The purpose of MS degree program in Bioinformatics is to provide the students with an advanced knowledge of computational biology, bioinformatics and biodata science. This program provides training to decipher the biological processes with the help of modern computational tools and information technology.
Bioinformatics is an emerging scientific discipline with highly remunerative career options. The career prospect in Bioinformatics has been gradually increasing with the use of information technology in the area of molecular biology. Bioinformatics degree holder can work in biomedical organizations, biotechnology institutions, research centers, hospitals, academics, pharmaceutical industries etc. Specific career areas which fall within the scope of this field are database design & maintenance, proteomics, pharmacology, sequence assembly & analysis, informatics, biodata science, clinical pharmacologist and others.
PROGRAM EDUCATIONAL OBJECTIVES (PEOs)
| PEO-1 | The graduates will be able to lead development and usage computer applications for solving biological problems and analyzing biological data in industry and academia. |
| PEO-2 | The graduates will be able tackle problems in various industries such as pharmaceutical, biotechnology, biodata science-based software houses. |
| PEO-3 | The graduates will undertake problem-based research on biological data. |
PROGRAM LEARNING OBJECTIVES (PLOs)
| PLO-1 | Knowledge |
Possess the core concepts of Bioinformatics and computational biology |
| PLO-2 | Problem Analysis |
Develop critical thinking and have research methods in Bioinformatics. |
| PLO-3 | Design and Development Solutions |
Design and implement research Projects by using bioinformatics skills to predict functions from structures, networks complexes, transcriptome and proteome data. |
| PLO-4 | Investigation |
Analyze efficient and reliable bioinformatics solutions by optimizing the usage of existing tools and developing new ones when needed. |
| PLO-5 | Modern Tool Usage |
Be able to use the existing tools of computational biology to analyze biological data. |
| PLO-6 | Professional attitude |
Be aware from the technologies for modern high-throughput DNA sequencing and their applications. |
ADMISSION REQUIREMENTS
- ELIGIBILITY CRITERIA FOR ADMISSION
- 16 years qualification e.g. BS (4 years) or M.Sc. in Biological Sciences, Computer Sciences and Physical sciences or other related subjects or medical graduates (MBBS/DVM/BDS) or Pharm D. with the minimum GPA of 2.0 or equivalent.
- SELECTION CRITERIA
- MAJU Admission Test/NTS GAT
- Interview
DEGREE REQUIREMENTS
For MS Bioinformatics degree, it is required to successfully complete 30 credit hours with minimum CGPA of 2.5 on scale of 4.0. Completion of defined Research. The course details are mentioned below:
| AREA | Cr. Hrs. |
|---|---|
| Core Courses | 12 |
| Electives | 12 |
| Research Thesis | 06 |
DURATION
MS Bioinformatics is two years program comprising of 4 semesters. Each year is comprised of a Fall and a Spring semester. The maximum duration to complete MS in Bioinformatics is 4 years.
Core Courses (06 Cr. Hrs.)
| Course Title | Course Code | Cr. Hrs. |
| Bioinformatics | BI5010 | 3 |
| Biostatistics | BI5020 | 3 |
| Machine Learning | CS5640 | 3 |
| Bioentrepreneurship | BI6030 | 3 |
Elective Courses (12 Cr. Hrs.)
| Course Title | Course Code | Cr. Hrs. |
| Advances in Cell & Molecular Biology | BT5060 | 3 |
| Genomic Medicine | BI5015 | 3 |
| Advances in Proteomics | BI5011 | 3 |
| Machine Learning | CS5640 | 3 |
| Information Extraction | CS7610 | 3 |
| Information Processing Techniques | BI5013 | 3 |
| Deep Learning | CS6650 | 3 |
| Artificial Intelligence | CS3310 | 3 |
| Advanced Research Methods | CS5110 | 3 |
| Advanced analysis of Algorithms | CS5510 | 3 |
| Applied Programming | CS6420 | 3 |
Research Thesis/Project (06 Cr. Hrs.)
| Course Title | Course Code | Cr. Hrs. |
| Research Thesis-I | BI5040 | 3 |
| Research Thesis-II | BI5050 | 3 |
SCHEME OF STUDIES
Semester 1
| Course Title | Course Code | Cr. Hrs. |
| Advanced Bioinformatics | BI5010 | 3 |
| Advanced Biostatistics | BI5020 | 3 |
| Machine Learning | CS5640 | 3 |
Semester 2
| Course Title | Course Code | Cr. Hrs. |
| Bioentrepreneurship | BI6030 | 3 |
| Electives-I | XXXXXX | 3 |
| Electives-II | XXXXXX | 3 |
Semester 3
| Course Title | Course Code | Cr. Hrs. |
| Research Thesis-I | BI5040 | 3 |
| Electives-III | XXXXXX | 3 |
Semester 4
| Course Title | Course Code | Cr. Hrs. |
| Research Thesis-II | BI5050 | 3 |
| Electives-IV | XXXXXX | 3 |