Science - Biochemistry-Computational-Biology-Track

Chairperson: Prof. Mahmoud Khalil

Associate Professors: Dr. Jamilah Borjac, Dr. Dalia El Badan

Assistant Professors: Dr. Ghada Khawaja, Dr. Rana El Hajj, Dr. Nawal Hakawaty, Dr. Noura Abu Zeinab

Part-Time Lecturers: Dr. Zeina Soayfane, Dr. Safaa Baydoun, Prof. Mazen Kurdy

The mission of the Computational Biology Track program is to provide students with a strong interdisciplinary foundation in both biological and computational sciences. Graduates will be equipped with the skills needed to analyze biological data, build complex biological systems using updated computational approaches. This curriculum also develops the scientific and technological skills needed by the students to excel in various careers. By providing the opportunities for the students to engage in biological and computational approaches, they will be prepared for employment in technological, research and academic institutions.

The Computational Biology track:

• Provides undergraduate students with knowledge and understanding of biological concepts and principles.
• Offer in-depth knowledge in bioinformatics.
• Provides an opportunity for the students to earn and apply the theoretical knowledge of computational biology and address the real-world biological challenges.
• Provide students with a strong foundation of the fundamental principles in biology and computer science.
• Equip students with the proficiency in programming languages and computational techniques, and integrate them in Biology.
• Prepares students for career options in computational biology, bioinformatics, and related fields.
• Develops the critical thinking abilities of students and foster the learning experience.
• Promotes the capacity for continuous lifelong learning within the rapidly-evolving field of computational biology.

a- Knowledge and understanding:

1. Develop critical thinking skills by implementing the scientific method through bioinformatics data analysis.
2. Explain and complete simple applications of the computational biology methods used for DNA, RNA, and protein analysis.
3. Understand the central dogma of biology and the tools needed for the high throughput biological next-generation sequencing proteomics datasets can help answer fundamental questions about the biology of DNA, RNA, and proteins.
4. Define systems biology and explain its importance in understanding biology; undertake basic data analyses in systems biology.
5. Identify common formats for biological data and be able to convert among different formats
6. Identify the modelling and optimization of those programming languages most commonly used in the field of Life Sciences, so as to develop and evaluate techniques and/or computational tools.
7. Integrate omics and clinical data for a better understanding of biological phenomena.
8. Accredit appropriate knowledge, skills and practices in the areas of organism and biosystems biology.

b- Intellectual abilities:

1. Apply reasoning about core biological concepts with emphasis on the cellular and molecular scale of biology.
2. Demonstrate comprehension of basic concepts of biological literacy.
3. Interpret computational biology analyses individually and in collaborative learning environments.
4. Apply mathematical foundations, algorithmic principles and theories of computer science within the modelling and design of biological systems.
5. Apply computational methods to solving problems in the ambits of molecular biology, genomics and medical and population genetics research.
6. Demonstrate the ability to pursue further education as independent professional learning.

c- Professional and Practical Competencies:

1. Analyze and evaluate bioinformatics data to discover patterns, critically evaluate conclusions and generate predictions for subsequent experiments.
2. Design, implement and evaluate computer-based systems, processes, components or programs in relation to the contexts of molecular and cellular biology and genomics research.
3. Acquire a knowledge of biology from the scale of the cellular through to the organism, with an interdisciplinary vision and with special emphasis placed on biomedical applications.
4. Manage and exploit all types of biological and biomedical information to transform this into knowledge.

d- General and transferable skills:

1. Work effectively autonomously or collaboratively within a team.
2. Communicate information relating to computational biology in both written and oral forms.
3. Develop written and oral communication skills that are crucial to articulating research goals and reporting research results.
4. Develop computational skills relevant to solving problems in biology.
5. Develop relevant skills in math, statistics and biology that enable success in the field of computational biology.
6. Develop analytical skills that will allow them to identify important problems in computational biology and to identify solutions.
7. Participate in the development of a computational biology research project, defending both the current state of the question in hand and possible strategies for carrying it out.
8. Work competently in a group on biological concepts in relation to computational biology and bioinformatics.
9. Summarize fundamental bioinformatics software tools, know when to apply them, and be able to use them.

To obtain the bachelor’s degree in Computational biology, students must successfully complete a total of 97 credit hours and obtain an Internet and Computing Core Certification (IC3), where the standard study duration is 6 semesters.

1. Bioinformatics analyst in a research institution, University, laboratory, pharmaceutical company: to analyse biological data such as DNA sequencing.
2. Biostatistician.
3. Software Developer in companies.
4. Data analyst in research institutions.
5. Consultant in research organizations and pharmaceutical companies.

Faculty and Major Core Courses: 

5 credits are selected from the University Mandatory courses list.

At least one course from social sciences and one course from humanities should be selected among the university elective courses.

Faculty and Major Core Courses: 

Computational Biology Track Courses: