Master of Technology (M.Tech.) in Bioinformatics syllabus at Amity Institute Of Biotechnology (AIB), Noida is also frequently updated to give industry relevant training and knowledge to students. Amity Institute Of Biotechnology (AIB) strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at Amity Institute Of Biotechnology (AIB) enable Master of Technology (M.Tech.) in Bioinformatics students to apply knowledge and skills in a controlled environment and get required experience.

According to syllabus of Master of Technology (M.Tech.) in Bioinformatics progress, students learn advanced topics and complex concepts. The Master of Technology (M.Tech.) in Bioinformatics curriculum at Amity Institute Of Biotechnology (AIB), Noida mainly focuses on analytical and critical thinking. As the Master of Technology (M.Tech.) in Bioinformatics course unfolds, students develop several important skills that increases their employability. As per syllabus of Master of Technology (M.Tech.) in Bioinformatics at Amity Institute Of Biotechnology (AIB) also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.

Master of Technology (M.Tech.) in Bioinformatics curriculum at Amity Institute Of Biotechnology (AIB) includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The Master of Technology (M.Tech.) in Bioinformatics syllabus at Amity Institute Of Biotechnology (AIB) aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.

Additional curriculum at Amity Institute Of Biotechnology (AIB)

  1. Workshops and Seminars - Regular sessions with industry experts help Master of Technology (M.Tech.) in Bioinformatics students at Amity Institute Of Biotechnology (AIB) to stay updated with current trends.
  2. Group Projects - Collaborative projects according to Amity Institute Of Biotechnology (AIB) syllabus develop teamwork and problem-solving skills.
  3. Case Studies - Master of Technology (M.Tech.) in Bioinformatics syllabus offers analysis of real-world scenarios to apply theoretical knowledge.
  4. Extracurricular Activities - Amity Institute Of Biotechnology (AIB) offers several activities like sports, clubs, societies, etc. to encourage overall development.

Note: Given below syllabus is based on the available web sources. Please verify with the Amity Institute Of Biotechnology (AIB), Noida for latest Master of Technology (M.Tech.) in Bioinformatics curriculum.

Syllabus & Subjects of Master of Technology in Bioinformatics

The Master of Technology (M.Tech) program in Bioinformatics is at the intersection of biology, computer science, and data analysis. It's a field dedicated to harnessing the power of computational tools and techniques to understand complex biological systems, analyze biological data, and make significant contributions to various domains such as genomics, proteomics, and drug discovery. The syllabus for this program is meticulously designed to equip students with the knowledge and skills required to work on cutting-edge research and applications in the field of bioinformatics. From molecular biology to statistical analysis, this program covers a wide range of subjects that enable students to tackle the challenges of the rapidly evolving life sciences industry.

Four semesters form the duration of the two-year M.Tech in Bioinformatics program. A distinct syllabus is used for each semester. The topics for each semester of the M.Tech in Bioinformatics are listed below:

Semesters Subjects
Semester I Algorithms for Bioinformatics
Advanced Biochemistry and Immunology
Bioinformatics - Techniques and Applications
Numerical and Biostatistical Methods
Elective-I
Semester II Applications of Mat-lab in Bioinformatics
Functional Genomics and Proteomics
Structural Bioinformatics
Elective-II
Semester III Seminar / Industrial Training
Project Work - Phase I
Elective-III
Semester IV Project Work - Phase II
Elective-IV
Elective-V
Elective Subjects Advanced Biology
Metabolic Engineering
Computational Chemistry
Microarray Bioinformatics
Macromolecular Biophysics
Molecular Mechanics and Simulation
Systems Biology - Models and Approaches
Unix & Java
Computer-Aided Drug Designing
Molecular Dynamics
Perl for Bioinformatics
Python for Bioinformatics

Projects

To better understand how machine learning is used in healthcare, particularly bioinformatics, here are five fascinating projects.

(i). Bioinformatics and Security: Discover data management practices and security protocols in the bioinformatics research and industry

(ii). Commercialization of Bioinformatics Research: Identifying potential commercial applications of bioinformatics research results and developing a plan for their successful commercialization.

(iii). Bioinformatics Workflow Optimization: Analyses existing bioinformatics workflows and identify areas for optimization and performance improvement. Develop strategies and tools to improve data analysis, streamline computational processes, and increase overall productivity in bioinformatics research.

(iv). Introduction of Artificial Intelligence (AI) in Bioinformatics: Exploring the Impact of Artificial Intelligence and Machine Learning Techniques on Bioinformatics Research and Applications. Assess the challenges and opportunities of integrating AI into existing workflows and develop strategies for successful adoption.

(v) Bioinformatics Compliance: Examines regulatory frameworks and compliance requirements for bioinformatics, such as privacy, data protection, and intellectual property rights. Develop policies and guidelines to ensure compliance with regulatory standards and reduce legal risks in bioinformatics projects

(vi). Ethical Issues in Bioinformatics: Examine ethical issues related to bioinformatics research and applications, such as B. Confidentiality, data ownership, and potential discrimination issues. Develop a framework or guidelines for ethics and practices in bioinformatics projects.

(vii)Technology Transfer and Commercialization of Academic Research: Learn strategies for effective technology transfer and commercialization of bioinformatics research conducted by academic institutions.

Reference Books

M.Tech in Bioinformatics books provide students with both a thorough general review of the subject matter and a close examination of their specific area of expertise. The following are some of the books for reference:

Name of Author Name of Book
David W. Mount Bioinformatics: Sequence and Genome Analysis
Arthur M. Lesk Introduction to Bioinformatics
Phillip Compeau and Pavel Pevzner Bioinformatics Algorithms: An Active Learning Approach
Marketa J. Zvelebil and Jeremy O. Baum Understanding Bioinformatics
Michael Agostino and Peter Sterk Practical Bioinformatics
S. R. Gautam Bioinformatics: Approaches and Applications
Ralf Blossey Computational Biology: A Statistical Mechanics Perspective
R. Duraiswamy and G. Muralidharan Computational Biology
Des Higgins and Willie Taylor Bioinformatics: Sequence, Structure, and Databanks: A Practical Approach



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