BS. COMPUTATIONAL BIOLOGY
INTRODUCTION
Making sense of advances in bioinformatics, sequenced microbial genomes, personalized medicine, improvements in nutrition, gene therapy progress, biomedical science and of the knowledge explosion in domains such as genetics, drug design, neuroscience, and environmental health requires both a sophisticated understanding of biological questions and powerful analytical tools to solve them. The integrated discipline of computational biology represents the application of modern computer science, statistics, and mathematics to exploring biological and biomedical problems. The Department of Biomedical Engineering in the Faculty of Engineering, Sciences, Technology and Management at Ziauddin University offers BS program in Computational Biology. This state-of-the-art program strengths in computer science and biology with the strong tradition of interdisciplinary research at Ziauddin University into a unique training program in this emerging field.
PROGRAM EDUCATIONAL OBJECTIVES (PEOs)
PEO-1 The graduates will show progress in the field of computational biology by expanding their expertise and skills.
PEO-2 The graduates would be able to contribute effectively to the industry by using the required technical skills.
PEO-3 The graduates will be committed to ethical ideals and will make a meaningful contribution to society.
PROGRAM LEARNING OUTCOMES (PLOs)
PLO-1 Knowledge: An ability to apply fundamental and specialized knowledge of computational biology to the solution of complex biological problems.
PLO-2 Hypothesis Formulation: An ability to identify, formulate, research literature, analyse complex biological problems, reaching substantiated conclusions towards formulation of hypothesis using fundamental principles of computational biology.
PLO-3 Experiment/ Process Design: An ability to design experimental solutions to validate computational biology Hypothesis and design process while maintaining biosciences standards, cultural, societal, and environmental considerations.
PLO-4 Investigation: An ability to investigate complex issues in computational biology in a methodical way including literature survey, and development of systems, analysis and interpretation of experimental data, and synthesis of information to derive valid conclusions.
PLO-5 Modern Tool Usage: An ability to select and apply appropriate techniques, resources, and modern tools, including prediction and modelling, to complex biosciences activities, with an understanding of the limitations.
PLO-6 Impact Analysis : An ability to apply reasoning informed by contextual knowledge to assess societal, legal and cultural issues and the consequent responsibilities relevant to professional computational biology practice and solution to complex problems.
PLO-7 Management Skills An ability to demonstrate management skills and apply computational biology principles to one’s own work, as a member and/or leader in a team, to manage projects in a multidisciplinary environment.
PLO-8 Team Work: An ability to work effectively, as an individual or in a team, on multifaceted and /or multidisciplinary settings.
PLO-9 Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of computational biology practice.
PLO-10 Communication: An ability to communicate effectively, orally as well as in writing, on complex computational biology activities with the computational biology community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
PLO-11 Lifelong Learning: An ability to recognize importance of, and pursue lifelong learning in the broader context of innovation and technological developments.
PLO 12: Project Management: An ability to engage in lifelong learning for technological change and will be able to manage independent research projects.
ELIGIBILITY CRITERIA
FSC in (Pre-medical / Pre-engineering / Computer Science)
OR
DAE
OR
A-Levels
OR
Equivalent
Applicants are required to appear in written test and interview.
BS Computational Biology Curriculum
Semester-I | |
Course code | Subjects |
HS 104 | Functional English (3+0) |
HS 101 HS 102 | Islamic Studies / Ethics (2+0) |
NS 105/ NS 104 | Basic Mathematics(pre-calculus)/ Basic Biology (3+0) |
BT 101 | Ecology, Biodiversity and Evolution (3+0) |
BT 105 | Organic Chemistry (2+1) |
CS 101 | Introduction to Computing (2+1) |
Total 15+2=17 |
Semester-II | |
Course code | Subjects |
Introduction to computational Biology (3+0) | |
Pakistan Studies (2+0) | |
HS 107 | Psychology (3+0) |
BT 120 | Inorganic Chemistry (2+1) |
NS 101 | Physics (2+1) |
BT 110 | Cell Biology (2+1) |
Total 14+3=17 |
Semester-III | |
Course code | Subjects |
HS 112 | Communication Skill (2+0) |
HS 231 | Sociology (3+0) |
BT 205 | Physical Chemistry (3+0) |
BT 216 | Biomathematics (3+0) |
BT 202 | Biochemistry-I (2+1) |
CS-201 | Object Oriented Programming (2+1) |
Total 15+2=17 |
Semester-IV | |
Course code | Subjects |
History of Computing (2+0) | |
NS 212 | Probability & Biostatistics (3+0) |
BT 207 | Immunology (3+0) |
CS-202 | Data Structure and Algorithms (2+1) |
BT 225 | Classical Genetics (2+1) |
BT 230 | Molecular Biology (3+0) |
Total 16+2=17 |
Semester-V | |
Course code | Subjects |
BT 326 | Biochemistry-II (3+0) |
HS 222 | Technical Report writing (3+0) |
CS-301 | Discrete Structures (2+1) |
CS-302 | Database Management Systems (2+1) |
BM 348 | Introduction to Bioinformatics (2+1) |
Total 11+4=15 |
Semester-VI | |
Course code | Subjects |
BI-302 | Fundamental of Bioinformatics Programming (2+1) |
Design and analysis of algorithms (2+1) | |
Bio-303 | Molecular Modelling of Proteomics (2+1) |
CS-304 | Graphics and Visualization (2+1) |
Elective-I (3+0) | |
BT 351 | Research Methodology and Skill Enhancement (3+0) |
Total 15+3=18 |
Semester-VII | |
Course code | Subjects |
CS-401 | Artificial Intelligence (2+1) |
BT 413 | Seminar-I (1+0) |
Enzyme Kinetics (3+0) | |
Genomics (3+0) | |
Elective-II (3+0) | |
BT 489 | Research Project/Internship or Special Paper-I (3+0) |
Total 15+1=16 |
Semester-VIII | |
Course code | Subjects |
Elective -III (3+0) | |
Elective -IV (3+0) | |
Methods in protein modeling (2+1) | |
BI-202 | Ethical and Legal Issues in Bioinformatics (3+0) |
BT 489 | Research Project/Internship or Special Paper-II (3+0) |
Total 13+1=15 | |
Total 115 + 18 = 133 |
List of Electives of BS Computational Biology
- Human Computer Interaction
- Nanotechnology
- Environmental Biotechnology
- Tools and Techniques in Genetic Engineering
- Immuno-Informatics
- Microbial genomics and proteomics
- Network Biology
- Biophysics
- Statistical methods in bioinformatics
- Epigenetics and gene regulation
- Protein chemistry
- Microbial genetics
- Molecular oncology